Istag reports. retrieved from ict research in fp7, 2011.

K. Ducatel, M. Bofdanowicz, F. Scapolo, J. Leijten, and J.-C. Burgelman. Scenarios forn ambient intelligence, 2010.

D. Reilly. An jini-based infrastructure for networked appliance management and adapta- tion. In Valerie Barr and Zdravko Markov, editors, Networked Appliances, 2002.

Liverpool. Proceedings. 2002 IEEE 5th International Workshop on, pages 161– 167. Sch. of Comput. & Math. Sci., Liverpool John Moores Univ., UK, 2002.

Istag reports. retrieved from ict research in fp7, 2011.

K. Ducatel, M. Bofdanowicz, F. Scapolo, J. Leijten, and J.-C. Burgelman. Scenarios forn ambient intelligence, 2010.

D. Reilly. An jini-based infrastructure for networked appliance management and adapta- tion. In Valerie Barr and Zdravko Markov, editors, Networked Appliances, 2002.

Liverpool. Proceedings. 2002 IEEE 5th International Workshop on, pages 161– 167. Sch. of Comput. & Math. Sci., Liverpool John Moores Univ., UK, 2002.

M. Leelaprute, P.and Nakamura, T.; Tsuchiya, K. Matsumoto, and T. Kikuno. Describing and verifying integrated services of home network systems’. In Proceedings of the 12th Asia-PacificSoftware Engineering Conference 2005. APSEC ’05., 2005.

Youth in europe, a statistical portrait, 2009.

Samsung pushes boundaries at ces 2012, 2012.

C. Dixon, R. Mahajan, S. Agarwal, AJ . Brush, B. Lee, S. Saroiu, and V. Bahl. An Operating System for the Home, 2012.

Home security systems, home security products, home alarm systems, 2012.

Home automation, building and campus control., 2012.

J. Krumm, S. Harris, B. Meyers, B. Brumitt, M. Hale, and S. Shafer. Multi-Camera Multi-Person Tracking for EasyLiving. In IEEE Workshop on Visual Surveillance, 2000.

J. Wu, A. Osuntogun, T. Choudhury, M. Philipose, and J. M. Rehg. Scalable Approach to Activity Recognition based on Object Use. In International Conference on Computer Vision, 2007.

QUIVICON. Vernetzen, steuern, kontrollieren, geniessen.

X. Xuemei, L .and Gang. Service oriented framework for modern home appliances. In CCCM, editor, Computing, Communication, Control, and Management, 2008.

ISECS International Colloquium on, pages 700–703. Sch. of Comput. & Math. Sci., Liver- pool John Moores Univ., UK, 2008.

J.R.Velasco,I.Marsa-Maestre,A.Navarro,M.A.Lopez-Carmona,A.J.deVicente,E.dela Hoz, A. Paricio, and M. Machuca. Location-aware services and interfaces in smart homes using multiagent systems. In PSC’05, pages 104–110, 2005.

Telecom Italia Lab. Java Agent Development Framework., 2010. Android apocalypse, 2010.

N.R. Clifton. Easier Housework By Better Equipment. London: Country Life Ltdl, 1929.

C. Nold and R. Van Kranenburg. The internet of people for a possible word, volume Situated technologies panphlet 8. The architectural league of New York., 2011.

S. Kyffin. Lessons learned., 2010.

J. Surowiecki. Mirror, Mirror: The Importance of Looks in Everyday Life. Albany: State Univ. NY Press, 1986.

Luigi Atzori, Antonio Iera, Giacomo Morabito, and Michele Nitti. The social internet of things (siot). when social networks meet the internet of things: Concept, architecture and network characterization. Computer Networks, 56(16):3594 – 3608, 2012.

Herbert S. Dordick. America calling: A social history of the telephone to 1940 by claude s. fischer university of california press, berkeley, ca, 1992, 424 pp, 25.00. Telecommunications Policy, 17(5):397 – 398, 1993.

ROBERT HUGHES and JASON D. HANS. Computers, the internet, and families: A review of the role new technology plays in family life. Journal of Family Issues, 22(6): 776–790, 2001.

M. Lea and R. Spears. Love at first byte? Building personal relationships over computer networks, pages 197–233. Understudied Relationships: Off the Beaten Track. Thousand Oaks, CA: Sage, 1995.

P.B. OO ̃Sullivan. A match made in cyberspace: interpersonal communication theory and interpersonal communication technology. In International Communication Association’s annual conference. Chicago (Interpersonal Communication Division), 1996.

R. Cathcart and G. Gumpert. Mediated interpersonal communication: toward a new typology. Quarterly Journal of Speech, 69:267277, 1983.

T.R. Tyler. Is the internet changing social life? it seems the more things change, the more they stay the same. Journal of Social Issues, 58:195–205, 2002.

J.A. Bargh and KYA McKenna. The internet and social life. ANNUAL REVIEW OF PSYCHOLOGY, 55:573–590, 2004.

L. Atzori, A. Iera, and G. Morabito. The internet of things: A survey. Computer Networks, 54(15):2787–2805, 2010.

E. Flaspoler, A. Hauke, and R. O. D Beeck. Literature review: The human-machine interface as an emerging risk, 2007.

L.W. PBarsalou. Perceptual symbol systems. Behavioral and Brain Sciences, 22:577–609, 1999.

G. Lakoff and M. Johnson. Philosophy in the Flesh. The Embodied Mind and its Challenge to Western Thought. C Basic Books, New York, 1999.

A. Sloman. How many separately evolved emotional beasties live within us? In R. Trappl, P. Petta, and S. Payr, editors, FEmotiom in Humans and Artifacts, Cambridge, MA., 2003. MIT Press.

D.A. Norman, A. Ortony, and D.M. Russell. Affect and machine design: lessons for the development of autonomous machine. IBM Systems Journal, 42(1):38–43, 2003.

V. Gallese. Being like me: self-other identity, mirror neurons and empathy. In S. Hurley and N. Chater, editors, Perspectives on Imitation: From Cognitive Neuroscience to Social Science, Boston, MA., 2005. MIT Press.

M.E. Bratman. What is intention? In P.R. Cohen, J. Morgan, and M. E. Pollack, editors, Intention in Communication, Cambridge, MA., 1990. MIT Press.

B. J. OKeefe and L. Lambert. Managing the flow of ideas: A local management approach to message design. In B.R. Burleson, editor, Communication Yearbook 18, Sage,CA, 1995. Thousand Oaks.

J. O. Greene. Message production: Advances in Communication Theory. Erlbaum, Mah- wah,N.J., 1997.

R. Ciceri. Mother/infant communicative complex system: Analysis of interactive, attuned behavioural patterns from 2 to 7 months. In ISSBD, 18th Biennal Meeting, pages 301–305, Ghent, 2004.

H. Giles, C. A. Shepard, and B.A. Le Poire. Communication accommodationtheory. In W. P. Robinson and H. Giles, editors, The new handbook of language and social psychology, pages 33–56, Chichester, UK, 2001. Wiley.

M.D. Lewis. Bridging emotion theory and neurobiology through dynamic systems modeling, Behavioral and Brain Sciences. Cambridge University Press, New York, 2004.

C. Darves and S. Oviat. Adaptation of users’ spoken dialogue patterns in a conversational interface. In J. Hansen and B. Pellom, editors, Proceedings of the International Conference on Spoken Language Processing (ICSLP’2002), volume 1, pages 561–564, Denver, CO, 2004. Casual Prod. Ltd.

R. Coulston, S. Kumar, and P. R. Cohen. Multimodal interaction under exerted condi- tions in a natural field setting. In Proceedings of the Sixth International Conference on Multimodal Interfaces (ICMI 2004), pages 14–15, Pennsylvania, USA, 2004.

F. Sebe, J.M. Mateo-Sanz, and J. Domingo-Ferrer. Adaptation of users’ spoken dialogue patterns in a conversational interface. In Ferrer J.D. and V. Torra, editors, Privacy in Statistical Databases, volume 3050, pages 201–215, Berlin Heidelberg, 2004. Springer.

M. Slater, M. Usoh, and A. Steed. Depth of presence in virtual environments. Presence: Teleoperators and Virtual Environments, 3(2):130–144, 2003.

R. W. Picard, E. Vyzas, and J. Healey. Toward machine emotional intelligence: anal- ysis of affective physiological state. IEEE Transactions Pattern Analysis and Machine Intelligence, 23(10):1185–1191, 2001.

R. Cowie, E. Douglas-Cowie, N. Tsapatsoulis, G. Votsis, S. Kollias, and J. G. Fellenz, W. andTaylor. Emotion recognition in human-computer interaction. IEEE Signal Process, 18:32–80, 2001.

C. Breazeal and L. Aryananda. Recognizing affective intent in robot directed speech. Autonomous Robots, 12(1):83–104, 2002.

C. Breazeal and L. Aryananda. Intelligent affective interfaces: a patient-modelling assess- ment for tele-home health care. International Journal of Human-Computer Studies, 59: 245–255, 2003.

F. Sebe, J.M. Mateo-Sanz, and J. Domingo-Ferrer. Appraisal considered as a process of multilevel sequential checking. In R. Scherer, K., A. Schorr, and T. Johnstone, editors, Pri- vacy in Statistical Databases, volume 14, pages 478–501, London, 2001. Oxford University Press.

C. M. Van Reekum, T. Johnstone, R. Banse, A. Etter, T. Wehrle, and K.R. Scherer. Psycho physiological responses to appraisal dimensions in a computer game. Cognition Emotion, 18(5):663–688, 2004.

Sandia National Laboratory. Cognitive science & applications, 2008.

M. Pantic, N. Sebe, J. Cohn, and T. Huang. Affective multimodal human-computer inter- action. In Proceedings of the 13th annual ACM international conference on Multimedia, Singapore, 2005.

W. Pedrycz. Granular computing in data mining. In M. Last and A. Kandel, editors, Data Mining & Computational Intelligence, Physica-Verlag, Studies in Fuzziness and Soft Computing, Vol. 68. Springer-Verlag, 2001

D.E. Rumelhart, J.L. McClelland, and the PDP Research Group . Parallel Distributed Processing: Explorations in the Microstructure of Cognition. MIT Press, Cambridge, MA, 1986.

A. Kamilaris and A. Trifa, V.and Pitsillides. The Smart Home meets the Web of Things. Int. J. of Ad Hoc and Ubiquitous Computing, pages 1–12, 2010.

J. Jacobson. Do We Really Need a Home Automation Standard?, 2010.

N. Kawaguchi. Plug and play technologies and ubiquitous computing, 2008.

Luigi Atzori, Antonio Iera, and Giacomo Morabito. The internet of things: A survey. Comput. Netw., 54(15):2787–2805, October 2010.

C.L. Wu, C.F. Liao, and L.C. Fu. Service-Oriented Smart-Home Architecture Based on OSGi and Mobile-Agent Technology. Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on, (2):193–205, 2007.

Luigi Atzori, Antonio Iera, and Giacomo Morabito. Siot: Giving a social structure to the internet of things. IEEE Communications Letters, 15(11):1193–1195.

