Mixed Discrete Continuous Non-Linear Planning through Piecewise Linear Approximation

Authors

  • Elad Denenberg King’s College London
  • Amanda Coles King’s College London

Abstract

Reasoning with continuously changing numeric quantities is vital to applying planners in many real-world scenarios. Several planners capable of doing this have been developed recently. Scalability remains a challenge for such planners, especially those that reason with non-linear continuous change. In this paper, we present a novel approach to reasoning with non-linear domains. Bounding the problem using linear over and under-estimators, allows us to use scalable planners that handle linear change to find plans for non-linear domains. We compare the performance of our approach to existing planners on several domains and demonstrate that our planner can achieve state-of-the-art performance in non-linear planning.

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Published

2021-05-25

How to Cite

Denenberg, E., & Coles, A. (2021). Mixed Discrete Continuous Non-Linear Planning through Piecewise Linear Approximation. Proceedings of the International Conference on Automated Planning and Scheduling, 29(1), 137-145. Retrieved from https://ojs.aaai.org/index.php/ICAPS/article/view/3469