AAAI Publications, Thirty-First AAAI Conference on Artificial Intelligence

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Nurturing Group-Beneficial Information-Gathering Behaviors Through Above-Threshold Criteria Setting
Igor Rochlin, David Sarne, Maytal Bremer, Ben Grynhaus

Last modified: 2017-02-12

Abstract


This paper studies a criteria-based mechanism for nurturing and enhancing agents' group-benefiting individual efforts whenever the agents are self-interested. The idea is that only those agents that meet the criteria get to benefit from the group effort, giving an incentive to contribute even when it is otherwise individually irrational. Specifically, the paper provides a comprehensive equilibrium analysis of a threshold-based criteria mechanism for the common cooperative information gathering application, where the criteria is set such that only those whose contribution to the group is above some pre-specified threshold can benefit from the contributions of others. The analysis results in a closed form solution for the strategies to be used in equilibrium and facilitates the numerical investigation of different model properties as well as a comparison to the dual mechanism according to only an agent whose contribution is below the specified threshold gets to benefit from the contributions of others. One important contribution enabled through the analysis provided is in showing that, counter-intuitively, for some settings the use of the above-threshold criteria is outperformed by the use of the below-threshold criteria as far as collective and individual performance is concerned.

Keywords


Multi-Agent Exploration; Self-Interested Agents; Cooperation; Teamwork; Economically-Motivated Agents

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