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Communication Dans Un Congrès Année : 2019

Installing Resilience in Distributed Constraint Optimization Operated by Physical Multi-Agent Systems

Résumé

We study the notion of k-resilient distribution of graph-structured computations supporting agent decisions, over dynamic and physical multi-agent systems. We devise a replication-based self-organizing distributed repair method, namely DRPM[MGM-2], to repair the distribution as to ensure the system still performs collective decisions and remains resilient to upcoming changes. We focus on a particular type of distributed reasoning process to repair, where computations are decision variables and constraints distributed over a set of agents. We experimentally evaluate the performances of our repair method on different topologies of multi-agent systems (uniform or problem-dependent) operating stateless DCOP algorithms (Max-Sum and A-DSA) to solve classical DCOP benchmarks (random graph, graph coloring, Ising model) while agents are disappearing.
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Dates et versions

hal-02013923 , version 1 (11-02-2019)

Identifiants

  • HAL Id : hal-02013923 , version 1

Citer

Pierre Rust, Gauthier Picard, Fano Ramparany. Installing Resilience in Distributed Constraint Optimization Operated by Physical Multi-Agent Systems. Autonomous Agents and Multiagent Systems (AAMAS) 2019, May 2019, Montréal, Canada. pp.2177-2179. ⟨hal-02013923⟩
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