Goal Recognition with Timing Information


  • Chenyuan Zhang The University of Melbourne
  • Charles Kemp The University of Melbourne
  • Nir Lipovetzky The University of Melbourne




Plan recognition, plan management, and goal reasoning, Human-aware planning and scheduling, Planning with time and resources


Goal recognition has been extensively studied by AI researchers, but most algorithms take only observed actions as input. Here we argue that the time taken to carry out these actions provides an additional signal that supports goal recognition. We present a behavioral experiment confirming that people use timing information in this way, and develop and evaluate a goal recognition algorithm that is sensitive to both actions and timing information. Our results suggest that existing goal recognition algorithms can be improved by incorporating a model of planning time on both synthetic data and human data, and that these improvements can be substantial in scenarios in which relatively few actions have been observed.




How to Cite

Zhang, C., Kemp, C., & Lipovetzky, N. (2023). Goal Recognition with Timing Information. Proceedings of the International Conference on Automated Planning and Scheduling, 33(1), 443-451. https://doi.org/10.1609/icaps.v33i1.27224