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Ad Hoc Teamwork Modeled with Multi-armed Bandits: An Extension to Discounted Infinite Rewards.
Samuel
Barrett and Peter Stone.
In Tenth International Conference on Autonomous
Agents and Multiagent Systems - Adaptive Learning Agents Workshop (AAMAS - ALA), May 2011.
[PDF]136.1kB [postscript]384.8kB
Before deployment, agents designed for multiagent team settings are commonly developed together or are given standardized communication and coordination protocols. However, in many cases this pre-coordination is not possible because the agents do not know what agents they will encounter, resulting in ad hoc team settings. In these problems, the agents must learn to adapt and cooperate with each other on the fly. We extend existing research on ad hoc teams, providing theoretical results for handling cooperative multi-armed bandit problems with infinite discounted rewards.
@InProceedings{AAMAS11-ALA-Barrett,
author = {Samuel Barrett and Peter Stone},
title = {Ad Hoc Teamwork Modeled with Multi-armed Bandits: An Extension to Discounted Infinite Rewards},
booktitle = {Tenth International Conference on Autonomous Agents and Multiagent Systems - Adaptive Learning Agents Workshop (AAMAS - ALA)},
location = {Taipei, Taiwan},
month = {May},
year = {2011},
abstract={Before deployment, agents designed for multiagent team settings are commonly developed together or are given standardized communication and coordination protocols. However, in many cases this pre-coordination is not possible because the agents do not know what agents they will encounter, resulting in ad hoc team settings. In these problems, the agents must learn to adapt and cooperate with each other on the fly. We extend existing research on ad hoc teams, providing theoretical results for handling cooperative multi-armed bandit problems with infinite discounted rewards.}
}
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