Using reinforcement learning to coordinate better

Computational Intelligence

Volumn 21, Issue 3, 2005, Pages 217-245

  Excelente Toledo, Cora B ^a   Jennings, Nicholas R ^b  

^a National Laboratory of Advanced Informatics Xalapa   (Mexico)

^b UNIVERSITY OF SOUTHAMPTON   (United Kingdom)

Author keywords

Agent interaction; Collaborative agents; Coordination; Reinforcement learning

Indexed keywords

AUTONOMOUS AGENTS; COMPUTATIONAL METHODS; COMPUTER SCIENCE; COMPUTER SUPPORTED COOPERATIVE WORK; DECISION MAKING; INFORMATION TECHNOLOGY;

AGENT INTERACTION; COLLABORATIVE AGENTS; COORDINATION; REINFORCEMENT LEARNING;

LEARNING SYSTEMS;

EID: 27644453173     PISSN: 08247935     EISSN: 14678640     Source Type: Journal    
DOI: 10.1111/j.1467-8640.2005.00272.x     Document Type: Article

References (38)

1. BARBER, K. S., D. C. HAN, and T. H. Liu. 2000. Coordinating distributed decision making using reusable interaction specifications. In Design and Applications of Intelligent Agents: Third Pacific Rim International Workshop on Multi-Agents (PRIMA 2000). Melbourne, Australia, pp. 1-15.
2. BOURNE, R. A., C. B. EXCELENTE-TOLEDO, and N. R. JENNINGS. 2000. Run-time selection of coordination mechanisms in multi-agent systems. In Proceedings of the 14th European Conference on Artificial Intelligence (ECAI-2000), pp. 348-352.
3. BOUTILIER, C. 1999. Sequential optimality and coordination in multiagent systems. In Proceedings of the sixteenth International Joint Conference on Artificial Intelligence (IJCAI-99). Stockholm, Sweden, pp. 478-485.
4. CLAUS, C., and C. BOUTILIER. 1998. The dynamics of reinforcement learning in cooperative multiagent systems. In Proceedings of fifteenth National Conference on Artificial Intelligence (AAAI-98). Madison, MI, pp. 746-752.
5. COHEN, P. R. 1995. Empirical Methods for Artificial Intelligence. The MIT Press: Cambridge, MA.
6. DURFEE, E. H. 1999. Practically coordinating. AI Magazine, 20(1): 99-116.
7. DURFEE, E. H., and V. R. LESSER. 1991. Partial global planning: A coordination framework for distributed hypothesis formation. IEEE Transactions on Systems, Man, and Cybernetics, 21(5): 1167-1183.
8. EXCELENTE-TOLEDO, C. B. 2003. The dynamic selection of coordination mechanisms. Ph.D. Thesis, Department of Electronics and Computer Science, University of Southampton. Available at http://eprints.ecs.soton.ac.uk/7814/.
9. EXCELENTE-TOLEDO, C. B., R. A. BOURNE, and N. R. JENNINGS. 2001. Reasoning about commitments and penalties for coordination between autonomous agents. In Proceedings of the fifth International Conference on Autonomous Agents (AGENTS'01). Montreal, Quebec, Canada, pp. 131-138.
10. EXCELENTE-TOLEDO, C. B., and N. R. JENNINGS. 2002. Learning to select a coordination mechanism. In Proceedings of the first International Joint Conference on Autonomous Agents & Multi-Agent Systems (AAMAS'02). Bologna, Italy, pp. 1106-1113.
11. EXCELENTE-TOLEDO, C. B., and N. R. JENNINGS. 2003. Learning when and how to coordinate. Web Intelligence and Agent Systems: An International Journal, 1(3-4): 203-218.
12. EXCELENTE-TOLEDO, C. B., and N. R. JENNINGS. 2004. The dynamic selection of coordination mechanisms. Journal of Autonomous Agents and Multi-Agent Systems, 9(1-2): 55-85.
13. FOX, M. S. 1981. An organizational view of distributed systems. IEEE Transactions on Systems, Man, and Cybernetics, 11(1): 70-80.
14. GALBRAITH, J. 1973. Designing Complex Organizations. Addison-Wesley Publishing Company, Inc. Reading, MA.
15. GARLAND, A., and R. ALTERMAN. 2001. Learning procedural knowledge to better coordinate. In Proceedings of Seventeenth International Joint Conference on Artificial Intelligence (IJCAI-01). Edited by B. NEBEL. AAAI Press, Seattle, Washington, Menlo Park, CA, pp. 1073-1083.
16. GARLAND, A., and R. ALTERMAN. 2004. Autonomous agents that learn to better coordinate. Autonomous Agents and Multi-Agent Systems, 8(3): 267-301.
