Task differentiation in Polistes wasp colonies: a model for self-organizing groups of robots
Proceedings of the first international conference on simulation of adaptive behavior on From animals to animats
Ant-like agents for load balancing in telecommunications networks
AGENTS '97 Proceedings of the first international conference on Autonomous agents
The ant colony optimization meta-heuristic
New ideas in optimization
Resource Allocation in Distributed Factory Scheduling
IEEE Expert: Intelligent Systems and Their Applications
Adaptive Task Allocation Inspired by a Model of Division of Labor in Social Insects
Biocomputing and emergent computation: Proceedings of BCEC97
Coordination of multiple agents in distributed manufacturing scheduling
Coordination of multiple agents in distributed manufacturing scheduling
Wasp-like Agents for Distributed Factory Coordination
Autonomous Agents and Multi-Agent Systems
An integrated token-based algorithm for scalable coordination
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Multi-agent system model for optimization the monitoring process within a Natura 2000 site
MCBC'08 Proceedings of the 9th WSEAS International Conference on Mathematics & Computers In Biology & Chemistry
Models for a multi-agent system based on wasp-like behaviour for distributed patients repartition
EC'08 Proceedings of the 9th WSEAS International Conference on Evolutionary Computing
A Token-Based Mutual Exclusion Approach to Improve Collaboration in Distributed Environments
ICCCI '09 Proceedings of the 1st International Conference on Computational Collective Intelligence. Semantic Web, Social Networks and Multiagent Systems
Self-organized task allocation for computing systems with reconfigurable components
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
Wasp-like agents for scheduling production in real-time strategy games
EPIA'11 Proceedings of the 15th Portugese conference on Progress in artificial intelligence
Adaptable swarm intelligence framework
Proceedings of the 2nd International Conference on Web Intelligence, Mining and Semantics
Bio-inspired multi-agent systems for reconfigurable manufacturing systems
Engineering Applications of Artificial Intelligence
Hi-index | 0.00 |
Agent-based approaches to manufacturing scheduling and control have gained increasing attention in recent years. Such approaches are attractive because they offer increased robustness against the unpredictability of factory operations. But the specification of local coordination policies that give rise to efficient global performance and effectively adapt to changing circumstances remains an interesting challenge. In this paper, we introduce a new approach to this coordination problem, drawing on various aspects of a computational model of how wasp colonies coordinate individual activities and allocate tasks to meet the collective needs of the nest. We focus specifically on the problem of configuring machines in a factory to best satisfy (potentially changing) product demands over time. Our system models the set of jobs queued in front of any given machine as a wasp nest, wherein wasp-like agents interact to form a social hierarchy and prioritize the jobs that they represent. Other wasp-like agents external to the nest act as overall machine proxies, and use a model of wasp task allocation behavior to determine which new jobs should be accepted into the machine's queue. We show for simple factories that our multi-agent system achieves the desired effect. For a given job mix, the system converges to a factory configuration that maximizes overall performance, and as the job mix changes, the system quickly adapts to a new, more appropriate configuration.