A General Approach to Exploit Model Predictive Control for Guiding Automated Planning Search in Hybrid Domains

Faizan Bhatti, Diane Kitchin, Mauro Vallati

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.
Original languageEnglish
Title of host publicationArtificial Intelligence XXXVI
Subtitle of host publication39th SGAI International Conference on Artificial Intelligence, AI 2019, Cambridge, UK, December 17–19, 2019, Proceedings
EditorsMax Bramer, Miltos Petridis
Place of PublicationCham
PublisherSpringer Nature Switzerland AG
Pages139-145
Number of pages7
Edition1st
ISBN (Electronic)9783030348854
ISBN (Print)9783030348847
DOIs
Publication statusPublished - 9 Jan 2020
Event39th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence - Peterhouse College, Cambridge, Cambridge, United Kingdom
Duration: 17 Dec 201919 Dec 2019
Conference number: 39
http://www.bcs-sgai.org/ai2019/?section=call

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11927 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference39th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence
Abbreviated titleAI 2019
Country/TerritoryUnited Kingdom
CityCambridge
Period17/12/1919/12/19
Internet address

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