Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 30184
Behavioral Analysis of Team Members in Virtual Organization based on Trust Dimension and Learning

Authors: Indiramma M., K. R. Anandakumar

Abstract:

Trust management and Reputation models are becoming integral part of Internet based applications such as CSCW, E-commerce and Grid Computing. Also the trust dimension is a significant social structure and key to social relations within a collaborative community. Collaborative Decision Making (CDM) is a difficult task in the context of distributed environment (information across different geographical locations) and multidisciplinary decisions are involved such as Virtual Organization (VO). To aid team decision making in VO, Decision Support System and social network analysis approaches are integrated. In such situations social learning helps an organization in terms of relationship, team formation, partner selection etc. In this paper we focus on trust learning. Trust learning is an important activity in terms of information exchange, negotiation, collaboration and trust assessment for cooperation among virtual team members. In this paper we have proposed a reinforcement learning which enhances the trust decision making capability of interacting agents during collaboration in problem solving activity. Trust computational model with learning that we present is adapted for best alternate selection of new project in the organization. We verify our model in a multi-agent simulation where the agents in the community learn to identify trustworthy members, inconsistent behavior and conflicting behavior of agents.

Keywords: Collaborative Decision making, Trust, Multi Agent System (MAS), Bayesian Network, Reinforcement Learning.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1057505

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1510

References:


[1] Indiramma M, K R Anandakumar "TCM:A trust computational model forCollaborative decision making in MultiAgent systems", IJCSNS, Vol 8, No.11,November 2008.
[2] Indiramma M, K R Anandakumar "Collaborative decision making framework for distributed systems", IEEE conference ICCCE08, May 2008, Malaysia
[3] Indiramma M, K R Anandakumar "Collaborative decision making for Multiagent systems for GiS application", ICAIA08, March, HongKong.
[4] Indiramma M, K R Anandakumar "Trust based decision making for Multiagent systems for GiS application", IEEE International conference RAST07, Alwar, India, December 2007.
[5] Antonio Carlos et al, "Adapting decision making synchronous/asynchronous environment to a distributed hypermedia concurrent Engineering system", proceedings of IEEE International conference on system sciences ,1997
[6] Elliis C A, Gibbs S J, rein G L "Groupware: some issues and experiences." Communications of the ACM,34(1):38-58, 1991
[7] M Bohance, 2007,DEXL A program for MADM
[8] K W Hipel et al., " Multiple participant multicriteria decision making" IEEE transactions on system, man,and cybernetics, vol 23, No 4, August 1993
[9] M.P.A. Davis, " A multicriteria decision model application for managing group decisions", Journal of operation Research Society, 45,1994
[10] Shi, J., Bochmann, G. and Adams, C.: A Trust Model with Statistical Foundation, Workshop on Formal Aspects in Security and Trust (FAST '04), Toulouse, France, Kluwer Academic Press, August 26-27, 2004 .
[11] McKnight, D. H. and Chervany, N. L.: The Meanings of Trust. Technical Report 94-04, Carlson School of Management, University of Minnesota, 1996.
[12] Golbeck, J., Parsia, B. and Hendler, J.: Trust networks on the semantic web. In Proceedings of Cooperative Intelligent Agents 2003, Helsinki, Finland, August (2003).
[13] A Abdul Rehaman and S Hailes Using Recommendations for managing Trust in distributed systems, In Proceedings of IEEE malaysia ICC,Kaulalampur, November 1997
[14] Wooldridge. M., and Jennings, N. 1995. Intelligent Agents: Theory and pacticeKnowledge Engineering Review 10(2): 115-152.
[15] Multiagent Systems, edited by Gerhard Weiss, MIT Press, 1999.
[16] L M Camainha-Matos et al "E-business and virtual enterprise: managing business to business cooperation"Norwell, MA kulwer,2000.
[17] Steve Jones, Steve Marsh "Human computer interaction-trust in CSCW",1999.
[18] R Riegelsberger et al "the researchers dilemma: evaluating trust in computer mediated communication", IJof Human comuter studies,58,2003.
[19] Martin Rehak et al "Fuzzy number approach to trust in coalition environment", AAMAS05, Netherlands.
[20] M K Ahuja and K M Carley," Network Stucture in Virtual Organization",JCM3 ($), June 1998.
[21] Ana Madureira et.al," Cooperation mechanism for team-work based MAS in dynamic scheduling through meta heuristics" IEEE international symposium on Assembly and Manufacturing,USA, 2007
[22] Achim Rettinger et.al, " learning initial trust Among interacting agents", AI/ cognition group report, Germany, 2007
[23] Leonid Sheremetov et. al "Collective intelligence as a framework for supply chain management",Second IEEE international conference on Intelligent Systems", June 2004
[24] Nada Lavarac et al."Trust modeling for networked organizations using reputation and collborattion estimates" IEEE transactions on system, man,and cybernetics, vol 37, No 3, May 2007
[25] V Buskens. The social structure of Trust, Social networks,20, 1998
[26] Efficient Multi-Agent Reinforcement Learning through Automated Supervision (Short Paper), Chongjie Zhang, Sherief Abdallah, Victor Lesser, Proc. of 7th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS 2008),
[27] Olivier "Incremental reinforcement learning for designing MAS", ACM, AGENTS 01 May-June 2001.
[28] M. Lauer and M. Riedmiller, "An algorithm for distributed reinforcement learning in cooperative multi-agent systems," in Proc. 17thICML. Morgan Kaufmann, San Francisco, CA, 2000, pp. 535-542.
[29] C. Watkins and P. Dayan, "Technical note: Q-learning," Machine Learning, vol. 8, pp. 279-292, 1992. om the biography.