Skip to main content

Verifying Strategic Abilities of Neural-symbolic Multi-agent Systems

Akintunde, Michael E., Botoeva, Elena, Kouvaros, Panagiotis, Lomuscio, Alessio (2020) Verifying Strategic Abilities of Neural-symbolic Multi-agent Systems. In: Proceedings of the 17th International Conference on Principles of Knowledge Representation and Reasoning. Proceedings of the 17th International Conference on Principles of Knowledge Representation and Reasoning. . pp. 22-32. International Joint Conferences on Artificial Intelligence Organization ISBN 978-0-9992411-7-2. (doi:10.24963/kr.2020/3) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:90813)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL
https://doi.org/10.24963/kr.2020/3

Abstract

We investigate the problem of verifying the strategic properties of multi-agent systems equipped with machine learning-based perception units. We introduce a novel model of agents comprising both a perception system implemented via feed-forward neural networks and an action selection mechanism implemented via traditional control logic. We define the verification problem for these systems against a bounded fragment of alternating-time temporal logic. We translate the verification problem on bounded traces into the feasibility problem of mixed integer linear programs and show the soundness and completeness of the translation. We show that the lower bound of the verification problem is PSPACE and the upper bound is coNEXPTIME. We present a tool implementing the compilation and evaluate the experimental results obtained on a complex scenario of multiple aircraft operating a recently proposed prototype for air-traffic collision avoidance.

Item Type: Conference or workshop item (Paper)
DOI/Identification number: 10.24963/kr.2020/3
Uncontrolled keywords: Reasoning about knowledge; beliefs; and other mental attitudes-General; Neural-symbolic learning-General;
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 75 Electronic computers. Computer science
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Amy Boaler
Date Deposited: 12 Oct 2021 13:44 UTC
Last Modified: 13 Oct 2021 10:44 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/90813 (The current URI for this page, for reference purposes)
  • Depositors only (login required):