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首页> 外文会议>Asia-Pacific Conference on Simulated Evolution and Learning(SEAL'2002); 20021118-22; Singapore(SG) >EVOLUTION OF FUZZY RULE BASED CONTROLLERS FOR DYNAMIC ENVIRONMENTS
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EVOLUTION OF FUZZY RULE BASED CONTROLLERS FOR DYNAMIC ENVIRONMENTS

机译：动态环境的模糊规则控制器的演变

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Fuzzy logic controllers have been applied to a wide range of control problems, but are very difficult to build for situations where the environment changes quickly and there is a lot of uncertainty. This work investigates a new method of creating fuzzy controllers, in the form of reactive agents, for such environments. The framework for this investigation is the RoboCup soccer simulation environment, where the agents are in the form of simulated soccer players evolved to exhibit competent dribble-and-score behaviours. The method proposed uses a messy genetic algorithm to evolve a set of behaviour producing fuzzy rules which define the agents. The results presented indicate that the messy genetic algorithm is well suited to this task, producing good performance by reducing complexity, and that the agents produced perform well in their environment. The best agent evolved is consistently and reliably able to locate the ball, dribble it to the goal and score.
机译：模糊逻辑控制器已被应用到各种各样的控制问题中，但是对于环境快速变化且存在很多不确定性的情况而言，构建模糊逻辑控制器非常困难。这项工作研究了一种针对此类环境创建反应控制器形式的模糊控制器的新方法。该调查的框架是RoboCup足球模拟环境，其中代理以模拟足球运动员的形式发展，以表现出能干的运球得分能力。所提出的方法使用杂乱的遗传算法来演化一组行为，从而产生定义代理的模糊规则。给出的结果表明，杂乱的遗传算法非常适合此任务，可通过降低复杂性来产生良好的性能，并且所产生的代理在其环境中表现良好。进化出的最佳特工始终如一地可靠地定位球，将球运到球门并得分。

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