Learning organizational roles for negotiated search in a multiagent system

International Journal of Human Computer Studies

Volumn 48, Issue 1, 1998, Pages 51-67

  Nagendra Prasad, M V ^a   Lesser, Victor R ^a   Lander, Susan E ^b  

^a Biologically Inspired Neural and Dynamical Systems Laboratory   (United States)

^b Blackboard Technology   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; HUMAN COMPUTER INTERACTION;

MULTIAGENT SYSTEMS (MAS);

LEARNING SYSTEMS;

EID: 0031701693     PISSN: 10715819     EISSN: None     Source Type: Journal    
DOI: 10.1006/ijhc.1997.0160     Document Type: Article

References (18)

1. A. BARTO, R. S. & WATKINS, C. (1990). Learning and sequential decision making. In M. GARIEL & J. W. MOORE, Eds. Learning and Computational Neuroscience. Cambridge, MA: MIT Press.
2. GARLAND, A. & ALTERMAN, R. (1996). Multi-agent learning through collective memory. In Proceedings of the AAAI Spring Symposium on Adaptation, Co-evolution and Learning in Multiagent Systems. Stanford, CA.
3. HOLLAND, J. H. (1985). Properties of bucket brigade algorithm. In Proceedings of the 1st International Conference on Genetic Algorithms and their Applications, pp. 1-7. Pittsburgh, PA.
4. LANDER, S. E. (1994). Distributed search in heterogeneous and reusable multi-agent systems. Ph.D. Thesis, Dept. of Computer Science, University of Massachusetts, Amherst.
5. LANDER, S. E. & LESSER, V. R. (1994). Sharing meta-information to guide cooperative search among heterogeneous reusable agents. Computer Science Technical Report 94-48, University of Massachusetts. IEEE Transactions on Knowledge and Data Engineering, (to appear).
6. LESSER, V. R. & ERMAN, L. D. (1980). Distributed interpretation: a model and an experiment. IEEE Transactions on Computers, C-29, 1144-1163.
7. MATARIC, M. J. (1994). Reward functions for accelerated learning. In Proceedings of the 11th International Conference on Machine Learning, San Francisco, CA.
8. NAGENDRA PRASAD, M. V., LESSER, V. R. & LANDER, S. E. (1996). Retrieval and reasoning in distributed case bases. Journal of Visual Communication and Image Representation, Special Issue on Digital Libraries, 7, 74-87.
9. SANDHOLM, T. & CRITES, R. (to appear). Multi-agent reinforcement learning in the repeated prisoner's dilemma. Biosystems.
10. SANDHOLM, T. & NAGENDRA PRASAD, M. V. (1993). Muscle: multi-agent system for coordinated learning experiments. Unpublished working paper.
11. SEN, S., SEKARAN, M. & HALE, J. (1994). Learning to coordinate without sharing information. In Proceedings of the 12th National Conference on Artificial Intelligence, pp. 426-431. Seattle, WA. New York: AAAI.
12. SIAN, S. S. (1991). Extending learning to multiple agents: issues and a model for multi-agent machine learning. In Proceedings of Machine Learning-EWSL 91, pp. 440-456. Berlin: Springer.
13. SILVER, B., FRAWELY, W., IBA, G., VITTAL, J. & BRADFORD, K. (1990). A framework for multi-paradigmatic learning. In Proceedings of the 7th International Conference on Machine Learning, pp. 348-358.
14. SUGAWARA, T. LESSER, V. R. (1993). On-line learning of coordination plans. In Procedings of the 12th International Workshop on Distributed AI, Hidden Valley, PA.
15. SUTTON, R. (1988). Learning to predict by the methods of temporal differences. Machine Learning, 3, 9-44.
16. TAN, M. (1993). Multi-agent reinforcement learning: independent vs. cooperative agents. In Proceedings of the 10th International Conference on Machine Learning, pp. 330-337.
17. WEISS, G. (1994). Some studies in distributed machine learning and organizational design. Technical Report FKI-189-94, Institut für Informatik, TU München.
18. WHITEHAIR, R. & LESSER, V. R. (1993). A framework for the analysis of sophisticated control in interpretation systems. Computer Science Technical Report 93-53, University of Massachusetts.