Title: Cooperative agents-based decentralised and scalable approach for complex task allocation pro massive multi-agent system

Authors: Zaki Brahmi, Mohamed Mohsen Gammoudi

Addresses: RIADI Research Laboratory, Business School of Tunis, Manouba University, 2010 Manouba, Tunisia. ' RIADI Research Laboratory, Higher School of Statistics and Information Analysis, University of November at Carthage, 6 Rue des metiers – Charguia II, BP 675 – 1080 Tunis, Tunisia

Abstract: A major challenge in the field of multi-agent systems is to enable autonomous agents to allocate tasks efficiently. In the context of massive multi-agents system (MMAS) which is characterised by a large number of dynamic and heterogeneous agents, traditional tasks allocations approaches based on the negotiation between agents, or a single allocator agent, proved impracticality. In this paper, we propose a decentralised and scalable approach for complex task allocation pro cooperative MMAS. Our approach is based on the idea of grouping agents according to their capacities to execute sub-tasks. Thus, the approach is based on two steps: 1) hierarchical organisation of agent groups using Galois sub-hierarchy, imminent from the formal concepts analysis approach (FCA); 2) computing the optimal allocation. These two steps are fully distributed among agents with the minimum of communication and a grant of finding the optimal allocation in a polynomial time. Further, this paper extends our last approach by distributing the global allocation process among all agents. It provides a solution based on cooperation among agents. This solution prohibits generation of conflicts. It is based on the idea that each agent has to pick out its own sub-task.

Keywords: task allocation; massive multi-agent systems; MMAS; formal concepts analysis; FCA; organisation; agent-based systems; cooperative agents; sub-tasks.

DOI: 10.1504/IJIIDS.2011.042530

International Journal of Intelligent Information and Database Systems, 2011 Vol.5 No.5, pp.431 - 451

Published online: 21 Oct 2014 *

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