Chameleon: A Software Infrastructure for Adaptive Fault Tolerance
IEEE Transactions on Parallel and Distributed Systems
Improving fault-tolerance by replicating agents
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 2
AQuA: An Adaptive Architecture that Provides Dependable Distributed Objects
SRDS '98 Proceedings of the The 17th IEEE Symposium on Reliable Distributed Systems
DARX—A Framework For The Fault-Tolerant Support Of Agent Software
ISSRE '03 Proceedings of the 14th International Symposium on Software Reliability Engineering
Solving Distributed Constraint Optimization Problems Using Cooperative Mediation
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 1
Adopt: asynchronous distributed constraint optimization with quality guarantees
Artificial Intelligence - Special issue: Distributed constraint satisfaction
Experience and prospects for various control strategies for self-replicating multi-agent systems
Proceedings of the 2006 international workshop on Self-adaptation and self-managing systems
Proceedings of the 2006 international workshop on Software engineering for large-scale multi-agent systems
A Predictive Method for Providing Fault Tolerance in Multi-agent Systems
IAT '06 Proceedings of the IEEE/WIC/ACM international conference on Intelligent Agent Technology
Probabilistically survivable MASs
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Dynamic and adaptive replication for large-scale reliable multi-agent systems
Software engineering for large-scale multi-agent systems
Replication Based on Role Concept for Multi-Agent Systems
ESAW '09 Proceedings of the 10th International Workshop on Engineering Societies in the Agents World X
Hi-index | 0.00 |
In this article, we propose an original method for providing fault tolerance in multi-agent systems. Our method focuses on building an automatic and adaptive replication policy to solve the resource allocation problem of determining where agents must be replicated to minimize the impact of failures. This policy is determined by taking into account the criticality of the agents and the reliability of the machines. We propose then different heuristics for the allocation of the available resources. Some measurements assessing the effectiveness of our approach are also presented.