Reducing buyer search costs: implications for electronic marketplaces
Management Science - Special issue: Frontier research on information systems and economics
Coalition structure generation with worst case guarantees
Artificial Intelligence
A stable and efficient buyer coalition formation scheme for e-marketplaces
Proceedings of the fifth international conference on Autonomous agents
Autonomous Agents and Multi-Agent Systems
Customer Coalitions in Electronic Markets
Agent-Mediated Electronic Commerce III, Current Issues in Agent-Based Electronic Commerce Systems (includes revised papers from AMEC 2000 Workshop)
Coalition Formation for Large-Scale Electronic Markets
ICMAS '00 Proceedings of the Fourth International Conference on MultiAgent Systems (ICMAS-2000)
Mechanisms for coalition formation and cost sharing in an electronic marketplace
ICEC '03 Proceedings of the 5th international conference on Electronic commerce
Ontology-guided learning to improve communication between groups of agents
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Mathematics of Operations Research
Collaborative multi agent physical search with Probabilistic knowledge
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Taxed congestion games with failures
Annals of Mathematics and Artificial Intelligence
Multi-goal economic search using dynamic search structures
Autonomous Agents and Multi-Agent Systems
On the existence of optimal taxes for network congestion games with heterogeneous users
SAGT'10 Proceedings of the Third international conference on Algorithmic game theory
Designing incentives for Boolean games
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Sequential Multilateral Search for a Common Goal
WI-IAT '11 Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Volume 02
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This paper considers the problem of self-interested agents engaged in costly exploration when individual findings benefit all agents. The purpose of the exploration is to reason about the nature and value of the different opportunities available to the agents whenever such information is a priori unknown. While the problem has been considered for the case where the goal is to maximize the overall expected benefit, the focus of this paper is on settings where the agents are self-interested, i.e, each agent's goal is to maximize its individual expected benefit. The paper presents an equilibrium analysis of the model, considering both mixed and pure equilibria. The analysis is used to demonstrate two somehow non-intuitive properties of the equilibrium cooperative exploration strategies used by the agents and their resulting expected payoffs: (a) when using mixed equilibrium strategies, the agents might lose due to having more potential opportunities available for them in their environment, and (b) if the agents can have additional agents join them in the exploration they might prefer the less competent ones to join the process.