Learning and predicting dynamic networked behavior with graphical multiagent models

11th International Conference on Autonomous Agents and Multiagent Systems 2012, AAMAS 2012: Innovative Applications Track

Volumn 1, Issue , 2012, Pages 336-343

  Duong, Quang ^a   Wellman, Michael P ^a   Singh, Satinder ^a   Kearns, Michael ^b  

^a UNIVERSITY OF MICHIGAN   (United States)

^b UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

Dynamic behavior; Graphical models; Structure learning

Indexed keywords

AUTONOMOUS AGENTS; COMPLEX NETWORKS; EXPERIMENTS; MULTI AGENT SYSTEMS;

AGENT INTERACTION; DYNAMIC BEHAVIORS; EMPIRICAL STUDIES; GRAPHICAL MODEL; GRAPHICAL STRUCTURES; GREEDY ALGORITHMS; MULTI-AGENT MODEL; STRUCTURE-LEARNING;

BEHAVIORAL RESEARCH;

EID: 84899408692     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (12)

1. J. Y. Broadway, J. S. Yedidia, W. T. Freeman, and Y. Weiss. Generalized belief propagation. In Thirteenth Annual Conference on Advances in Neural Information Processing Systems, pages 689-695, Denver, 2000.
2. C. Daskalakis and C. H. Papadimitriou. Computing pure Nash equilibria in graphical games via Markov random fields. In Seventh ACM conference on Electronic Commerce, pages 91-99, Ann Arbor, MI, 2006.
3. Q. Duong, M. P. Wellman, and S. Singh. Knowledge combination in graphical multiagent models. In Twenty-Fourth Conference on Uncertainty in Artificial Intelligence, pages 153-160, Helsinki, 2008.
4. Q. Duong, M. P. Wellman, S. Singh, and Y. Vorobeychik. History-dependent graphical multiagent models. In Ninth International Conference on Autonomous Agents and Multiagent Systems, pages 1215-1222, Toronto, 2010.
5. Y. Gal and A. Pfeffer. Networks of influence diagrams: A formalism for representing agents' beliefs and decision-making processes. Journal of Artificial Intelligence Research, 33:109-147, 2008.
6. A. X. Jiang, K. Leyton-Brown, and N. A. R. Bhat. Action-graph games. Games and Economic Behavior, 71:141-173, 2010.
7. S. Kakade, M. Kearns, J. Langford, and L. Ortiz. Correlated equilibria in graphical games. In Fourth ACM Conference on Electronic Commerce, pages 42-47, San Jose, CA, 2003.
8. M. Kearns, S. Judd, J. Tan, and J. Wortman. Behavioral experiments on biased voting in networks. Proceedings of the National Academy of Sciences, 106(5):1347-1352, 2009.
9. M. Kearns, M. L. Littman, and S. Singh. Graphical models for game theory. In Seventeenth Conference on Uncertainty in Artificial Intelligence, pages 253-260, Seattle, 2001.
10. M. Kearns and J. Tan. Biased voting and the Democratic primary problem. In Fourth International Workshop on Internet and Network Economics, pages 639-652, Shanghai, 2008.
11. D. Koller and B. Milch. Multi-agent influence diagrams for representing and solving games. Games and Economic Behavior, 45:181-221, 2003.
12. M. E. J. Newman. Mixing patterns in networks. Physical Review E, 67(2), 2003.