Verifying Heterogeneous Multi-Agent Programs

Trang Doan, Yuan Yao, Natasha Alechina, Brian Logan

Research output: Chapter in Book/Report/Conference proceedingConference proceeding

8 Citations (Scopus)

Abstract

We present a new approach to verifying heterogeneous multi-agent programs — multi-agent systems in which the agents are implemented in different (BDI-based) agent programming languages. Our approach is based on meta-APL, a BDI-based agent programming language that allows both an agent’s plans and its deliberation strategy to be encoded as part of the agent program. The agent programs comprising a heterogeneous multi-agent program are first translated into meta-APL, and the resulting system is then verified using the Maude term rewriting system. We prove correctness of translations of Jason and 3APL programs and deliberation strategies into meta-APL. Preliminary experimental results indicate that our approach can significantly out-perform previous approaches to
verification of heterogeneous multi-agent programs.
Original languageEnglish
Title of host publicationThe 13th International Conference on Autonomous Agents and Multiagent Systems
Subtitle of host publicationAAMAS 2014
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems, 2014
Pages149-156
Number of pages8
ISBN (Electronic)978-1-4503-2738-1
Publication statusPublished - 2014
Externally publishedYes
EventInternational Conference on Autonomous Agents & Multiagent Systems - Paris, France
Duration: 5 May 20149 May 2014

Conference

ConferenceInternational Conference on Autonomous Agents & Multiagent Systems
Abbreviated titleAAMAS '14
CountryFrance
CityParis
Period5/05/149/05/14

Keywords

  • Agent programming languages
  • Agent programs
  • Verification

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  • Cite this

    Doan, T., Yao, Y., Alechina, N., & Logan, B. (2014). Verifying Heterogeneous Multi-Agent Programs. In The 13th International Conference on Autonomous Agents and Multiagent Systems : AAMAS 2014 (pp. 149-156). International Foundation for Autonomous Agents and Multiagent Systems, 2014.