Myhome automation:the functions, 2012.

Dematronics technologies. La domotica, 2010.

Andreas Pitsillides Andreas Kamilaris, Vlad Trifa. HomeWeb: An Application Framework for Web-based Smart Homes. 978-1-4577-0024-8/11 IEEE, 2011.

UPnP forum, 2012.

Echonet Consortium. Echonet lite overview, 2012.

Apache river, 2012.

Home technology resources, 2012.

The worldwide STANDARD for home and building control, 2012.

J. Jacobson. Do We Really Need a Home Automation Standard?, 2010.

D.S. Kim, G.Y. Cho, W.H. Kwon, Y.I.K Wan, and Y.H. Kim. Home network message specification for white goods and its applications. IEEE Transactions on, 2002.

Siemens. SIMATIC WinCC Recipes, 2012. [80] L. KTerrenghi. Computing technologies in the kitchen: The living cookbook as a design mindful cooking experiences. Material Culture Review, 2009.

Xie Li. The design and implementation of home network system using osgi compliant middleware. Consumer Electronics, IEEE Transactions on, 50(2):528 – 534, 2004.

Association of Home Appliance Manufacturers. Assessment of Communication Standards for Smart Appliances:The Home Appliance IndustryO ̃s Technical Evaluation of Commu- nication Protocols, 2010.

URIs, URLs, and URNs: Clarifications and Recommendations 1.0, 2012. [84] N. B Priyantha, A. Kansal, M. Goraczko, and ZhaoF. Tiny web services: design and implementation of interoperable and evolvable sensor networks. (SenSys) ACM, 2008.

C. Groba and S. Clarke. Web services on embedded systems - a performance study. (PERCOM Workshops) IEEE, 2010.

N. Zosol. RESTful Web Services, 2008.

L. Schor, P. Sommer, and R. Wattenhofer. Towards a Zero-Configuration Wireless Sensor Network Architecture for Smart Buildings. (BuildSys Workshops) ACM, 2010.

D. Yazar and A. Dunkels. Efficient Application Integration in IP-based Sensor Networks. (BuildSys Workshops) ACM, 2009.

M. Kovatsch, M. Weiss, and D. Guinard. Embedding Internet Technology for Home Au- tomation. (ETFA) IEEE, 2010.

E. Wilde. Putting things to REST. Technical report, Technical Report UCB iSchool Report, 2007.

D. Guinard and V. Trifa. Towards the Web of Things: Web Mashups for Embedded Devices. (Workshop on Mashups)Enterprise Mashups, 2009.

D. Guinard and V. Trifa. Towards the Web of Things: Web Mashups for Embedded Devices. (Workshop on Mashups)Enterprise Mashups, 2009.

W. Drytkiewicz, I. Radusch, S. Arbanowski, and R. Popescu-Zeletin. pREST: a REST- based protocol for pervasive systems. (Conference on Mobile Ad-hoc and Sensor Sys- tems)IEEE, 2004

K. Sanghai. Building Complex VDK/LwIP Applications Using Blackfin Processors. Analog Devices Inc., 2008.

John Day. Patterns in Network Architecture: A return to Fundamentals. Prentice Hall, New Jersey, 2007.

IRATI FP7 Project. IRATI Investigation RINA as an Alternative to TCP/I, 2013.

IETF. Uniform Resource Identifier (URI): Generic Syntax, 2005.

Damon Horowitz and Sepandar D. Kamvar. Searching the village: models and methods for social search. Commun. ACM, 55(4):111–118, April 2012.

Luigi Atzori, Antonio Iera, Giacomo Morabito, and Michele Nitti. The social internet of things (siot) – when social networks meet the internet of things: Concept, architecture and network characterization. Computer Networks, 56:3594–3608, 2012.

Susan D. Greenbaum and Paul E. Greenbaum. The ecology of social networks in four urban neighborhoods. Social Networks, 7(1):47 – 76, 1985.

Darren P. Croft, Joah R. Madden, Daniel W. Franks, and Richard James. Hypothesis testing in animal social networks. Trends in Ecology & Evolution, 26(10):502 – 507, 2011.

Anindita Bhadra, Ferenc Jordan, A. Sumana, Sujata A. Deshpande, and Raghavendra Gadagkar. A comparative social network analysis of wasp colonies and classrooms: Linking network structure to functioning. Ecological Complexity, 6(1):48 – 55, 2009.

Jan Kratzer, Roger Th.A.J. Leenders, and Jo M.L. van Engelen. A social network perspec- tive on the management of product development programs. The Journal of High Technology Management Research, 20(2):169 – 181, 2009.

Sue Oreszczyn, Andy Lane, and Susan Carr. The role of networks of practice and webs of influencers on farmers’ engagement with and learning about agricultural innovations. Journal of Rural Studies, 26(4):404 – 417, 2010.

Amateur Radio Social Network.

Erik Jippes, Marjolein C. Achterkamp, Paul L.P. Brand, Derk Jan Kiewiet, Jan Pols, and Jo M.L. van Engelen. Disseminating educational innovations in health care practice: Training versus social networks. Social Science & Medicine, 70(10):1509 – 1517, 2010.

Isabel Rodriguez-Tejedo, Sonia Lara, Marta Zarraga-Rodriguez, and Victoria Rodriguez- Chacon. An assessment of the impact of social networks on collaborative learning at college level. Procedia - Social and Behavioral Sciences, 47(0):1616 – 1621, 2012.

Cyprus International Conference on Educational Research (CY-ICER-2012) North Cyprus, US08- 10 February, 2012.

G.Fischer.Usermodelinginhuman–computerinteraction.Usermodelinganduser-adapted interaction, 11(1):65–86, 2001.

A. Kobsa. Generic user modeling systems. User modeling and user-adapted interaction, 11 (1):49–63, 2001.

A. Cooper. The inmates are running the asylum, volume 1. 2004. J. Pruitt and J. Grudin. Personas: practice and theory. In Proceedings of the 2003 con-

ference on Designing for user experiences, pages 1–15. ACM, 2003.

J.P. Djajadiningrat, WW Gaver, and JW Fres. Interaction relabelling and extreme charac- ters: methods for exploring aesthetic interactions. In Proceedings of the 3rd conference on Designing interactive systems: processes, practices, methods, and techniques, pages 66–71. ACM, 2000.

P.T.A. Junior and L.V.L. Filgueiras. User modeling with personas. In Proceedings of the 2005 Latin American conference on Human-computer interaction, pages 277–282. ACM, 2005.

S. Amershi and C. Conati. Unsupervised and supervised machine learning in user modeling for intelligent learning environments. In Proceedings of the 12th international conference on Intelligent user interfaces, pages 72–81. ACM, 2007.

G.I. Webb, M.J. Pazzani, and D. Billsus. Machine learning for user modeling. User modeling and user-adapted interaction, 11(1):19–29, 2001.

L.L. Constantine and L.A.D. Lockwood. Usage-centered engineering for web applications. Software, IEEE, 19(2):42–50, 2002.

J. Hong, E.H. Suh, J. Kim, and S.Y. Kim. Context-aware system for proactive personalized service based on context history. Expert Systems with Applications, 36(4):7448–7457, 2009.

A. Zimmermann, M. Specht, and A. Lorenz. Personalization and context management. User Modeling and User-Adapted Interaction, 15(3):275–302, 2005.

M. Raento, A. Oulasvirta, R. Petit, and H. Toivonen. Contextphone: A prototyping platform for context-aware mobile applications. Pervasive Computing, IEEE, 4(2):51–59, 2005.

S. Wasserman and K. Faust. Social network analysis: Methods and applications, volume 8. Cambridge university press, 1994.

ISTAG. Report on revising europe ict strategy. Technical report, European Commission, 2009.

T. Spiliotopoulos and I. Oakley. Applications of social network analysis for user modeling. Y. Shi, M. Larson, and A. Hanjalic. Towards understanding the challenges facing effective

trust-aware recommendation. Recommender Systems and the Social Web, page 40, 2010.

W. De Nooy. Social network analysis, graph theoretical approaches to. Encyclopedia ofComplexity and System Science. Springer-Verlag, Berlin/Heidelberg,(in print), 2009.

I. Cantador, A. Bellogn, and P. Castells. A multilayer ontology-based hybrid recommen-dation model. AI Communications, 21(2):203–210, 2008.

I. Torre. Adaptive systems in the era of the semantic and social web, a survey. User
Modeling and User-Adapted Interaction, 19(5):433–486, 2009.

Q. Jones and S. Rafaeli. User population and user contributions to virtual publics: a systems model. In Proceedings of the international ACM SIGGROUP conference on Sup- porting group work, pages 239–248. ACM, 1999.

J. Vassileva. Motivating participation in social computing applications: a user modeling perspective. User Modeling and User-Adapted Interaction, pages 1–25, 2012.

S. Rafaeli, D.R. Raban, and G. Ravid. Social and economic incentives in google answers. In ACM Workshop Sustaining Community: The role and design of incentive mechanisms in online systems, Sanibel Island, FL USA, 2005.

S. Munson, D. Lauterbach, M. Newman, and P. Resnick. Happier together: integrating a wellness application into a social network site. Persuasive Technology, pages 27–39, 2010.

E. Gaudioso, A. Soller, and J. Vassileva. Preface to the special issue on user modeling to support groups, communities and collaboration. User Modeling and User-Adapted Inter- action, 16(3):171–174, 2006.

M. Safar and K.A. Mahdi. Social Networking and Community Behavior Modeling: Quali- tative and Quantitative Measures. IGI Global (701 E. Chocolate Avenue, Hershey, Penn- sylvania, 17033, USA), 2012.

A. Soller. Adaptive support for distributed collaboration. The adaptive web, pages 573–595, 2007.

J. Vassileva and L. Sun. Using community visualization to stimulate participation in online communities. E-Service Journal, 6(1):3–39, 2007.

Jon Kleinberg. The convergence of social and technological networks. Commun. ACM, 51 (11):66–72, November 2008.

Benjamin Doerr, Mahmoud Fouz, and Tobias Friedrich. Why rumors spread so quickly in social networks. Commun. ACM, 55(6):70–75, June 2012.

K. Islam, Weiming Shen, and Xianbin Wang. Security and privacy considerations for wireless sensor networks in smart home environments. In Computer Supported Cooperative Work in Design (CSCWD), 2012 IEEE 16th International Conference on, pages 626 –633, may 2012.

M. Gruteser and D. Grunwald. Anonymous usage of location-based services through spa- cial and temporal cloaking. In Proc. of the International Conference on Mobile Systems, Applications, and Services (MobiSys), 2003.

Jing Deng, Richard Han, and Shivakant Mishra. Decorrelatingwireless sensor network traffic to inhibit traffic analysis attacks. Elsevier Pervasive and Mobile Computing Journal, Special Issue on Security in Wireless Mobile Computing Systems, 2:pp. 159–186, 2006.

