The advantages of designing adaptive business agents using reputation modeling compared to the approach of recursive modeling

Computational Intelligence

Volumn 20, Issue 4, 2004, Pages 532-547

  Tran, Thomas ^a   Cohen, Robin ^a  

^a UNIVERSITY OF WATERLOO   (Canada)

Author keywords

Adaptive business agents; Electronic commerce; Multi agent systems; Reinforcement learning; Reputation modeling; Trust of business agents

Indexed keywords

ALGORITHMS; DECISION MAKING; ELECTRONIC COMMERCE; LEARNING SYSTEMS; MATHEMATICAL MODELS; MULTI AGENT SYSTEMS;

ADAPTIVE BUSINESS AGENTS; REINFORCEMENT LEARNING; REPUTATION MODELING; TRUST OF BUSINESS AGENTS;

ADAPTIVE SYSTEMS;

EID: 8344244434     PISSN: 08247935     EISSN: None     Source Type: Journal    
DOI: 10.1111/j.0824-7935.2004.00252.x     Document Type: Article

References (12)

1. DAVIS, R., and R. G. SMITH. 1983. Negotiation as a metaphor for distributed problem solving. Artificial Intelligence, 20(1):63-109.
2. LITTMAN, M. L. 1994. Markov games as framework for multi-agent reinforcement learning. In Proceedings of the Eleventh International Conference on Machine Learning, pp. 157-163.
3. ONO, N., and K. FUKUMOTO. 1996. Multi-agent reinforcement learning: A modular approach. In Proceedings of the Second International Conference on Multi-Agent Systems, pp. 252-258.
4. SABATER, J., and C. SIERRA. 2001. REGRET: A reputation model for gregarious societies. In Papers from the Fifth International Conference on Autonomous Agents Workshop on Deception, Fraud and Trust in Agent Societies, pp. 61-69.
5. SANDHOLM, T. W., and R. H. CRITES. 1995. Multi-agent reinforcement in the iterated Prisoner's dilemma. Biosystems, 37:147-166.
6. SEN, S., M. SEKARAN, and J. HALE. 1994. Learning to coordinate without Sharing Information. In Proceedings of the Twelfth National Conference on Artificial Intelligence, pp. 426-431.
7. SMITH, R. G. 1980. The contract net protocol: High level communication and control in a distributed problem solver. IEEE Transactions on Computers, C-29(12):1104-1113.
8. TRAN, T. 2003. Reputation-Oriented Reinforcement Learning Strategies for Economically-Motivated Agents in Electronic Market Environments. Ph.D. Thesis, School of Computer Science, University of Waterloo.
9. TRAN, T. T., and R. COHEN. 2002. A reputation-oriented reinforcement learning strategy for agents in electronic marketplaces. Computational Intelligence (CI) Journal Special Issue on Agent Technology for Electronic Commerce, 18(4):550-565.
10. VIDAL, J. M. 1998. Computational Agents That Learn About Agents: Algorithms for Their Design and A Predictive Theory of Their Behavior. Ph.D. Thesis, Department of Computer Science & Engineering, University of Michigan.
11. VIDAL, J. M., and E. H. DURFEE. 1996. The impact of nested agent models in an information economy. In Proceedings of the Second International Conference on Multi-Agent Systems, pp. 377-384.
12. YU, B., and M. P. SINGH. 2000. A social mechanism of reputation management in electronic communities. In Cooperative Information Agents IV; Lecture Notes in Artificial Intelligence, Vol. 1860. Edited by M. Klusch and L. Kerschberg. Springer-Verlag, Berlin, pp. 154-165.