Using generalized learning automata for state space aggregation in MAS

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5177 LNAI, Issue PART 1, 2008, Pages 182-193

  De Hauwere, Yann Michaël ^a   Vrancx, Peter ^a   Nowé, Ann ^a  

^a VRIJE UNIVERSITEIT BRUSSEL   (Belgium)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATA THEORY; KNOWLEDGE BASED SYSTEMS; LARGE SCALE SYSTEMS; LEARNING SYSTEMS; REINFORCEMENT LEARNING; ROBOTS; SOFTWARE AGENTS;

DISCRETE STATE SPACE; GENERALIZED LEARNING; INDEPENDENT LEARNING; MULTI-AGENT ALGORITHMS; MULTI-AGENT ENVIRONMENT; MULTI-AGENT LEARNING; MULTI-AGENT REINFORCEMENT LEARNING; MULTI-AGENT SETTING;

MULTI AGENT SYSTEMS;

EID: 57849155854     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-85563-7_28     Document Type: Conference Paper

References (13)

1. Sutton, R.S., Precup, D., Singh, S.P.: Between MDPs and semi-MDPs: A framework for temporal abstraction in reinforcement learning. Artificial Intelligence 112(1-2), 181-211 (1999)
2. Stolle, M., Precup, D.: Learning options in reinforcement learning. In: Koenig, S., Holte, R.C. (eds.) SARA 2002. LNCS (LNAI), vol. 2371, pp. 212-223. Springer, Heidelberg (2002)
3. Boutilier, C.: Planning, learning and coordination in multiagent decision processes. In: Theoretical Aspects of Rationality and Knowledge, pp. 195-201 (1996)
4. Boutilier, C., Dearden, R., Goldszmidt, M.: Exploiting structure in policy construction. In: Mellish, C. (ed.) Proceedings of the 14th International Joint Conference on Artificial Intelligence, pp. 1104-1111. Morgan Kaufmann, San Francisco (1995)
5. Guestrin, C., Koller, D., Parr, R.: Multiagent planning with factored mdps. In: 14th Neural Information Processing Systems (NIPS-14) (2001)
6. Degris, T., Sigaud, O., Wuillemin, P.H.: Learning the structure of factored markov decision processes in reinforcement learning problems. In: Proceedings of the 23rd International Conference on Machine learning, New York, NY, USA, pp. 257-264 (2006)
7. Strehl, A.L., Diuk, C., Littman, M.L.: Efficient structure learning in factored-state mdps. In: AAAI, pp. 645-650. AAAI Press, Menlo Park (2007)
8. Abbeel, P., Koller, D., Ng, A.Y.: Learning factor graphs in polynomial time and sample complexity. Journal of Machine Learning Research 7, 1743-1788 (2006)
9. Boutilier, C.: Planning, Learning and Coordination in Multiagent Decision Processes. In: Proceedings of the Sixth Conference on Theoretical Aspects of Rationality and Knowledge table of contents, pp. 195-210 (1996)
10. Guestrin, C., Hauskrecht, M., Kveton, B.: Solving factored MDPs with continuous and discrete variables. In: Proceedings of the 20th conference on Uncertainty in artificial intelligence, pp. 235-242 (2004)
11. Williams, R.: Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning. Reinforcement Learning 8, 229-256 (1992)
12. Thathachar, M., Sastry, P.: Networks of Learning Automata: Techniques for Online Stochastic Optimization. Kluwer Academic Pub., Dordrecht (2004)
13. Phansalkar, V., Thathachar, M.: Local and global optimization algorithms for generalized learning automata. Neural Computation 7(5), 950-973 (1995)