F. Cena, N. Dokoohaki, and M. Matskin. Forging trust and privacy with user modeling frameworks: An ontological analysis. In SOTICS 2011, The First International Conference on Social Eco-Informatics, pages 43–48, 2011.

A.NarayananandV.Shmatikov.De-anonymizingsocialnetworks.InSecurityandPrivacy, 2009 30th IEEE Symposium on, pages 173–187. IEEE, 2009.

Jens Riegelsberger, M. Angela Sasse, and John D. McCarthy. The mechanics of trust: A framework for research and design. International Journal of Human-Computer Studies, 62 (3):381 – 422, 2005.

Donovan Artz and Yolanda Gil. A survey of trust in computer science and the semantic web. Web Semantics: Science, Services and Agents on the World Wide Web, 5(2):58 – 71, 2007.

Yongsheng Ding, Fengming Liu, and Bingyong Tang. Context-sensitive trust computing in distributed environments. Knowledge-Based Systems, 28(0):105 – 114, 2012.

Domenico Rosaci. Trust measures for competitive agents. Knowledge-Based Systems, 28 (0):38 – 46, 2012.

Jose M. Such, Agustin Espinosa, Ana Garcia-Fornes, and Vicent Botti. Partial identities as a foundation for trust and reputation. Engineering Applications of Artificial Intelligence, 24(7):1128 – 1136, 2011.

Adam Wierzbicki. The case for fairness of trust management. Electronic Notes in Theoret- ical Computer Science, 197(2):73 – 89, 2008. ¡ce:title¿Proceedings of the 3rd International Workshop on Security and Trust Management (STM 2007)¡/ce:title¿.

P. Victor, M. Cock, and C. Cornelis. Trust and recommendations. Recommender Systems Handbook, pages 645–675, 2011.

J.GolbeckandA.Mannes.Usingtrustandprovenanceforcontentfilteringonthesemantic web. In Proceedings of the Models of Trust for the Web Workshop, 2006.

T. Heath and E. Motta. Ease of interaction plus ease of integration: Combining web2. 0 and the semantic web in a reviewing site. Web Semantics: Science, Services and Agents on the World Wide Web, 6(1):76–83, 2008.

Isaac Agudo, Carmen Fernandez-Gago, and Javier Lopez. A scale based trust model for multi-context environments. Computers & Mathematics with Applications, 60(2):209 – 216, 2010.

Isaac Agudo, Carmen Fern ́andez-Gago, and Javier Lopez. An evolutionary trust and distrust model. Electronic Notes in Theoretical Computer Science, 244(0):3 – 12, 2009.

Ferdinando Colombo and Guido Merzoni. In praise of rigidity: The bright side of long-term contracts in repeated trust games. Journal of Economic Behavior & Organization, 59(3): 349 – 373, 2006.

Sheikh I. Ahamed, Munirul M. Haque, Md. Endadul Hoque, Farzana Rahman, and Niloth- pal Talukder. Design, analysis, and deployment of omnipresent formal trust model (ftm) with trust bootstrapping for pervasive environments. Journal of Systems and Software, 83 (2):253 – 270, 2010.

Churn-Jung Liau. Belief, information acquisition, and trust in multi-agent systems—a modal logic formulation. Artificial Intelligence, 149(1):31 – 60, 2003.

P.Venkat Rangan. An axiomatic theory of trust in secure communication protocols. Com- puters & Security, 11(2):163 – 172, 1992.

Vincenza Carchiolo, Alessandro Longheu, and Michele Malgeri. Reliable peers and useful resources: Searching for the best personalised learning path in a trust- and recommendation-aware environment. Information Sciences, 180(10):1893 – 1907, 2010.

Stefan Schmidt, Robert Steele, Tharam S. Dillon, and Elizabeth Chang. Fuzzy trust evaluation and credibility development in multi-agent systems. Applied Soft Computing, 7 (2):492 – 505, 2007.

Florian Skopik, Daniel Schall, and Schahram Dustdar. Modeling and mining of dynamic trust in complex service-oriented systems. Information Systems, 35(7):735 – 757, 2010.

Ayman Tajeddine, Ayman Kayssi, Ali Chehab, and Hassan Artail. Fuzzy reputation-based trust model. Applied Soft Computing, 11(1):345 – 355, 2011.

Zhi-Ping Fan, Wei-Lan Suo, Bo Feng, and Yang Liu. Trust estimation in a virtual team: A decision support method. Expert Systems with Applications, 38(8):10240 – 10251, 2011.

Yung-Ming Li and Chien-Pang Kao. Trepps: A trust-based recommender system for peer production services. Expert Systems with Applications, 36(2, Part 2):3263 – 3277, 2009.

Jungtae Mun, Moonsoo Shin, Kyunghuy Lee, and Mooyoung Jung. Manufacturing en- terprise collaboration based on a goal-oriented fuzzy trust evaluation model in a virtual enterprise. Computers & Industrial Engineering, 56(3):888 – 901, 2009.

Sudha Chinni, Johnson Thomas, Gheorghita Ghinea, and Zhengming Shen. Trust model for certificate revocation in ad hoc networks. Ad Hoc Networks, 6(3):441 – 457, 2008.

Mieso K. Denko, Tao Sun, and Isaac Woungang. Trust management in ubiquitous com- puting: A bayesian approach. Computer Communications, 34(3):398 – 406, 2011.

Mogens Nielsen, Karl Krukow, and Vladimiro Sassone. A bayesian model for event- based trust. Electronic Notes in Theoretical Computer Science, 172(0):499 – 521, 2007. ¡ce:title¿Computation, Meaning, and Logic: Articles dedicated to Gordon Plotkin¡/ce:title¿.

Y.C. Jiang, Z.Y. Xia, Y.P. Zhong, and S.Y. Zhang. Autonomous trust construction in multi-agent systems—a graph theory methodology. Advances in Engineering Software, 36 (2):59 – 66, 2005.

Andrew Koster, Marco Schorlemmer, and Jordi Sabater-Mir. Engineering trust alignment: Theory, method and experimentation. International Journal of Human-Computer Studies, 70(6):450 – 473, 2012.

Mark Hoogendoorn, S. Waqar Jaffry, and Jan Treur. Cognitive and neural modeling of dynamics of trust in competitive trustees. Cognitive Systems Research, 14(1):60 – 83, 2012.

Guoxing Zhan, Weisong Shi, and Julia Deng. Sensortrust: A resilient trust model for wireless sensing systems. Pervasive and Mobile Computing, 7(4):509 – 522, 2011.

Feng Zhang, Zhi-Ping Jia, Hui Xia, Xin Li, and H.-M. Sha Edwin. Node trust evaluation in mobile ad hoc networks based on multi-dimensional fuzzy and markov SCGM(1,1) model. Computer Communications, 35(5):589 – 596, 2012.

A. Boukerch, L. Xu, and K. EL-Khatib. Trust-based security for wireless ad hoc and sensor networks. Computer Communications, 30:2413 – 2427, 2007.

Liming Jiang, Jian Xu, Kun Zhang, and Hong Zhang. A new evidential trust model for open distributed systems. Expert Systems with Applications, 39(3):3772 – 3782, 2012.

Babak Khosravifar, Jamal Bentahar, Maziar Gomrokchi, and Rafiul Alam. Crm: An efficient trust and reputation model for agent computing. Knowledge-Based Systems, 30 (0):1 – 16, 2012.

Young Ae Kim and Hee Seok Song. Strategies for predicting local trust based on trust propagation in social networks. Knowledge-Based Systems, 24(8):1360 – 1371, 2011.

Basit Qureshi, Geyong Min, and Demetres Kouvatsos. A distributed reputation and trust management scheme for mobile peer-to-peer networks. Computer Communications, 35(5): 608 – 618, 2012.

Hamdi Yahyaoui. A trust-based game theoretical model for web services collaboration. Knowledge-Based Systems, 27(0):162 – 169, 2012.

Zhengqiang Liang and Weisong Shi. Analysis of ratings on trust inference in open envi- ronments. Performance Evaluation, 65(2):99 – 128, 2008.

Olufunmilola Onolaja, Rami Bahsoon, and Georgios Theodoropoulos. Agent-based trust management and prediction using d3-frt. Procedia Computer Science, 9(0):1119 – 1128, 2012. ¡ce:title¿Proceedings of the International Conference on Computational Science, ICCS 2012¡/ce:title¿.

Hongwei Lu and Bailing Liu. Dfans: A highly efficient strategy for automated trust nego- tiation. Computers & Security, 28(7):557 – 565, 2009.

Fabio Martinelli and Marinella Petrocchi. A uniform framework for security and trust modeling and analysis with crypto-ccs. Electronic Notes in Theoretical Computer Science, 186(0):85 – 99, 2007.

J. Todd McDonald and Alec Yasinsac. Application security models for mobile agent sys- tems. Electronic Notes in Theoretical Computer Science, 157(3):43 – 59, 2006.

Cai-Nicolas Ziegler and Jennifer Golbeck. Investigating interactions of trust and interest similarity. Decision Support Systems, 43(2):460 – 475, 2007.

Elizabeth Gray, Christian Jensen, Paul O’Connell, Stefan Weber, Jean-Marc Seigneur, and Yong Chen. Trust evolution policies for security in collaborative ad hoc applications. Electronic Notes in Theoretical Computer Science, 157(3):95 – 111, 2006.

Cynthia L. Corritore, Beverly Kracher, and Susan Wiedenbeck. On-line trust: concepts, evolving themes, a model. International Journal of Human-Computer Studies, 58(6):737 – 758, 2003.

Saeedeh Shekarpour and S.D. Katebi. Modeling and evaluation of trust with an extension in semantic web. Web Semantics: Science, Services and Agents on the World Wide Web, 8(1):26 – 36, 2010.

Nathan Griffiths. Enhancing peer-to-peer collaboration using trust. Expert Systems with Applications, 31(4):849 – 858, 2006.

Gee-Woo Bock, Jumin Lee, Huei-Huang Kuan, and Jong-Hyun Kim. The progression of online trust in the multi-channel retailer context and the role of product uncertainty. Decision Support Systems, 53(1):97 – 107, 2012.

Yolanda Gil and Donovan Artz. Towards content trust of web resources. Web Semantics: Science, Services and Agents on the World Wide Web, 5(4):227 – 239, 2007.

Morten Hertzum, Hans H.K Andersen, Verner Andersen, and Camilla B Hansen. Trust in information sources: seeking information from people, documents, and virtual agents. Interacting with Computers, 14(5):575 – 599, 2002.

Yung-Ming Li and Ching-Wen Chen. A synthetical approach for blog recommendation: Combining trust, social relation, and semantic analysis. Expert Systems with Applications, 36(3, Part 2):6536 – 6547, 2009.

Jordi Sabater-Mir and Mario Paolucci. On representation and aggregation of social evalua- tions in computational trust and reputation models. International Journal of Approximate Reasoning, 46(3):458 – 483, 2007.

Nele Verbiest, Chris Cornelis, Patricia Victor, and Enrique Herrera-Viedma. Trust and distrust aggregation enhanced with path length incorporation. Fuzzy Sets and Systems, 202(0):61 – 74, 2012. ¡ce:title¿Theme: Aggregation Functions¡/ce:title¿.

