Autonomous agents and multi-agent systems: explorations in learning, self-organization and adaptive computation
Multi-agent oriented constraint satisfaction
Artificial Intelligence
Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence
Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence
An evolutionary autonomous agents approach to image featureextraction
IEEE Transactions on Evolutionary Computation
A multiagent genetic algorithm for global numerical optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Multiagent Evolutionary Algorithm for T-coloring Problem
SEAL '08 Proceedings of the 7th International Conference on Simulated Evolution and Learning
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With the intrinsic properties of job-shop scheduling problems (JSPs) in mind, we integrate the multiagent systems and evolutionary algorithms to form a new algorithm, Multiagent Evolutionary Algorithm for JSPs (MAEA-JSPs). In MAEA-JSPs, all agents live in a latticelike environment. Making use of the designed behaviors, MAEA-JSPs realizes the ability of agents to sense and act on the environment in which they live. During the process of interacting with the environment and the other agents, each agent increases energy as much as possible, so that MAEA-JSPs can find the optima. In the experiments, 59 benchmark JSPs are used, and good performance is obtained.