Strategies for Querying Information Agents
CIA '98 Proceedings of the Second International Workshop on Cooperative Information Agents II, Learning, Mobility and Electronic Commerce for Information Discovery on the Internet
Efficient algorithms for learning to play repeated games against computationally bounded adversaries
FOCS '95 Proceedings of the 36th Annual Symposium on Foundations of Computer Science
Adaptive load balancing: a study in multi-agent learning
Journal of Artificial Intelligence Research
Learning models of intelligent agents
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
The evolution and stability of cooperative traits
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 3
Helping based on future expectations
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Predicting agent strategy mix of evolving populations
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Evolving service semantics cooperatively: a consumer-driven approach
Autonomous Agents and Multi-Agent Systems
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Information sharing is important for different goals, such as sharing reputations of sellers among potential buyers, load balancing, solving technical problems, etc. In the short run, providing information as a response to queries is often unbeneficial. In the long run, mechanisms that enable beneficial stable strategies for information exchange can be found. This paper presents such mechanisms and specifies under which conditions it is beneficial to the agents to answer queries. We analyze a model of repeated encounters in which two agents ask each other queriesover time. We present different strategies that enable information exchange, and compare them according to the expected utility for the agents, and the conditions required for the cooperative equilibrium to exist.