Patricia Victor, Chris Cornelis, Martine De Cock, and Paulo Pinheiro da Silva. Grad- ual trust and distrust in recommender systems. Fuzzy Sets and Systems, 160(10):1367 – 1382, 2009. ¡ce:title¿Special Issue: Fuzzy Sets in Interdisciplinary Perception and Intelli- gence¡/ce:title¿.

Anthony G. Bower, Steven Garber, and Joel C. Watson. Learning about a population of agents and the evolution of trust and cooperation. International Journal of Industrial Organization, 15(2):165 – 190, 1997.

Giangiacomo Bravo, Flaminio Squazzoni, and Riccardo Boero. Trust and partner selection in social networks: An experimentally grounded model. Social Networks, (0):–, 2012.

Florian Herold. Contractual incompleteness as a signal of trust. Games and Economic Behavior, 68(1):180 – 191, 2010.

Kiku Jones and Lori N.K. Leonard. Trust in consumer-to-consumer electronic commerce. Information & Management, 45(2):88 – 95, 2008.

Dan J. Kim, Yong I. Song, S.B. Braynov, and H.R. Rao. A multidimensional trust for- mation model in B-to-C e-commerce: a conceptual framework and content analyses of academia/practitioner perspectives. Decision Support Systems, 40(2):143 – 165, 2005.

Chun Zhang, Sridhar Viswanathan, and John W. Henke Jr. The boundary spanning ca- pabilities of purchasing agents in buyer–supplier trust development. Journal of Operations Management, 29(4):318 – 328, 2011.

Dan J. Kim, Donald L. Ferrin, and H. Raghav Rao. A trust-based consumer decision- making model in electronic commerce: The role of trust, perceived risk, and their an- tecedents. Decision Support Systems, 44(2):544 – 564, 2008.

Yoon Jeon Koh and S. Shyam Sundar. Effects of specialization in computers, web sites, and web agents on e-commerce trust. International Journal of Human-Computer Studies, 68(12):899 – 912, 2010.

Huei-Huang Kuan and Gee-Woo Bock. Trust transference in brick and click retailers: An investigation of the before-online-visit phase. Information & Management, 44(2):175 – 187, 2007.

Yao-Hua Tan and Walter Thoen. Formal aspects of a generic model of trust for electronic commerce. Decision Support Systems, 33(3):233 – 246, 2002.

Tiffany Y. Tang, Pinata Winoto, and Xiaolin Niu. I-trust: investigating trust between users and agents in a multi-agent portfolio management system. Electronic Commerce Research and Applications, 2(4):302 – 314, 2003.

Pearl Pu and Li Chen. Trust-inspiring explanation interfaces for recommender systems. Knowledge-Based Systems, 20(6):542 – 556, 2007.

Kim-Phuong L. Vu, Vanessa Chambers, Beth Creekmur, Dongbin Cho, and Robert W. Proctor. Influence of the privacy bird⃝R user agent on user trust of different web sites. Computers in Industry, 61(4):311 – 317, 2010.

Elizabeth Sillence, Pam Briggs, Peter Harris, and Lesley Fishwick. A framework for un- derstanding trust factors in web-based health advice. International Journal of Human- Computer Studies, 64(8):697 – 713, 2006.

Trust in health infomediaries. Decision Support Systems, 43(2):390 – 407, 2007. ¡ce:title¿Emerging Issues in Collaborative Commerce¡/ce:title¿.

Young Ae Kim and Rasik Phalak. A trust prediction framework in rating-based experience sharing social networks without a web of trust. Information Sciences, 191(0):128 – 145, 2012.

Ke Liu, Nael Abu-Ghazaleh, and Kyoung-Don Kang. Location verification and trust man- agement for resilient geographic routing. Journal of Parallel and Distributed Computing, 67(2):215 – 228, 2007.

Javier Lopez, Rodrigo Roman, Isaac Agudo, and Carmen Fernandez-Gago. Trust manage- ment systems for wireless sensor networks: Best practices. Computer Communications, 33 (9):1086 – 1093, 2010.

Asad Amir Pirzada, Amitava Datta, and Chris McDonald. Incorporating trust and repu- tation in the dsr protocol for dependable routing. Computer Communications, 29(15):2806 – 2821, 2006.

Hui Xia, Zhiping Jia, Xin Li, Lei Ju, and Edwin H.-M. Sha. Trust prediction and trust- based source routing in mobile ad hoc networks. Ad Hoc Networks, (0):–, 2012.

Alexandra Olteanu and Guillaume Pierre. Towards robust and scalable peer-to-peer social networks. In Proceedings of the Fifth Workshop on Social Network Systems, SNS ’12, pages 10:1–10:6, New York, NY, USA, 2012. ACM.

C. Kadushin. Understanding social networks: Theories, concepts, and findings. Oxford University Press, 2012.

Santo Fortunato. Community detection in graphs. Physics Reports, 486(3-5):75 – 174, 2010.

Bill Howard. Analyzing online social networks. Commun. ACM, 51(11):14–16, November 2008.

Bernard Chazelle. Natural algorithms and influence systems. Communications of the ACM, 55(12):101–110, 2012.

Gary Anthes. Html5 leads a web revolution. Commun. ACM, 55(7):16–17, July 2012.

A.M. Tring. Computing machinery and intelligence. Mind, 59:433–469, 1950. I. H. Witten and E. Frank. Data Mining: Practical Machine Learning Tools and Techniques.

Morgan Kaufmann, 2005. D. H. Ackley, G. E. Hinton, and T. J. Sejnowski. A learning algorithm for boltzmann

machines. Cognitive Science, 9:147–169, 1985. T.G. Dietterich. A Tutorial on Learning with Bayesian Networks. MIT Press, Cambridge,

MA, 1997. V. Vapnik. The Nature of Statistical Learning Theory. Springer, New York, 1995.

D. Haussler. Quantifying inductive bias: AI learning algorithms and Valiant’s learning framework. Artificial Intelligence, 36:177–221, 1988.

S. Roychowdhury and W. Pedrycz. Modeling temporal functions with granular regression and fuzzy rules. Fuzzy Sets and Systems, 126:377–387, 2002.

J.C. Bezdek. Pattern Recognition with Fuzzy Objective Function Algoritms. Plenum Press, New York, 1981.

B Apolloni, S. Bassis, D. Malchiodi, and W. Pedrycz. Interpolating support information granules. Neurocomputing, 71:2433–2445, 2008.

G.I. S ́ainz, R. Garc ́ıa, and M.J. Fuente. Fault fuzzy rule extraction from ac motors by neuro-fuzzy models. In Joan Cabestany, Alberto Prieto, and Francisco Sandoval, edi- tors, Computational Intelligence and Bioinspired Systems, volume 3512 of Lecture Notes in Computer Science, pages 1116–1123. Springer Berlin Heidelberg, 2005.

Rub ́en Garc ́ıa, Gregorio I. S ́ainz, and Jos ́e M. Ben ́ıtez. Frasel: A consensus of feature ranking methods for time series modelling. Soft Computing Journal, In press.

F. Barrientos and G. I. S ́ainz. Interpretable knowledge extraction from emergency call data based on fuzzy unsupervised decision tree. LNCS Knowledge-Based Systems Journal, 25:77–87, 2012.

Massoud Babaie-Zadeh and Christian Jutten. A general approach for mutual information minimization and its application to blind source separation. Signal Process., 85(5):975–995, 2005.

J. Karhunen, A. Hyvdirinen, R. Vigario, J. Hurri, and E. Oja. Applications of neural blind separation to signal and image processing. In Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP ’97) -Volume 1 - Volume 1, ICASSP ’97, pages 131–, Washington, DC, USA, 1997. IEEE Computer Society.

A. Hyv ̈arinen, J. Kahunen, and E. Oja. Independent Component Analysis. John Wi- ley&Sons, 2001.

David J. C. MacKay. Information Theory, Inference & Learning Algorithms. Cambridge University Press, New York, NY, USA, 2002.

Isabelle Guyon and Andr ́e Elisseeff. An introduction to variable and feature selection. J. Mach. Learn. Res., 3:1157–1182, 2003.

B. Apolloni, S. Bassis, and A. Brega. Feature selection via boolean independent component analysis. Information Science, 179(22):3815–3831, 2009.

S. Ozawa, S. Too, S. Abe, S. Pang, and N. Kasabov. Incremental learning of feature space and classifier for online face recognition. Neural Netw., page 575584, 2005.

S. Pang, S. Ozawa, and N. Kasabov. Incremental linear discriminant analysis for classifi- cation of data streams. IEEE Trans. SMC-B, 35(4):905914, 2005.

S. Bin, L. Yuan, and W. Xiaoyi. Research on data mining models for the internet of things. In IASP 10 - 2010 International Conference on Image Analysis and Signal Processing, pages 127–132, 2010.

J. MacQueen. Some methods for classification and analysis of multivariate observations. In Univ. of Calif. Press, editor, Proc. Fifth Berkeley Symp. on Math. Statist. and Prob., volume 1, pages 281–297, 1967.

Charles Elkan. Clustering with k-means: faster, smarter, cheaper,. In Workshop on Clus- tering High-Dimensional Data, SIAM International Conference on Data Mining, 2004. (keynote talk).

A. Banerjee, S. Merugu, I. Dhillon, and J. Ghosh. Clustering with bregman divergences. Journal of Machine Learning Research, 6:1705–1749, 2005.

J. C. Bezdek. Fuzzy Mathematics in Pattern Classification. PhD thesis, Cornell University, Ithaca, NY., 1973.

Bin Zhang, Meichun Hsu, and Umeshwar Dayal. K-harmonic means - a data clustering algorithm. Technical report, Hewlett-Packard Laboratories-124, 1999.

L. M. Sangalli, P. Secchi, S. Vantini, and V. Vitelli. k-mean alignment for curve clustering. Computational Statistics and Data Analysis, 54(5):1219–1233, 2010. Cited By (since 1996): 8.

N. K. Kasabov and Q. Song. Denfis: Dynamic evolving neural-fuzzy inference system and its application for time-series prediction. IEEE Transactions on Fuzzy Systems, 10(2): 144–154, 2002.

M. Futschik and N. Kasabov. Fuzzy clustering in gene expression data analysis. In DC IEEE Press, Washington, editor, Proceedings of the World Congress of Computational Intelligence WCCIO ̃2002, Hawaii, 2002.

S. Li, L. Xu, and X. Wang. Compressed sensing signal and data acquisition in wireless sensor networks and internet of things. Industrial Informatics, IEEE Transactions on, PP (99):1, 2012.

Ana I. GonzA ̃¡lez. Contributions to Unsupervised and Supervised Learning with Applica- tions in Digital Image Processing. PhD thesis, The University of the Basque Country, 2012.

K. Fukunaga. Statistical Pattern Recognition. Academic Press, 1990. T. Kohonen. Self Organization and Associative memory. Springer Verlag, 1989.

