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A Genetic Programming-based Framework for Semi-automated Multi-agent Systems Engineering

Published:28 May 2023Publication History
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Abstract

With the rise of new technologies, such as Edge computing, Internet of Things, Smart Cities, and Smart Grids, there is a growing need for multi-agent systems (MAS) approaches. Designing multi-agent systems is challenging, and doing this in an automated way is even more so. To address this, we propose a new framework, Evolved Gossip Contracts (EGC). It builds on Gossip Contracts (GC), a decentralised cooperation protocol that is used as the communication mechanism to facilitate self-organisation in a cooperative MAS. GC has several methods that are implemented uniquely, depending on the goal the MAS aims to achieve. The EGC framework uses evolutionary computing to search for the best implementation of these methods. To evaluate EGC, it was used to solve a classical NP-hard optimisation problem, the Bin Packing Problem (BPP). The experimental results show that EGC successfully discovered a decentralised strategy to solve the BPP, which is better than two classical heuristics on test cases similar to those on which it was trained; the improvement is statistically significant. EGC is the first framework that leverages evolutionary computing to semi-automate the discovery of a communication protocol for a MAS that has been shown to be effective at solving an NP-hard problem.

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  1. A Genetic Programming-based Framework for Semi-automated Multi-agent Systems Engineering

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          cover image ACM Transactions on Autonomous and Adaptive Systems
          ACM Transactions on Autonomous and Adaptive Systems  Volume 18, Issue 2
          June 2023
          139 pages
          ISSN:1556-4665
          EISSN:1556-4703
          DOI:10.1145/3599693
          Issue’s Table of Contents

          Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s).

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          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 28 May 2023
          • Online AM: 2 March 2023
          • Accepted: 13 February 2023
          • Revised: 12 February 2023
          • Received: 6 March 2021
          Published in taas Volume 18, Issue 2

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