Forming coalitions in the face of uncertain rewards
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Reducing buyer search costs: implications for electronic marketplaces
Management Science - Special issue: Frontier research on information systems and economics
Dynamic pricing by software agents
Computer Networks: The International Journal of Computer and Telecommunications Networking - electronic commerce
Autonomous Agents and Multi-Agent Systems
Coalition formation with uncertain heterogeneous information
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Managing parallel inquiries in agents' two-sided search
Artificial Intelligence
Two-sided bandits and the dating market
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Methods for task allocation via agent coalition formation
Artificial Intelligence
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Anarchy, stability, and utopia: creating better matchings
Autonomous Agents and Multi-Agent Systems
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In this paper we study distributed agent matching in environments characterized by uncertain signals, costly exploration, and the presence of an information broker. Each agent receives information about the potential value of matching with others. This information signal may, however be noisy, and the agent incurs some cost in receiving it. If all candidate agents agree to the matching the team is formed and each agent receives the true unknown utility of the matching, and leaves the market. We consider the effect of the presence of information brokers, or experts, on the outcomes of such matching processes. Experts can, upon payment of a fee, perform the service of disambiguating noisy signals and revealing the true value of a match to any agent. We analyze equilibrium behavior given the fee set by a monopolist expert and use this analysis to derive the revenue maximizing strategy for the expert as the first mover in a Stackelberg game. Surprisingly, we find that better information can hurt: the presence of the expert, even if the use of its services is optional, can degrade both individual agents' utilities and overall social welfare. While in one-sided search the presence of the expert can only help, in two-sided (and general k-sided) search the externality imposed by the fact that others are consulting the expert can lead to a situation where the equilibrium outcome is that everyone consults the expert, even though all agents would be better off if the expert were not present. As an antidote, we show how market designers can enhance welfare by taxing use of expert services.