Teams of agents may not always be developed in a planned, coordinated fashion. Rather, as deployed agents become more common in e-commerce and other settings, there are increasing opportunities for previously unacquainted agents to cooperate in ad hoc team settings. In such scenarios, it is useful for individual agents to be able to collaborate with a wide variety of possible teammates under the philosophy that not all agents are fully rational. This paper considers an agent that is to interact repeatedly with a teammate that will adapt to this interaction in a particular suboptimal, but natural way. We formalize this setting in game-theoretic terms, provide and analyze a fully-implemented algorithm for finding optimal action sequences, prove some theoretical results pertaining to the lengths of these action sequences, and provide empirical results pertaining to the prevalence of our problem of interest in random interaction settings.
|Original language||American English|
|Title of host publication||Agent-Mediated Electronic Commerce|
|Subtitle of host publication||Designing Trading Strategies and Mechanisms for Electronic Markets - IJCAI Workshop, TADA 2009, Selected and Revised Papers|
|Number of pages||15|
|State||Published - 2010|
|Event||2009 Workshop on Trading Agent Design and Analysis, TADA 2009, Co-located with the IJCAI 2009 Conference - Pasadena, CA, United States|
Duration: 13 Jul 2009 → 13 Jul 2009
|Name||Lecture Notes in Business Information Processing|
|Conference||2009 Workshop on Trading Agent Design and Analysis, TADA 2009, Co-located with the IJCAI 2009 Conference|
|Period||13/07/09 → 13/07/09|
Bibliographical noteFunding Information:
This work was supported in part by the German Research Foundation (DFG) as part of the SFB 588 and by the European Commission under project CHIL (contract #506909).