Abstract
Robust autonomous agents should be able to cooperate with new teammates effectively by employing ad hoc teamwork. Reasoning about ad hoc teamwork allows agents to perform joint tasks while cooperating with a variety of teammates. As the teammates may not share a communication or coordination algorithm, the ad hoc team agent adapts to its teammates just by observing them. Whereas most past work on ad hoc teamwork considers the case where the ad hoc team agent has a prior model of its teammate, this paper is the first to introduce an agent that learns models of its teammates autonomously. In addition, this paper presents a new transfer learning algorithmthat can be used when the ad hoc agent only has limited observations about potential teammates.
| Original language | English |
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| Pages | 57-63 |
| Number of pages | 7 |
| State | Published - 2012 |
| Event | 2012 Workshop on Adaptive and Learning Agents, ALA 2012 - Held in Conjunction with the 11th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2012 - Valencia, Spain Duration: 4 Jun 2012 → 5 Jun 2012 |
Conference
| Conference | 2012 Workshop on Adaptive and Learning Agents, ALA 2012 - Held in Conjunction with the 11th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2012 |
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| Country/Territory | Spain |
| City | Valencia |
| Period | 4/06/12 → 5/06/12 |
Keywords
- Ad hoc teams
- Multiagent systems
- Teamwork
All Science Journal Classification (ASJC) codes
- Artificial Intelligence
- Software