AAAI 2021
Efficient Querying for Cooperative Probabilistic Commitments
Abstract
Multiagent systems can use commitments as the core of a general coordination infrastructure, supporting both cooperative and non-cooperative interactions. Agents whose objectives are aligned, and where one agent can help another achieve greater reward by sacrificing some of its own reward, should choose a cooperative commitment to maximize their joint reward. We present a solution to the problem of how cooperative agents can efficiently find an (approximately) optimal commitment by querying about carefully-selected commitment choices. We prove structural properties of the agents’ values as functions of the parameters of the commitment specification, and develop a greedy method for composing a query with provable approximation bounds, which we empirically show can find nearly optimal commitments in a fraction of the time methods that lack our insights require.
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Context
- Venue
- AAAI Conference on Artificial Intelligence
- Archive span
- 1980-2026
- Indexed papers
- 28718
- Paper id
- 137484959252371910