Capability models and their applications in planning

Yu Zhang, Sarath Sreedharan, Subbarao Kambhampati

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

One important challenge for a set of agents to achieve more efficient collaboration is for these agents to maintain proper models of each other. An important aspect of these models of other agents is that they are often not provided, and hence must be learned from plan execution traces. As a result, these models of other agents are inherently partial and incomplete. Most existing agent models are based on action modeling and do not naturally allow for incompleteness. In this paper, we introduce a new and inherently incomplete modeling approach based on the representation of capabilities, which has several unique advantages. First, we show that the structures of capability models can be learned or easily specified, and both model structure and parameter learning are robust to high degrees of incompleteness in plan traces (e.g., with only start and end states partially observed). Furthermore, parameter learning can be performed efficiendy online via Bayesian learning. While high degrees of incompleteness in plan traces presents learning challenges for traditional (complete) models, capability models can still learn to extract useful information. As a result, capability models are useful in applications in which traditional models are difficult to obtain, or models must be learned from incomplete plan traces, e.g., robots learning human models from observations and interactions. Furthermore, we discuss using capability models for single agent planning, and then extend it to multi-agent planning (with each agent modeled separately by a capability model), in which the capability models of agents are used by a centralized planner. The limitation, however, is that the synthesized "plans" (called c-plans) are incomplete, i.e., there may or may not be a complete plan for a c-plan. This is, however, unavoidable for planning using partial and incomplete models (e.g., considering planning using action models learned from partial and noisy plan traces).

Original languageEnglish (US)
Title of host publicationProceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Pages1151-1159
Number of pages9
Volume2
ISBN (Print)9781450337700
StatePublished - 2015
Event14th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2015 - Istanbul, Turkey
Duration: May 4 2015May 8 2015

Other

Other14th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2015
CountryTurkey
CityIstanbul
Period5/4/155/8/15

Keywords

  • Agent theories and models
  • Capability models
  • Teamwork in humanagent mixed networks

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software
  • Control and Systems Engineering

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  • Cite this

    Zhang, Y., Sreedharan, S., & Kambhampati, S. (2015). Capability models and their applications in planning. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS (Vol. 2, pp. 1151-1159). International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS).