Online Action Recognition

Authors

  • Alejandro Suárez-Hernández Institut de Robòtica i Informàtica Industrial, CSIC-UPC, Barcelona
  • Javier Segovia-Aguas Institut de Robòtica i Informàtica Industrial, CSIC-UPC, Barcelona Universitat Pompeu Fabra, Barcelona
  • Carme Torras Institut de Robòtica i Informàtica Industrial, CSIC-UPC, Barcelona
  • Guillem Alenyà Institut de Robòtica i Informàtica Industrial, CSIC-UPC, Barcelona

Keywords:

Activity and Plan Recognition, Applications, Knowledge Acquisition, Deterministic Planning

Abstract

Recognition in planning seeks to find agent intentions, goals or activities given a set of observations and a knowledge library (e.g. goal states, plans or domain theories). In this work we introduce the problem of Online Action Recognition. It consists in recognizing, in an open world, the planning action that best explains a partially observable state transition from a knowledge library of first-order STRIPS actions, which is initially empty. We frame this as an optimization problem, and propose two algorithms to address it: Action Unification (AU) and Online Action Recognition through Unification (OARU). The former builds on logic unification and generalizes two input actions using weighted partial MaxSAT. The latter looks for an action within the library that explains an observed transition. If there is such action, it generalizes it making use of AU, building in this way an AU hierarchy. Otherwise, OARU inserts a Trivial Grounded Action (TGA) in the library that explains just that transition. We report results on benchmarks from the International Planning Competition and PDDLGym, where OARU recognizes actions accurately with respect to expert knowledge, and shows real-time performance.

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Published

2021-05-18

How to Cite

Suárez-Hernández, A., Segovia-Aguas, J., Torras, C., & Alenyà, G. (2021). Online Action Recognition. Proceedings of the AAAI Conference on Artificial Intelligence, 35(13), 11981-11989. Retrieved from https://ojs.aaai.org/index.php/AAAI/article/view/17423

Issue

Section

AAAI Technical Track on Planning, Routing, and Scheduling