H.K. Kushner and D.S. Clark. Stochastic approximation for constrained and unconstrained systems. Springer Verlag, Berlin, 1978.

H. Ritter, T. Martinetz, and K. Schulten. Neural computation and self-organizing maps: an introduction. MA: Addison-Wesley, Reading, 1992.

J.T. Tou and R.C. Gonzalez. Pattern recognition principles. Addison-Wesley, Reading,, 1974.

S. Haykin. Neural Networks: A comprehensive foundation. IEEE press, New York: Macmil- lan Coll. Pub. Co, 1994.

J.A. Hertz, A.S. Krogh, and R.G. Palmer. Introduction to the theory of neural computation. Addison Wesley, 1991.

B. Kosko. Stochastic competitive learning. IEEE trans Neural Networks, 2:522–529, 1991. R.D. Duda and P.E. Hart. Pattern Classification and Scene Analysis. Wiley, 1973.

C.Malsburg.Selforganizationoforientationsensitivecellsinthestriatecortex.Kybernetic, 14:85–100, 1973.

S. Grossberg. Adaptive pattern classification and universal recording, i: Parallel develop- ment and coding of neural feature detectors. Biological Cybernetics, 23:121–134, 1976.

T. Kohonen. Clustering, taxonomy, and topological maps of patterns. In Proc. 6th Int. Conf. Pattern Recognition, pages 114–128, Munich, 1982.

B. Fritzke. Growing cell structures: a self-organizing network for unsupervised and super- vised learning. Neural Networks, 7:1441–1460, 1994.

E. Bodt, M. Verleysen, and M. Cottrell. Kohonen maps versus vector quan- tization for data analysis. In M. Verleysen, editor, Proc. ESANN’97, pages 211–218. dFacto press, Brussels, 1997.

S. Kaski. Data exploration using Self-Organizing Maps. PhD thesis, Helsinki University of Technology, Neural Networks Research Centre, Es- poo, Finland, 1997.

J. Si, S. Lin, and M.A. Vuong. Dynamic topology representing networks. Neural Networks, 13:617627, 2000.

D. Deng and N. Kasabov. Esom: An algorithm to evolve self-organizing maps from online data streams. In Proceedings of IJCNNO ̃2000, Como, Italy, volume 6, page 38, 2000.

J.C. Bezdek and N.R. Pal. Two soft relatives of learning vector quantization. Neural Networks, 8:729–743, 1995.

F.L. Chung and T.Lee. Fuzzy competitive learning. Neural Networks, 7(3):539–551, 1994. N.B. Karayiannis. A methodology for constructing fuzzy algorithms for learning vector

quantization. IEEE trans. Neural Networks, 8(3):505–518, 1997.

N.B. Karayiannis, J.C. Bezdek, N.R. Pal, R.J. Hathaway, and Pin-I Pai. Repairs to glvq: a new family of competitive learning schemes. Neural Networks, IEEE Transactions on, 7 (5):1062 –1071, sep 1996.

D.C. Park and I. Dagger. Gradient based fuzzy c-means (gbfcm) algorithm. In Proc ICCNN’94, volume 3, pages 1626–1631, 1994.

E.C.K. Tsao, J.C. Bezdek, and N.R. Pal. Fuzzy kohonen clustering networks. Pattern Recognition, 27(5):757–764, 1994.

E. Yair, K. Zeger, and A. Gersho. Competitive learning and soft competition for vector quantization. IEEE Trans. Sign. Proc., 40(2):294–308, 1992.

T. Martinetz, S. Berkovich, and K. Schulten. Neural-gas network for vector quantization and his application to time series prediction. IEEE trans. Neural Networks, 4(4):558 – 569, 1993.

C. Alippi and R. Cucchiara. Cluster partitioning in image analysis classification: a ge- netic algorithm approach. In Proc IEEE COMPEURO, Computer Systems and Software Engineering, pages 139–144, 1992.

P. Andrey and P. Tarroux. Unsupervised image segmentation using a distributed genetic algorithm. Pattern Recognition, 27(5):659–673, 1994.

G. P. Babu and N.M. Murty. Clustering with evolution strategies. Pattern Recognition, 27 (2):321–329, 1994.

J.C. Bezdek and R.J. Hathaway. Optimization of fuzzy clustering criteria using genetic algorithms. In Proc 1st IEEE Conf. Evol. Comp., pages 589–594, 1994.

J.C. Bezdek, S. Boggavaparu, L.O. Hall, and A. Bensaid. Genetic algorithm guided clus- tering. In Proc 1st IEEE Conf. Evol. Comp, pages 34–39. IEEE press, 1994.

J. N. Bhuyan, V.V. Raghavan, and V.K. Elayavalli. Genetic algorithm for clustering with an ordered representation. In Proc. 4th Int. Cong. Gen. Alg., pages 408–415, 1991.

K. Blekas and A. Stafylopatis. Real coded genetic optimization of fuzzy clustering. In Proc. EUFIT’96, pages 461–465, 1996.

B.P. Buckles, F.E. Petry, D. Prabhu, R. George, and R. Srikanth. Fuzzy clustering with genetic search. In Proc. 1st IEEE Conf. Evol. Comp., pages 46–50, 1994.

D. R. Jones and M.A. Beltrano. Clustering with genetic algorithms. Technical report, Operating Sciences Dept., General Motors Res. Lab., Warren, Mich., 1990.

F.Z. Ketaff and J.P. Asselin de Beauville. Genetic and fuzzy based clustering. In Proc. 5th Conf. Int. Fed. Class. Soc., pages 100–103, 1996.

C.B. Lucasius, A.D. Dane, and G. Kateman. On k-medoid clustering of large data sets with the aid of a genetic algorithm: background, feasibility and comparison. Analytica Chimica Acta, 282:647–669, 1993.

S. Luchian, H. Luchian, and M. Petriuc. Evolutionary automated classification. In Proc 1st IEEE Conf. Evol. Comp., pages 585–588, 1994.

I.R. Moraczewski, W. Borkowski, and A. Kierzek. Clustering geobotanical data with the use of a genetic algorithm. COENOSES, 10(1):17–28, 1995.

T. Back and H.P. Schwefel. An overview of evolution algorithms for parameter optimiza- tion. Evolutionary Computation, 1:1–24, 1993.

T. Back and H.P. Schwefel. Evolutionary computation: an overview. In IEEE ICEC’96, pages 20–29, 1996.

Z. Michalewicz. Evolutionary computation: practical issues. In IEEE ICEC’96, pages 30–39, 1996.

A. I. Gonz ́alez, M. Gran ̃a, F. Albizuri, A. D’Anjou, and F. J. Torrealdea. A near real-time evolution-based adaptation strategy for dynamic color quantization of image sequences. Information Sciences, 122:Elsevier, February 2000.

B. Choi and K. Bluff. Genetic optimisation of control parameters of neural networks. In DC IEEE Computer Society Press, Washington, editor, Proceedings of the International Conference on Artificial Neural Networks and Expert Systems (ANNES 1995), Dunedin, New Zealand, page 174177, 1995.

F.L.MinkuandT.B.Ludermir.Evolutionarystrategiesandgeneticalgorithmsfordynamic parameter optimisation of evolving fuzzy neural networks. In Proceedings of IEEE Congress on Evolutionary Computation, (CEC), Edinburgh, September, volume 3, page 19511958, 2005.

Hugo de Garis. Neurite networks: The genetic programming of cellular automata based neural nets which grow. In Proceedings of the International Joint Conference on Neural Networks, volume 3, pages 2921–2924, 1993.

T. Furuhashi, K. Nakaoka, and Y. Uchikawa. Efficient finding of fuzzy rules using a new approach to genetic based machine learning. In IEEE International Conference on Fuzzy Systems, volume 2, pages 715–722, 1995.

T. Furuhashi, K. Nakaoka, and Y. Uchikawa. A new approach to genetic based machine learning and an efficient finding of fuzzy rules. In Proceedings of the WWWO ̃94 Workshop, University of Nagoya, Japan,, page 114122, 1994.

M. Watts and N. Kasabov. Evolutionary computation for the optimisation of evolving connectionist systems. In DC IEEE Press, Washington, editor, Proceedings of WCCIO ̃2002 (World Congress of Computational Intelligence), Hawaii,, 2002.

J. Liu, W. Xu, and J. Sun. Quantum-behaved particle swarm optimization with mutation operator. In Seventeenth IEEE International Conference on Tools with Artificial Intelli- gence (ICTAIO ̃05), 2005.

G.K Venayagamoorthy and G. Singhal. Quantum-inspired evolutionary algorithms and binary particle swarm optimization for training mlp and srn neural networks. J. Theor. Comput. Nanosci., 2:561568, 2005.

A. P. Dempster, N. M. Laird, and D. B. Rubin. Maximum likelihood from incomplete data via the em algorithm. Journal of the Royal Statistical Society., 39:1–38, 1977.

Geoffrey McLachlan and Thriyambakam Krishn. The EM Algorithm and Extensions. John Wiley & Son, 1996.

Frank Rosenblatt. The perceptron –a perceiving and recognizing automaton. Technical Report 85-460-1, Cornell Aeronautical Laboratory., 1957.

S. I. Gallant. Perceptron-based learning algorithms. IEEE Transactions on Neural Net- works, 1(2):179–191, 1990.

Martin D. Buhmann. Radial Basis Functions: Theory and Implementations. Cambridge University, 2003.

E.H.L. Aarts and J.H.M. Korst. Simulated Annealing and Boltzmann Machines: a stochas- tic approach to combinatorial optimization and neural computing. John Wiley & Sons, 1989.

J.R. Quinlan. Induction of decision trees. Machine Learning, 1:81–106, 1986. J.R. Quinlan. C4.5: Programs for Machine Learning. Morgan Kaufmann, 1993.

L. Breiman, J. Friedman, R. Olshen, and C. Stone. Classification and Regression Trees. Wadsworth Int. Group, 1984.

C. Cortes and V.N. Vapnik. Support-vector networks. Machine Learning, 20, 1995. C.J.C. Burges. A tutorial on support vector machines for pattern recognition. Data Mining

and Knowledge Discovery, 2:1–47, 1998.

V. Blanz, B. Scholkopf, H. Bulthoff, C.Burges, V. Vapnik, and T. Vetter. Comparison of view-based object recognition algorithms using realistic 3d models. In C. von der Mals- burg, W. von Seelen, J.C. Vorbruggen, and B.Sendhoff, editors, Artificial Neural Networks ICANN’96. Lecture Notes in Computer Science, volume 1112, pages 251–256. Springer, 1996.

B. Scholkopf and A.J. Smola. Learning with Kernels. MIT Press, 2002. J. Pearl. Fusion, propagation, and structuring in belief networks. Artificial Intelligence,

29(3):241–288, 1986. M. Goldszmidt and J. Pearl. Qualitative probabilities for default reasoning, belief revision,

and causal modeling. Artificial Intelligence, 84(1-2):57–112, 1996. Judea Pearl and Stuart Russell. Handbook of Brain Theory and Neural Networks, chapter

Bayesian Networks, pages 157–160. MIT Press, 2003.

