Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Artificial intelligence: a modern approach
Artificial intelligence: a modern approach
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
An orthogonal genetic algorithm with quantization for globalnumerical optimization
IEEE Transactions on Evolutionary Computation
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In the standard GA, the individual has no intelligence and must act upon some rules established by a programmer in advance, such as various genetic operator. The result is to make the evolutionary process to be trapped into the local optimization of the objective function. In order to solve this problem, through studying the structure of an agent and selection operator, the paper designs a new genetic algorithm based on agent, called AGA (Agent-based Genetic Algorithm). At the premise of giving the definition of the outer environment where an agent lives and of an agent's belief, this paper gives some rules on how an agent selects one agent to cross their genes and some rules on how to solve competition. In addition, a communication method based on blackboard is presented to solve the communication among the agent society. Finally, the paper gives the structure of AGA and the simulation result for a multi-peak function, which demonstrates the validity of the AGA.