Abstract
Automated planning techniques are increasingly exploited in real-world applications, thanks to their flexibility and robustness. Hybrid domains, those that require to reason both with discrete and continuous aspects, are particularly challenging to handle with existing planning approaches due to their complex dynamics. In this paper we present a general approach that allows to combine the strengths of automated planning and control systems to support reasoning in hybrid domains. In particular, we propose an architecture to integrate Model Predictive Control (MPC) techniques from the field of control systems into an automated planner, to guide the effective exploration of the search space.
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Bhatti, F., Kitchin, D., Vallati, M. (2019). A General Approach to Exploit Model Predictive Control for Guiding Automated Planning Search in Hybrid Domains. In: Bramer, M., Petridis, M. (eds) Artificial Intelligence XXXVI. SGAI 2019. Lecture Notes in Computer Science(), vol 11927. Springer, Cham. https://doi.org/10.1007/978-3-030-34885-4_10
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DOI: https://doi.org/10.1007/978-3-030-34885-4_10
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