Judea Pearl. Causality: Models, Reasoning and Inference. 2nd ed. Cambridge University Press, 2009.

D. Koller and N. Friedman. Probabilistic Graphical Models Principles and Techniques. MIT Press, 2009.

S. Greenland, J. Pearl, and J. M. Robins. Causal diagrams for epidemiologic research. Epidemiology, 10(1):37–48, 1999.

D. Geiger and J. Pearl. Logical and algorithmic properties of independence and their application to bayesian networks. Annals of Mathematics and Artificial Intelligence, 2 (1-4):165–178, 1990.

S. E. Fienberg, A. M. Haviland, D. Heckerman, R. Shachter, J. B. Kadane, S. Moral, and J. Pearl. Statistics and causal inference: Discussion. Test, 12(2):319–345, 2003.

S. Andreassen, C. Riekehr, B. Kristensen, H. C. Schonheyder, and L. Leibovici. Using prob- abilistic and decision-theoretic methods in treatment and prognosis modeling. Artificial Intelligence in Medicine, 15(2):121–134, 1999.

N. Caticha and J. P. Neirotti. The evolution of learning systems: To bayes or not to be. In AIP Conference Proceedings, volume 872, pages 203–210, 2006.

J. Liu, K. . Chang, and J. Zhou. Learning bayesian networks with a hybrid convergent method. IEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Hu- mans, 29(5):436–449, 1999.

M. Kim and V. Pavlovic. Discriminative learning of mixture of bayesian network classifiers for sequence classification. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, volume 1, pages 268–275, 2006.

P.M. Djuric and Yunlong Wang. Distributed bayesian learning in multiagent systems: Im- proving our understanding of its capabilities and limitations. Signal Processing Magazine, IEEE, 29(2):65–76, march 2012.

Michael E. Tipping. Sparse bayesian learning and the relevance vector machine. Journal of Machine Learning Research, 1(3):211–244, 2001.

R.S. Sutton and A.G. Barto. Reinforcement learning: An introduction. Cambridge Univ Press, 1998.

Christopher Watkins and Peter Dayan. Technical note: Q-learning. In Machine Learning, volume 8, pages pp. 279–292, May 1992.

Liviu Panait and Sean Luke. Cooperative multi-agent learning: The state of the art. Autonomous Agents and Multi-Agent Systems, 11:387–434, 2005. 10.1007/s10458-005-2631- 2.

L. Busoniu, R. Babuska, and B. De Schutter. Comprehensive survey of multiagent re- inforcement learning. IEEE Transactions on Systems, Man, and Cybernetics. Part C: Applications and Reviews, 38(2):pp. 156–172, 2008.

D. Marquardt. An algorithm for least-squares estimation of nonlinear parameters. SIAM J. Appl. Math., 11:431–441, 1963.

G. A. Carpenter and S. Grossberg. Adaptive resonance theory. In M.A. ZArbib, editor, he Handbook of Brain Theory and Neural Networks, pages 87–90. MIT Press, Cambridge, MA, 2003.

B. Scholkopf, K. Tsuda, and J.P. Vert. Kernel Methods in Computational Biology. MIT Press, Cambridge, MA, 2004.

P. Bartlett and M.S. Rademacher. Svm complexities: risk bounds and structural results. Journal of Machine Learning Research, 3:463–482, 2002.

T.G. Dietterich. Ensemble methods in machine learning. In J. Kittler and F. Roli, edi- tors, Multiple Classifier Systems. First International Workshop, MCS 2000, Cagliari, Italy, volume 1857 of Lecture Notes in Computer Science, pages 1–15. Springer-Verlag, 2000.

Jordan. M.J. and R.A. Jacobs. Hierarchical mixtures of experts and the em algorithm. Neural Computation, 6(2):181–214, 1994.

L. Breiman. Bagging predictors. Machine Learning, 24(2):123–140, 1986.

Y. Freund and R. E. Schapire. A decision-theoretic generalization of on-line learning and application to boosting. In Proceedings of the 2nd European Conference on Computational Learning Theory, pages 92–99, Barcelona, 1995.

L. Kuncheva and C. Whitaker. Measures of diversity in classifier ensembles. Machine Learning, 51:181–207, 2003.

J. J. Garcia Adeva, U. Ulises Cervino, and R. Calvo. Accuracy and diversity in ensembles of text categorisers. Machine Learning, 8(16):1 – 12, 2005.

M. Gashler, C. Giraud-Carrier, and Martinez. Decision tree ensemble: Small heterogeneous is better than large homogeneous. In The Seventh International Conference on Machine Learning and Applications, pages 900–905, 2008.

K.Monteith,J.Carroll,K.Seppi,andT.Martinez.Bayesianmodelaveragingintobayesian model combination. In Proceedings of the International Joint Conference on Neural Net- works IJCNN’11, pages 2657–2663, 2011.

G. Towell, J. Shavlik, and M. Noordewier. Refinement of approximate domain theories by knowledge based neural networks. In Proceedings of the Eighth National Conference on Artificial Intelligence AAAIO ̃90, pages 861–866, 1990.

T. Yamakawa and S. Tomoda. A fuzzy neuron and its application to pattern recognition. In Proceedings of the Third IFSA Congress, pages 1–9, 1989.

B. Apolloni and I. Zoppis. Subymbolically managing pieces of symbolical functions for sorting. IEEE Trans on Neural Networks, 10(5):1099–1122, 1999.

B. Apolloni, A. Piccolboni, and E. Sozio. A hybrid symbolic subsymbolic controller for complex dynamical systems. Neurocomputing, 37:127–163, 2001.

band Lin, C.H and C.F. Hsu. Neural-network hybrid control for antilock braking systems. IEEE Transactions on Neural Networks, 14(2), 2003.

B. Apolloni, A. Esposito, D. Malchiodi, C. Orovas, G. Palmas, and J. G. Taylor. A hybrid symbolic subsymbolic controller for complex dynamical systems. IEEE Transactions on Neural Networks, 15(6):1333–1349, 2004.

R. Andrews and S. Geva. Rule extraction from local cluster neural nets. Neurocomputing, 1(20), 2002.

R. Sun and L. Bookman. Computational Architectures Integrating Neural and Symbolic Processes. Kluwer Academic Publishers, Needham, MA., 1994.

S. Wermter and R. Sun. Hybrid Neural Systems. Springer-Verlag, Heidelberg, 2000.

S. Wermter and R. Sun. Hybrid Neural Systems. Springer-Verlag, Heidelberg, 2000.

F. Baader, D. Calvanese, D. L. McGuinness, D. Nardi, and P. F. Patel-Schneider. The Description Logic Handbook. Theory, Implementation and Applications. Cambridge Uni- versity Press, UK, 2003.

A. Borgida and R. Brachman. Description Logic Handbook, chapter Conceptual Modeling with Description Logics, pages 349–372. 2003.

D. Calvanese, G. de Giacomo, D. Lembo, M. Lenzerini, and R. Rosati. Dl-lite: Tractable description logics for ontologies. In Proc. of the 20th Nat. Conf. on Artificial Intelligence (AAAI 2005), 2005.

D. Calvanese, G. de Giacomo, D. Lembo, M. Lenzerini, and R. Rosati. Data complexity of query answering in description logics. In Proc. of the 2005 Description Logics Workshop (DL’05), 2005.

D. Calvanese, G. de Giacomo, D. Lembo, M. Lenzerini, and R Rosati. Tractable reasoning an efficient query answering in description logics: The dl-lite family. Journal of Automated Reasoning, 39, 2007.

D. Calvanese, G. de Giacomo, D. Lembo, M. Lenzerini, A. Poggi, and R. Rosati. Linking data to ontologies: The description logic dl-lite. In Proc. of the 2nd Int. Workshop on OWL: (OWLED 2006), 2006.

H ́ector Perez-Urbina, Boris Motik, and I. Horrocks. Rewriting conjunctive queries over description logic knowledge bases. Semantics in Data and Knowledge Bases LNCS, 4925: 199–214, 2008.

H. Perez-Urbina, I. Horrocks, and B. Motik. Efficient query answering for owl 2. In LNCS, editor, Proc. of the 8th Int. Semantic Web Conference (ISWC 2009), volume 5823, pages 489–504, 2009.

H. Perez-Urbina, B. Motik, and I. Horrocks. Tractable query answering and rewriting under description logic constraints. Journal of Applied Logic, 2009.

Roger C. Schank and Robert P. Abelson. Scripts, plans, goals and understanding: An inquiry into human knowledge structures. Lawrence Erlbaum, Oxford, England, 1977.

A. Aamodt and E. Plaza. Case-based reasoning: Foundational issues, methodological variations, and system approaches. AI Communications, 7(i), 1994.

David B. Leake. Case-Based Reasoning: Experiences, Lessons and Future Directions. MIT Press, Cambridge, MA, USA, 1st edition, 1996.

R. C. Schank. Dynamic Memory. Cambridge Univ. Press, 1983. I. Watson. Applying case-based reasoning: techniques for enterprise systems. Morgan

Kaufmann Publishers Inc., San Francisco, CA, USA, 1998.

Lotfi A. Zadeh. Fuzzy sets. Information and control, 8(3):338–353, 1965.

T. Berners-Lee, J. Hendler, and O. Lassila. The semantic web. Scientific American, 2001.

F. Baader, D. McGuinness, D. Nardi, and P. Patel-Schneider. The Description Logic Handbook: Theory, implementation and applications. Cambridge University Press, 2002.

J. Alejandro, T. Belle, and J. Smith. Modal keywords, ontologies and reasoning for video understanding. In Proceedings of the International Conference on Image and Video Re- trieval, 2003.

A. B. Benitez, J. R. Smith, and S. Chang. Medianet: a multimedia information network for knowledge representation. In John R. Smith; Chinh Le; Sethuraman Panchanathan; C.-C. J. Kuo, editor, Proc. SPIE, Internet Multimedia Management Systems, volume 4210, pages 1–12, 2000.

D. McGuiness. The Description Logic Handbook: Theory, Implementation, and Applica- tions, chapter Configuration, pages 388–405. Cambridge University Press, 2003.

F. Baader, I. Horrocks, and U. Sattler. Description logics for the semantic web. KI, 16(4): 57–59, 2002.

I. Horrocks and U. Sattler. A description logic with transitive and inverse roles and role hierarchies. Journal of Logic and Computation, 9:385–410, 1999.

J.Z. Pan, G. Stoilos, G. Stamou, V. Tzouvaras, and I. Horrocks. f-swrl: A fuzzy extension of swrl. Journal of Data Semantics, 6:27–45, 2006.

P Hajek. Metamathematics of Fuzzy Logic. Kluwer, 1998. L. V. S. Lakshmanan and N. Shiri. A parametric approach to deductive databases with

uncertainty. IEEE Transactions on Knowledge and Data Engineering, 13(4):554–570, 2001. M. Kifer and A. Li. On the semantics of rule-based expert systems with uncertainty.

