Implicit Negotiation in Repeated Games
ATAL '01 Revised Papers from the 8th International Workshop on Intelligent Agents VIII
A framework for sequential planning in multi-agent settings
Journal of Artificial Intelligence Research
The lemonade stand game competition: solving unsolvable games
ACM SIGecom Exchanges
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In repeated multi-agent constant-sum games, each player's objective is to maximize control over a finite set of resources. We introduce Tens potter, an easy-to-use publicly-available game designed to allow human players to compete as agents against a machine algorithm. The algorithm learns play strategies from humans, reduces them to nine basic strategies, and uses this knowledge to build and adapt its collusion strategy. We use a tournament format to test our algorithm against human players as well as against other established multi-agent algorithms taken from the literature. Through these tournament experiments, we demonstrate how learning techniques adapted using human computation--information obtained from both human and machine inputs--can contribute to the development of an algorithm able to defeat two well-established multi-agent machine algorithms in tournament play.