Strategy Synthesis for Autonomous Agents Using PRISM

Giaquinta, R., Hoffmann, R., Ireland, M. , Miller, A. and Norman, G. (2018) Strategy Synthesis for Autonomous Agents Using PRISM. In: 10th NASA Formal Methods Symposium (NFM 2018), Newport News, VA, USA, 17-19 Apr 2018, pp. 220-236. ISBN 9783319779348 (doi: 10.1007/978-3-319-77935-5_16)

156231.pdf - Accepted Version



We present probabilistic models for autonomous agent search and retrieve missions derived from Simulink models for an Unmanned Aerial Vehicle (UAV) and show how probabilistic model checking and the probabilistic model checker PRISM can be used for optimal controller generation. We introduce a sequence of scenarios relevant to UAVs and other autonomous agents such as underwater and ground vehicles. For each scenario we demonstrate how it can be modelled using the PRISM language, give model checking statistics and present the synthesised optimal controllers. We conclude with a discussion of the limitations when using probabilistic model checking and PRISM in this context and what steps can be taken to overcome them. In addition, we consider how the controllers can be returned to the UAV and adapted for use on larger search areas.

Item Type:Conference Proceedings
Glasgow Author(s) Enlighten ID:Norman, Dr Gethin and Giaquinta, Dr Ruben and Miller, Professor Alice and Ireland, Dr Murray and Hoffmann, Dr Ruth
Authors: Giaquinta, R., Hoffmann, R., Ireland, M., Miller, A., and Norman, G.
College/School:College of Arts > School of Humanities > Classics
College of Science and Engineering > School of Computing Science
Published Online:11 March 2018
Copyright Holders:Copyright © 2018 Springer International Publishing AG, part of Springer Nature
First Published:First published in Lecture Notes in Computer Science 10811:220-236
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher
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