17. HU, J., and M. P. WELLMAN. 1998. Online learning about other agents in a dynamic multiagent system. In Proceedings of second International Conference on Autonomous Agents (AGENTS'98). Minneapolis, MN, pp. 239-246.
18. HUHNS, M. N., and L. M. STEPHENS. 1999. Multiagent systems and society of agents. In Multiagent Systems: A Modern Approach To Distributed Artificial Intelligence, Chapter 2. Edited by G. WEISS. The MIT Press, Cambridge, MA, pp. 79-120.
19. JENNINGS, N. R. 1993. Commitments and conventions: The foundation of coordination in multi-agent systems. The Knowledge Engineering Review, 8(3): 223-250.
20. JENNINGS, N. R. 2000. On agent-based software engineering. Artificial Intelligence, 117(2): 277-296.
21. KAELBLING, L. P., M. L. LITTMAN, and A. W. MOORE. 1996. Reinforcement learning: A survey. Journal of Artificial Intelligence Research, 4(4): 237-285.
22. LANE, D. M. 2001. Hyperstat online textbook, http://davidmlane.com/ hyperstat/January/2003.
23. MALONE, T. W. 1987. Modeling coordination in organizations and markets. Management Science, 33(10): 1317-1332.
24. NAGAYUKI, Y., S. ISHII, and K. DOYA. 2000. Multi-agent reinforcement learning: An approach based on the other agent's internal model. In Proceedings on the fourth International Conference on Multi-Agent Systems (ICMAS-00). Boston, MA, pp. 215-221.
25. PRASAD, M. V. N., and V. R. LESSER. 1999. Learning situation-specific coordination in cooperative multi-agent systems. Autonomous Agents and Multi-Agent Systems, 2(2): 173-207.
26. ROSENSCHEIN, J. S., and G. ZLOTKIN. 1994. Rules of Encounter: Designing Conventions for Automated Negotiation among Computers. The MIT Press: Cambridge, MA.
27. RUSSELL, S. J., and P. NORVIG. 1995. Reinforcement learning. In Artificial Intelligence: A Modern Approach, Learning, Chapter 20, pp. 598-624. Prentice Hall: Upple Saddle River, NJ.
28. SEN, S., M. SEKARAN, and J. HALE. 1994. Learning to cooperate without sharing information. In Proceedings of the twelfth National Conference on Artificial Intelligence (AAAI-94). Amherst, MA, pp. 426-431.
29. SEN, S., and G. WEISS. 1999. Learning in multiagent systems. In Multiagent Systems: A Modern Approach To Distributed Artificial Intelligence, Chapter 6. Edited by G. WEISS. The MIT Press, Cambridge, MA, pp. 259-298.
30. SHOHAM, Y., and M. TENNENHOLTZ. 1992. On the synthesis of useful social laws for artificial agent societies. In Proceedings of the Tenth National Conference on Artificial Intelligence (AAAI-92). San Jose, California, pp. 276-281.
31. SINGH, S. P., T. JAAKKOLA, M. L. LITTMAN, and C. SZEPESVARI. 2000. Convergence results for single-step on-policy reinforcement-learning algorithms. Machine Learning, 38(3): 287-308.
32. SMITH, R. G., and R. DAVIS. 1981. Frameworks for cooperation in distributed problem solving. IEEE Transactions on Systems, Man, and Cybernetics, 11(1): 61-70.
33. STONE, P., andM. VELOSO. 2000. Multiagent systems: A survey from a machine learning perspective. Autonomous Robots, 3(8): 345-383.
34. SUGAWARA, T., and V R. LESSER. 1998. Learning to improve coordinated actions in cooperative distributed problem-solving environments. Machine Learning, 33(2/3): 129-153.
35. SUTTON, R. S., and G. A. BARTO. 1998. Reinforcement Learning: An introduction. The MIT Press: Cambridge, MA.
36. TAN, M. 1993. Multi-agent reinforcement learning: Independent vs cooperative agents. In Proceedings of the tenth International Conference on Machine Learning. Amherst, MA, pp. 330-337.
37. VIDAL, J. M., and E. H. DURFEE. 1997. Agents learning about agents: A framework and analysis. In Collected papers from the AAAI-97 workshop on Multiagent Learning Providence, Rhode Island.
38. WATKINS, C. J. C. H., and P. DAYAN. 1992. Technical note: Q-learning. Machine Learning, 8: 279-292.