A Framework for Plan Library Evolution in BDI Agent Systems

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Abstract

The Belief-Desire-Intention (BDI) paradigm is a flexible framework for representing intelligent agents. Practical BDI agent systems rely on a static plan library to reduce the planning problem to the simpler problem of plan selection. However, fixed pre-defined plan libraries are unable to adapt to fast-changing environments pervaded by uncertainty. In this paper, we advance the state-of-the-art in BDI agent systems by proposing a plan library evolution architecture with mechanisms to incorporate new plans (plan expansion) and drop old/unsuitable plans (plan contraction) to adapt to changes in a realistic environment. The proposal follows a principled approach to define plan library expansion and contraction operators, motivated by postulates that clearly highlight the underlying assumptions, and quantified by decision-support measures of temporal information. In particular, we demonstrate the feasibility of the proposed contraction operator by presenting a multi-criteria argumentation based decision making to remove plans exemplified in a planetary vehicle scenario.
Original languageEnglish
Title of host publication2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI 2018)
Subtitle of host publicationProceedings of a meeting held 5-7 November 2018, Volos, Greece
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages414-421
Number of pages8
ISBN (Electronic)9781538674499
ISBN (Print)9781538674505
DOIs
Publication statusPublished - Feb 2019

Publication series

NameInternational Conference on Tools with Artificial Intelligence (ICTAI)
ISSN (Electronic)2375-0197

Keywords

  • libraries
  • planning
  • plan library expansion/contraction
  • multi-criteria decision making
  • BDI agent systems

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  • Cite this

    Xu, M., Bauters, K., McAreavey, K., & Liu, W. (2019). A Framework for Plan Library Evolution in BDI Agent Systems. In 2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI 2018): Proceedings of a meeting held 5-7 November 2018, Volos, Greece (pp. 414-421). (International Conference on Tools with Artificial Intelligence (ICTAI)). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ICTAI.2018.00071