Lecture Notes in Computer Science, 326:102–117, 1988. M. Kifer and V.S. Subrahmanian. Theory of generalized annotated logic programming and

its applications. Journal of Logic Programming, 12(4):335–367, 1992. T.H. Cao. Annotated fuzzy logic programs. Fuzzy Sets and Systems, 113:277–298, 2000.

C. V. Damasio and L. M. Pereira. Monotonic and residuated logic programs. Lecture Notes in Computer Science, 2143:748–759, 2001.

J. Medina, M. Ojeda-Aciego, and P. Vojtas. Multi-adjoint logic programs with continuous semantics. Lecture Notes in Computer Science, 2173:351–364, 2001.

L.V.S. Lakshmanan and N. Shiri. Uncertain deductive databases: A hybrid approach. Information Systems, 22(8):483–508, 1997.

A. Chortaras, G.B. Stamou, and A. Stafylopatis. Definition and adaptation of weighted fuzzy logic programs. International Journal of Uncertainty, Fuzziness and Knowledge- Based Systems, 17(1):85–135, 2009.

Y. Loyer and U. Straccia. The well-founded semantics in normal logic programs with uncertainty. Lecture Notes in Computer Science, 2441:152–166, 2002.

Y. Loyer and U. Straccia. The approximate well-founded semantics for logic programs with uncertainty. Lecture Notes in Computer Science, 2747:541–550, 2003.

U. Straccia. Query answering in normal logic programs under uncertainty. Lecture Notes in Computer Science, 3571:687–700, 2005.

C.V. Damasio, J. Medina, and M. Ojeda-Aciego. Termination of logic programs with imperfect information: applications and query procedure. Journal of Applied Logic, 5(3): 435–458, 2007.

U. Straccia. A top-down query answering procedure for normal logic programs under the any-world assumption. Lecture Notes in Computer Science, 4724:115–127, 2007.

C.G. Looney. Fuzzy petri nets for rule-based decisionmaking. Systems, Man and Cyber- netics, IEEE Transactions on, 18(1):178–183, jan/feb 1988.

R. Zurawski and MengChu Zhou. Petri nets and industrial applications: A tutorial. In- dustrial Electronics, IEEE Transactions on, 41(6):567–583, dec 1994.

Woei-Tzy Jong, Yuh-Shin Shiau, Yih-Jen Horng, Hsin-Horng Chen, and Shyi-Ming Chen. Temporal knowledge representation and reasoning techniques using time petri nets. Sys- tems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on, 29(4):541–545, aug 1999.

Shyi-Ming Chen, Jyh sheng Ke, and Jin-Fu Chang. Knowledge representation using fuzzy petri nets. Knowledge and Data Engineering, IEEE Transactions on, 2(3):311–319, sep 1990.

XiaoOu Li, Wen Yu, and F. Lara-Rosano. Dynamic knowledge inference and learning under adaptive fuzzy petri net framework. Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on, 30(4):442–450, nov 2000.

W. Pedrycz and F. Gomide. A generalized fuzzy petri net model. Fuzzy Systems, IEEE Transactions on, 2(4):295–301, nov 1994.

Witold Pedrycz. Generalized fuzzy petri nets as pattern classifiers. Pattern Recognition Letters, 20(14):1489–1498, 1999.

M.M. Hanna, A. Buck, and R. Smith. Fuzzy petri nets with neural networks to model products quality from a cnc-milling machining centre. Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on, 26(5):638–645, sep 1996.

Han Seong Son and Poong Hyun Seong. A quality control method for nuclear instrumen- tation and control systems based on software safety prediction. Nuclear Science, IEEE Transactions on, 47(2):408–421, apr 2000.

Fei-Yue Wang. Agent-based control for fuzzy behavior programming in robotic excavation. Fuzzy Systems, IEEE Transactions on, 12(4):540–548, aug. 2004.

G.G. Rigatos. Fuzzy stochastic automata for intelligent vehicle control. Industrial Elec- tronics, IEEE Transactions on, 50(1):76–79, feb 2003.

Rong-JongWaiandChia-MingLiu.Designofdynamicpetrirecurrentfuzzyneuralnetwork and its application to path-tracking control of nonholonomic mobile robot. Industrial Electronics, IEEE Transactions on, 56(7):2667–2683, july 2009.

Tzu-Chiang Chiang, Cheng-Feng Tai, and Ting-Wei Hou. A knowledge-based inference multicast protocol using adaptive fuzzy petri nets. Expert Systems with Applications, 36 (4):8115–8123, 2009.

Dayal Ramakrushna Parhi and Jagadish Chandra Mohanta. Navigational control of several mobile robotic agents using petri-potential-fuzzy hybrid controller. Applied Soft Comput- ing, 11(4):3546–3557, 2011.

L.Zouaghi,A.Alexopoulos,A.Wagner,andE.Badreddin.Mission-basedonlinegeneration of probabilistic monitoring models for mobile robot navigation using petri nets. Robotics and Autonomous Systems, (0), 2012.

Rong-Jong Wai and Chia-Chin Chu. Robust petri fuzzy-neural-network control for linear induction motor drive. Industrial Electronics, IEEE Transactions on, 54(1):177–189, feb. 2007.

Rong-Jong Wai and Chia-Chin Chu. Motion control of linear induction motor via petri fuzzy neural network. Industrial Electronics, IEEE Transactions on, 54(1):281–295, feb. 2007.

Alexander Fay. A fuzzy knowledge-based system for railway traffic control. Engineering Applications of Artificial Intelligence, 13(6):719–729, 2000.

Yung-Hsiang Cheng and Li-An Yang. A fuzzy petri nets approach for railway traffic control in case of abnormality: Evidence from taiwan railway system. Expert Systems with Applications, 36(4):8040–8048, 2009.

R. Tang, G.K.H. Pang, and S.S. Woo. A continuous fuzzy petri net tool for intelligent process monitoring and control. Control Systems Technology, IEEE Transactions on, 3(3): 318–329, sep 1995.

Ying Tang, MengChu Zhou, and Meimei Gao. Fuzzy-petri-net-based disassembly planning considering human factors. Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on, 36(4):718–726, july 2006.

D. Ben-Arieh, Rajeev Ranjan Kumar, and M.K. Tiwari. Analysis of assembly operations difficulty using enhanced expert high-level colored fuzzy petri net model. Robotics and Computer-Integrated Manufacturing, 20(5):385–403, 2004.

Xiuli Meng. Modeling of reconfigurable manufacturing systems based on colored timed object-oriented petri nets. Journal of Manufacturing Systems, 29:81–90, 2010.

FatihTaysazandCengizKahraman.Modelingaflexiblemanufacturingcellusingstochastic petri nets with fuzzy parameters. Expert Systems with Applications, 37(5):3910–3920, 2010.

Feng Zhou, R.J. Jiao, Qianli Xu, and K. Takahashi. User experience modeling and simula- tion for product ecosystem design based on fuzzy reasoning petri nets. Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on, 42(1):201–212, jan. 2012.

A. Pantelopoulos and N.G. Bourbakis. Prognosis - a wearable health-monitoring system for people at risk: Methodology and modeling. Information Technology in Biomedicine, IEEE Transactions on, 14(3):613–621, may 2010.

Yi-ChunChangandChih-PingChu.Applyinglearningbehavioralpetrinetstotheanalysis of learning behavior in web-based learning environments. Information Sciences, 180(6): 995–1009, 2010.

Yi-Chun Chang, Ying-Chia Huang, and Chih-Ping Chu. B2 model: A browsing behavior model based on high-level petri nets to generate behavioral patterns for e-learning. Expert Systems with Applications, 36(10):12423–12440, 2009.

Victor R.L. Shen, Cheng-Ying Yang, Yu-Ying Wang, and Yu-Hsiang Lin. Application of high-level fuzzy petri nets to educational grading system. Expert Systems with Applications, 39(17):12935–12946, 2012.

J. Lee, K.F.R. Liu, and Weiling Chiang. A fuzzy petri net-based expert system and its application to damage assessment of bridges. Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on, 29(3):350–370, jun 1999.

Jing Sun, Shi-Yin Qin, and Yong-Hua Song. Fault diagnosis of electric power systems based on fuzzy petri nets. Power Systems, IEEE Transactions on, 19(4):2053–2059, nov. 2004.

Xu Luo and M. Kezunovic. Implementing fuzzy reasoning petri-nets for fault section estimation. Power Delivery, IEEE Transactions on, 23(2):676–685, april 2008.

Dong-Her Shih, Hsiu-Sen Chiang, Binshan Lin, and Shih-Bin Lin. An embedded mobile ecg reasoning system for elderly patients. Information Technology in Biomedicine, IEEE Transactions on, 14(3):854–865, may 2010.

Metin M. Ozbek and George F. Pinder. A fuzzy-petri net formalization of expert informa- tion for groundwater risk management. In William G. Gray S. Majid Hassanizadeh, Ruud J. Schotting and George F. Pinder, editors, Computational Methods in Water Resources Proceedings of the XIVth International Conference on Computational Methods in Water Resources (CMWR XIV), volume 47 of Developments in Water Science, pages 779–786. Elsevier, 2002.

Yong Ge, Xitao Xing, and Qiuming Cheng. Simulation and analysis of infrastructure interdependencies using a petri net simulator in a geographical information system. Inter- national Journal of Applied Earth Observation and Geoinformation, 12(6):419–430, 2010.

Meimei Gao, MengChu Zhou, Xiaoguang Huang, and Zhiming Wu. Fuzzy reasoning petri nets. Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on, 33(3):314–324, may 2003.

V.R.L. Shen. Knowledge representation using high-level fuzzy petri nets. Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on, 36(6):1220–1227, nov. 2006.

X. Li and F. Lara-Rosano. Adaptive fuzzy petri nets for dynamic knowledge representation and inference. Expert Systems with Applications, 19(3):235–241, 2000.

Huaiqing Wang, Changjun Jiang, and Shaoyi Liao. Concurrent reasoning of fuzzy logical petri nets based on multi-task schedule. Fuzzy Systems, IEEE Transactions on, 9(3): 444–449, jun 2001.

D.S. Yeung, Xi-Zhao Wang, and E.C.C. Tsang. Handling interaction in fuzzy production rule reasoning. Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on, 34(5):1979–1987, oct. 2004.

Amit Konar, Uday K. Chakraborty, and Paul P. Wang. Supervised learning on a fuzzy petri net. Information Sciences, 172:397–416, 2005.

Amit Konar and Uday K. Chakraborty. Reasoning and unsupervised learning in a fuzzy cognitive map. Information Sciences, 170:419–441, 2005.

V.R.L. Shen. Reinforcement learning for high-level fuzzy petri nets. Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on, 33(2):351–362, apr 2003.

M Weiss. Leveraging smart meter data to recognize home appliances. Pervasive Comput- ing and Communications (PerCom), 2012 IEEE International Conference, pages 190–197, 2012.

Gyung-Leen Park Junghoon Lee, Young-cheol Kim. An analysis of smart meter readings using artificial neural networks. Convergence and Hybrid Information Technology. Com- puter Science, 7425:182–188, 2012.

