Yu Zhang
ABSTRACT
Techniques that support effective communication during teamwork processes are of particular importance. Psychological study shows that an effective team often can anticipate information exchange among the team and communicate relevant information proactively. Proactive communication is crucial for understanding and sharing common goals and for cooperative actions. Communication can be valuable if it assists agents with new and timely information; it also has cost because it consumes network resources such as bandwidth. To address these issues, we present a new model that uses information production and need to capture the complex multi-agent communication process and a dynamic decision-theoretic determination of communication strategies. We also introduce a generic utility function and an algorithm, DTPC (Decision-Theoretic Proactive Communication), that focuses on representing information production and need of team members and resolving decision interactions among them for making decisions.
- Balch, T. and R. C. Arkin, 1994. Communication in Reactive Multi-agent Robotic Systems. Autonomous Robots, 1(1):27--53. Google Scholar
Digital Library
- Bui, H., D. Kieronska, and S. Venkatesh, 1997. Optimal Communication Among Team Members. Lecture Notes in Artificial Intelligence, 1342: 116--126. Google ScholarDigital Library
- Casella, G., and R. L Berger, Statistical Inference, Duxbury Press, 1990Google Scholar
- Gmytrasiewicz, P. J. and E. H. Durfee, 2000. Rational Communication in Multi-Agent Environments. Autonomous Agents and Multi-Agent Systems, 3(4):233--272. Google ScholarDigital Library
- Jennings, N. R., 1995. Controlling Cooperative Problem Solving in Industrial Multi-Agent Systems Using Joint Intentions. Artificial Intelligence, 75(2). Google ScholarDigital Library
- Kaminka, G. A. and M. Tambe, 2002. Monitoring Teams by Overhearing: A Multi-Agent Plan-Recognition Approach. Journal of Artificial Intelligence Research. Google ScholarDigital Library
- Parsons, S. and M. Wooldridge, 2002. Game Theory and Decision Theory in Multi-Agent Systems. Autonomous Agents and Multi-Agent Systems, 5: 243--254. Google ScholarDigital Library
- Pynadath, D., and M. Tambe, 2002. Multi-Agent Teamwork: Analyzing the Optimality and Complexity of Key Theories and Models. Proceedings of the 1st Autonomous Agents and Multi-Agent System Conference (AAMAS'02). Google ScholarDigital Library
- Russell, S. and P. Norvig, 1995. Artificial Intelligence: A Modern Approach, NJ: Prentice Hall. Google ScholarDigital Library
- Stone, P. and M. Veloso, 1999. Task Decomposition, Dynamic Role Assignment, and Low-Bandwidth Communication for Real-Time Strategic Teamwork. Artificial Intelligence, 110(2): 241--273. Google ScholarDigital Library
- Sycara, K. P. and M. C. Lewis, 1991. Forming Shared Mental Models. Proceedings of 13th Annual Meeting of the Cognitive Science Society, Chicago, pp. 400--405.Google Scholar
- Tambe, M., 1997. Towards Flexible Teamwork. Journal of Artificial Intelligence Research, 7: 83--124. Google ScholarDigital Library
- Wooldridge, M. J., and N. R. Jennings, 1995. Intelligent Agents: Theory and Practice. Knowledge Engineering Review, 10(2).Google ScholarCross Ref
- Xuan, P., V. Lesser, and S. Zilberstein, 2001. Communication Decisions in Multi-Agent Cooperation: Model and Experiments. Proceedings of the 5th International Conference on Autonomous Agents (Agents'01), pp. 616--623. Google ScholarDigital Library
- Yen, J., J. Yin, T. R. Ioerger, M. S. Miller, D. Xu, and R. A. Volz, 2001. CAST: Collaborative Agents for Simulating Teamwork. Proceedigs of International Joint Conference on Artificial Intelligence (IJCAI'01). Google ScholarDigital Library
- Yen, J., X. Fan and R. A. Volz, "Proactive Information Exchanges Based on the Awareness of Teammates' Information Needs", Working Notes of AAMAS 2003 Workshop on Agent Communication Languages and Communication Policies, Melbourne, Australia, July 15, 2003. Google ScholarDigital Library
- Yen, J. X. Fan and R. A. Volz, "On Need-driven Proactive Information Exchanges in Agent Teams," IEEE Computer Society and Web Intelligence Consortium Intelligent Agent Technology 2003, Beijing, China, Oct., 2003. Google ScholarDigital Library
- Zhang, Y., R.A. Volz, T.R. Ioerger, S. Cao, and J. Yen, 2002. Proactive Information Exchange During Team Cooperation. International Conference on Artificial Intelligence (IC-AI'02), pp. 341--346.Google Scholar
- A decision-theoretic approach for designing proactive communication in multi-agent teamwork
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