Archibald, B. , Calder, M. , Sevegnani, M. and Xu, M. (2022) Verifying BDI Agents in Dynamic Environments. In: 34th International Conference on Software Engineering & Knowledge Engineering, Pittsburgh, USA, 01-10 Jul 2022, ISBN 1891706543 (doi: 10.18293/SEKE2022-149)
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Publisher's URL: https://doi.org/10.18293/SEKE2022-149
Abstract
The Belief-Desire-Intention (BDI) architecture is a popular framework for rational agents, yet most verification approaches are limited to analysing the behaviours of an agent in a subset of all possible environments. However, in practice, BDI agents operate in dynamic environments where the exact occurrence of external changes is difficult to predict. For safety/security we need to assess whether the agent behaves as required in all circumstances. To address this, we define environments, accounting for both sensor information about physical changes and new tasks to be completed, as a non-deterministic finite-state automata. We give an environment-enabled extension to the Conceptual Agent Notation (CAN) language including an executable semantics via an encoding to Milner’s bigraphs and the BigraphER tool. We illustrate the framework through a simple Unmanned Aerial Vehicle (UAV) example that is verified using mainstream tools including PRISM model checker. Results show our approach can automatically identify agent design flaws to aid agent programmers in design, debugging, and analysis.
| Item Type: | Conference Proceedings |
|---|---|
| Additional Information: | This work is supported by the EPSRC, under PETRAS SRF grant MAGIC (EP/S035362/1) and S4: Science of Sensor Systems Software (EP/N007565/1). |
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Calder, Professor Muffy and Xu, Dr Mengwei and Sevegnani, Dr Michele and Archibald, Dr Blair |
| Authors: | Archibald, B., Calder, M., Sevegnani, M., and Xu, M. |
| College/School: | College of Science and Engineering > School of Computing Science |
| ISSN: | 2325-9000 |
| ISBN: | 1891706543 |
| Copyright Holders: | Copyright © 2022 KSI Research Inc. and Knowledge Systems Institute Graduate School |
| First Published: | Proceedings of the 34th International Conference on Software Engineering and Knowledge Engineering (SEKE22) |
| Publisher Policy: | Reproduced in accordance with the copyright policy of the publisher |
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