SebastianGottwalta,WolfgangKetterb,CarstenBlockc,JohnCollinsd,andChristofWein- hardtc. Demand side manegement - a simulation of household behavior under variable prices. Energy policy, 39:8163–8174, 2011.

Lucia Terrenghi. Computing technologies in the kitchen: The living cookbook as a design mindful cooking experiences. Material Culture Review, 70, 2009.

Thomson Reuters. Web of knowledge., .


Google. Google scholar.

Lucia Terrenghi, Otmar Hilliges, and Andreas Butz. Kitchen stories: sharing recipes with the living cookbook. Personal and Ubiquitous Computing, 11:409–414, 2007.

PANASONIC. Panasonic expands smart home appliance line, adds android smart app, cloud services.

Dario Bonino and Fulvio Corno. Dogont - ontology modeling for intelligent domotic envi- ronments. Computer Science, 5318:790–803, 2008.

Bruno Apolloni, Witold Pedrycz, Simone Bassis, and Dario Malchiodi. The Puzzle of Granular Computing. Studies in Computational Intelligence, Vol. 138. Springer, 2008.

European Commission.

ThomsonReuters.Webofscience.− z/webofscience/,

Thomson Reuters. Web of knowledge.,

IEEE Institute of Electrical and Electronics Engineers.

Google. Google scholar.

Z-wave Alliance. (2012). Tratto da Z-wave:

ZigBee Alliance. (2012). Tratto da ZigBee:

Zhdanova, A. V. (2008). Community driven ontologies in social networking portals. Web Intelligence and Agent Systems , 6 (1), 93-121.

WASP. (2010). Wasp Project. Tratto da

WirelessHART. (2010). Tratto da WirelessHART:

Xiaochen, L., Mao, W., Zeng, D., & Wange, F. (2008). Agent-Based Social Simulation and Modeling in Social Computing. Intelligence and Security Informatics, 5075/2008, p. 401-412.

Vermesan, O., & al., a. (2011). IoT Cluster Strategic agenda. Tratto da Intenet of Things Research:

Vigna, L. B. (2011). Four Degrees of Separation. CoRR , abs/1111.4570.

Villaverde, I., Echegoyen, Z., Moreno, R., & Graña, M. (2010). Experiments on Robotic Multiagents systems for Hose Deployment and Transportation. PAAMS, (p. 573-580).

Acampora, G., & Loia, V. (2005). Fuzzy control interoperability and scalability for adaptive domotic framework. IEEE Transactions on Idustrial Iformatics , 1 (2), 97-111.

Aiello, M., & Dustdar, S. (2008). Are our homes ready for services? A domotic infrastructure based on the web-service stack. Pervasive mobile computing , 4 (4), 506-525.

ALLOW. (2007). Tratto da Allow Project:

Anderson, W. T. (2003). Augmentation, symbiosis, transcendence: technology and the future(s) of human identity. Futures , 35 (5), 535-546.

Apolloni, B., Bassis, S. G., & Rossi, G. (2009). Collaboration at the Basis of Sharing Focused Information: The Opportunistic Networks. Computational Intelligence: Collaboration, Fusion and Emergence (p. 201-524). Springer.

Apolloni, B., Bassis, S., & Zippo, A. (2009). Processing of Information Microgranules within an Individual's Society. Human-Centric Information Processing Through Granular Modelling , 182, 233-264.

Apolloni, B., Bassis, S., Galliani, G. L., & Valerio, L. (2010). Wireless Domotic: An Enabling Platform for Granular Intelligence. 5th International Conference on Future Information Technology (FutureTech), (p. 1-6). IEEE.

Apolloni, B., Bassis, S., Malchiodi, D., & W., P. (2008). The puzzle of granular computing. Springer-Verlag.

Asterics. (2010). Tratto da Asterics:

Aristotele. (2010). Tratto da Aristotele:

Butler. (2011). Tratto da Butler Smartlife:

Backstrom, L., Boldi, P., Rosa, M., Ugander, J., & Vigna, S. (2011). Four Degrees of Separation. CoRR , abs/1111.4570.

Bishop, C. (2006). Pattern Recognition and Machine Learning. New York, Berlin: Springer.

CUBIQ. (2010). Tratto da CUBIQ:

CASAGRAS. (2008). Tratto da CORDIS:

Cartif. (2012). Tratto da cartif:

COMANCHE. (2006). Tratto da COMANCHE:

Cordis. (2008). Tratto da Cordis:

CordisWire. (2008). CordiWire. Tratto da

CSIL Company. (2010). Profiles of 50 major appliance manifacturers worldwide. CSIL.

Crew. (2010). Tratto da Crew:

Echelon Corporation. (2012). LonWorks Platform for Control Energy. Tratto da

edutain@grid. (2006). Tratto da edutain@grid

EFAA. (2012). Tratto da EFAA:

Eisenhauer, M., and Rosengren, P., & Antolin, P. (2009). A Development Platform for Integrating Wireless Devices and Sensors into Ambient Intelligence Systems. 6th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks Workshops. IEEE.

EIT. (2011). Smart Spaces. Tratto da EIT ICT Labs:

Encyclopedia of business. (2012). SIC5722 Household Appliance stores. Tratto da Encyclopedia of business:

e-Sense. (2007). Tratto da e-Sense:

E-Stars. (2008). Tratto da E-Stars:

Ducatel, K., Bofdanowicz, M., Scapolo, F., Leijten, J., & Burgelman, J.-C. (2010). Scenarios forn Ambient Intelligence. Tratto da Cordis:

Duffy, B. R. (2003). Anthropomorphism and the social robot. (190, A cura di) Robotics and Autonomous Systems , 42 (3-4), 177-.

DynamicRideShareing. (2012). Inhibitors. Tratto da

Dehems. (2008). Tratto da Dehems:

Future Internet X-ETP, G. (2010, January). Future Internet Strategic Research Agenda.

Fernández-Gauna, B., López-Guede, J. M., & Graña, M. (2011). Towards concurrent Q-Learning on linked multicomponent robotic systems. HAIS, (p. 463-470).

Guide . (2010). Tratto da Guide:

Gotta, M. (2011). Cisco Collaboration. Tratto da Cisco:

IBM. (2000). Web Service Architechture Overview. Tratto da IBM:

IERC. (2009). IERC. Tratto da IERC:

IERC. (2011). Pan European Research and Innovation Vision . Tratto il giorno 2011 da European Research Cluster on the Internet of Things:

IERC-b. (2010). Tratto da IERC:

IFR Statistical Department. (2010). Tratto da IFR Statistical Department:

IFR Statistical Department. (2011). Tratto da IFR Statistical Department:

IFTT. (2012). Tratto da IFTT:

interactivex. (2010). Tratto da interactivex:

IoT-A. (2011). Tratto da Internet of Things-Architectures:

IoT-A SOTA. (2011). Documents. Tratto da Internet of Things Architecture:

IoT-I. (2011). Public Deliverables. Tratto da Internet of things Initiative:

ISTAG. (2009). Tratto da

ISTAG. (2007). ISTAG. Tratto da ISTAG:

ISTAG. (2011). Istag Reports. Tratto da ICT Research in FP7:

HYDRA Project. (2010). Hydra Project. Tratto da

Hansmass, U. (2003). Pervasive Computing: The Mobile World. Springer.

Hendler, J., & Tim, B.-L. (2010). From Semantic Web to social machines: A research challenge for AI on the World Wide Web. Artificial Intelligence , 174 (2), 156-161.

Honda. (2011). Asimo. Tratto da Honda:

Horizon Excellent Science 2020. (2012). Excellent Science. Tratto da Horizon 2020:

Jackson, P. (1986). Introduction to Expert Systems. Addison-Wesley.

Johnson, S. (2002). Emergence: the connected lives of ants, brains, cities and software. Scribner.

Kyffin, S. (2010). Lessons Learned. Tratto da i3originals:

Kaliszewski, I. (2006). Soft Computing for Complex Multiple Criteria Decision. In International Series in Operations Research and Management (Vol. 85). Springer.

Konnex Association. (2012). Tratto da Konnex:

Liu, M., Corno, F., Bonino, D., & Castellina, E. (2009). An ontology-based context management and reasoning on the DOG gateway. IEEE Iternational Conference on Computational Intelligence and Software Engineering. IEEE.

López, T. S., Ranasinghe, D. C., Patkai, B., & McFarlane, D. (2009). Taxonomy, technology and applications of smart objects. Information Systems Frontiers , 1-20.

Nold, C., & Van Kranenburg, R. (2011). The internet of people for a possible word (Vol. Situated technologies panphlet 8). The architectural leage of New York.

MyHome Biticino. (2012). Tratto da MyHome:

Mamdami, E. H. (1977). Application of fuzzy logic to approximate reasoning using linguistic synthesis. IEEE Transactions on Computers , 26 (12), 1182-1191.

MIUR PONREC. (2012). Smartcities. Tratto da PONREC:

Miori, V., Russo, D., & Aliberti, M. (2010). Domotic Technologies incompatibility becomes user transparent. Communication of ACM , 53 (1), 153-157.

MIT Media Laboratory . (1996). Smart Spaces. Tratto da Smart Spaces:

MIT. (1996). Smart Spaces. Tratto da Smart Spaces:

OpenLab. (2011). Tratto da OpenLab:

ORBIS Company. (2012). Tratto da Orbis:

Oresteia Project. (2001). Tratto da Oresteia Project:

PASCAL 2 . (2010). Tratto da PASCAL 2:

PECES. (2007). Tratto da PECES :

PHYSTA Project. (1998). Tratto da PHYSTA:

Pobicos Project. (2011). Pobicos Project. Tratto da

SunSPOT. (2010). Tratto da SunSPOT:

Sutton, & Barto. (1998). Reinforcement Learning: An Introduction. MIT Press.

SANSEI. (2088). Tratto da Sensei Project:

Schuler, D. (1994). Social Computing. Communication of ACM , 37 (1), 28-29.

Sgroi, M., Wolisz, A., Sangiovanni-Vincetelli, A., & Rabaey, J. M. (2005). A Service-Based Universal Application Interface for Ad-hoc Wireless. In W. Weber, J. Rabaey, & E. H. Aarts, Ambient Intelligence (p. 149-156). Springer.

SmartProducts. (2009). Tratto da SmartProducts:

SmartSantander. (2010). Tratto da SmartSantander:

SOMACCA. (2009). Tratto da SOMACCA:

REWIRE Project. (2011). Tratto da REWIRE:

Reynolds, N. C. (1929). Easier Housework by better equipment. Madison: Country Life, Ltd.

REFLECT. (2008). REFLECT : Responsive flexible collaborating ambient. Tratto da ICT Research in FP7:

Riva, G., Loreti, P., Lunghi, M., Vatalaro, F., & Davide, F. (2003). Presence 2010: the Emergence of Ambient Intelligence. In G. Riva, F. Davide, & W. A. IJsselsteijn, Being there : concepts, effects and measurements of user presence in synthetic environments. IOS Press.