An LP-Based Approach for Goal Recognition as Planning

Authors

  • Luísa R. A. Santos Universidade Federal do Rio Grande do Sul
  • Felipe Meneguzzi Pontifical Catholic University of Rio Grande do Sul
  • Ramon Fraga Pereira Sapienza Università di Roma
  • André Grahl Pereira Universidade Federal do Rio Grande do Sul

Keywords:

Activity and Plan Recognition

Abstract

Goal recognition aims to recognize the set of candidate goals that are compatible with the observed behavior of an agent. In this paper, we develop a method based on the operator-counting framework that efficiently computes solutions that satisfy the observations and uses the information generated to solve goal recognition tasks. Our method reasons explicitly about both partial and noisy observations: estimating uncertainty for the former, and satisfying observations given the unreliability of the sensor for the latter. We evaluate our approach empirically over a large data set, analyzing its components on how each can impact the quality of the solutions. In general, our approach is superior to previous methods in terms of agreement ratio, accuracy, and spread. Finally, our approach paves the way for new research on combinatorial optimization to solve goal recognition tasks.

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Published

2021-05-18

How to Cite

Santos, L. R. A., Meneguzzi, F., Fraga Pereira, R., & Pereira, A. G. (2021). An LP-Based Approach for Goal Recognition as Planning. Proceedings of the AAAI Conference on Artificial Intelligence, 35(13), 11939-11946. Retrieved from https://ojs.aaai.org/index.php/AAAI/article/view/17418

Issue

Section

AAAI Technical Track on Planning, Routing, and Scheduling