Abstract
In this paper, we look at the Multi-Agent Meeting Scheduling problem where distributed agents negotiate meeting times on behalf of their users. While many negotiation approaches have been proposed for scheduling meetings, it is not well understood how agents can negotiate strategically in order to maximize their users’ utility. To negotiate strategically, agents need to learn to pick good strategies for negotiating with other agents. We show how the playbook approach, introduced by [1] for team plan selection in small-size robot soccer, can be used to select strategies. Selecting strategies in this way gives some theoretical guarantees about regret. We also show experimental results demonstrating the effectiveness of the approach.
Keywords
- MultiAgent System
- Choice Point
- Negotiation Strategy
- Learning Agent
- Strategy Agent
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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© 2005 Springer-Verlag Berlin Heidelberg
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Crawford, E., Veloso, M. (2005). Learning to Select Negotiation Strategies in Multi-agent Meeting Scheduling. In: Bento, C., Cardoso, A., Dias, G. (eds) Progress in Artificial Intelligence. EPIA 2005. Lecture Notes in Computer Science(), vol 3808. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11595014_57
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DOI: https://doi.org/10.1007/11595014_57
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30737-2
Online ISBN: 978-3-540-31646-6
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