Detecting commitment abandonment by monitoring sub-optimal steps during plan execution

Ramon Fraga Pereira, Nir Oren, Felipe Meneguzzi

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

5 Citations (Scopus)

Abstract

Assessing whether an agent has abandoned a goal is important when multiple agents are trying to achieve joint goals, or when agents commit to achieving goals for each other. Making such an inference for a single goal by observing only plan traces is not a trivial task because agents often deviate from the optimal plans for various reasons, including the pursuit of multiple goals or the inability to act optimally. In this paper, we develop an approach that uses plan optimality monitoring techniques to determine whether an agent will honour a commitment. Specifically, to determine commitment abandonment, we use these techniques with planning fact partitions (e.g., dead-ends). Our approach is domain-independent and detects commitment abandonment in nearly all cases.
Original languageEnglish
Title of host publicationAAMAS '17 Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems
EditorsKate Larson, Michael Winikoff, Sanmay Das, Edmund Durfee
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Pages1685-1687
Number of pages3
Volume3
ISBN (Electronic)9781510855076
Publication statusPublished - 8 May 2017
Event16th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2017 - Sao Paulo, Brazil
Duration: 8 May 201712 May 2017

Conference

Conference16th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2017
CountryBrazil
CitySao Paulo
Period8/05/1712/05/17

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Keywords

  • Abandonment
  • Commitments
  • Goals
  • Plan execution

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software
  • Control and Systems Engineering

Cite this

Pereira, R. F., Oren, N., & Meneguzzi, F. (2017). Detecting commitment abandonment by monitoring sub-optimal steps during plan execution. In K. Larson, M. Winikoff, S. Das, & E. Durfee (Eds.), AAMAS '17 Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems (Vol. 3, pp. 1685-1687). International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS).