Skip to Main content Skip to Navigation
Conference papers

Predictive Fault Tolerance in Multi-Agent Systems: a Plan-Based Replication Approach

Alessandro de Luna Almeida 1 Samir Aknine 1 Jean-Pierre Briot 1 Jacques Malenfant 2 
1 SMA - Systèmes Multi-Agents
LIP6 - Laboratoire d'Informatique de Paris 6
2 MoVe - Modélisation et Vérification
LIP6 - Laboratoire d'Informatique de Paris 6
Abstract : The fact that multiagent applications are prone to the same faults that any distributed system is susceptible to and the need for a higher quality of service in these systems justify the increasing interest in fault-tolerant multiagent systems. In this article, we propose an original method for providing dependability in multiagent systems through replication. Our method is different from other works because our research focuses on building an automatic, adaptive and predictive replication policy where critical agents are replicated to minimize the impact of failures. This policy is determined by taking into account the criticality of the plans of the agents, which contain the collective and individual behaviors of the agents in the application. The set of replication strategies applied at a given moment to an agent is then fine-tuned gradually by the replication system so as to reflect the dynamicity of the multiagent system. Some preliminary measurements were made to assess the efficiency of our approach and future directions are presented.
Document type :
Conference papers
Complete list of metadata

https://hal.archives-ouvertes.fr/hal-01335146
Contributor : Lip6 Publications Connect in order to contact the contributor
Submitted on : Tuesday, June 21, 2016 - 5:42:27 PM
Last modification on : Sunday, June 26, 2022 - 9:54:29 AM

Identifiers

Citation

Alessandro de Luna Almeida, Samir Aknine, Jean-Pierre Briot, Jacques Malenfant. Predictive Fault Tolerance in Multi-Agent Systems: a Plan-Based Replication Approach. International Conference on Autonomous Agents and Multiagent Systems (AAMAS'07) - Poster Session, May 2007, Honolulu, Hawai, United States. pp.672-673, ⟨10.1145/1329125.1329295⟩. ⟨hal-01335146⟩

Share

Metrics

Record views

147