The effect of resource limits and task complexity on collaborative planning in dialogue
Artificial Intelligence - Special volume on empirical methods
Learning models of other agents using influence diagrams
UM '99 Proceedings of the seventh international conference on User modeling
Rational Communication in Multi-Agent Environments
Autonomous Agents and Multi-Agent Systems
Multi-Agent Multi-User Modeling in I-Help
User Modeling and User-Adapted Interaction
ETAPP: a framework of agent collaboration under conditions of uncertainty regarding team members
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
ETAPP: a collaboration framework that copes with uncertainty regarding team members
UM'05 Proceedings of the 10th international conference on User Modeling
| Hi-index | 0.00 |
In a collaborative environment, knowledge about collaborators' skills is an important factor when determining which team members should perform a task. However, this knowledge may be incomplete or uncertain. In this paper, we extend our ETAPP (Environment-Task-Agents-Policy-Protocol) collaboration framework by modeling team members that exhibit non-deterministic performance, and comparing two alternative ways of using these models to assign agents to tasks. Our simulation-based evaluation shows that performance variability has a large impact on task performance, and that task performance is improved by consulting agent models built from a small number of observations of agents' recent performance.