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Learning Symbolic Rules with a Reactive with Tages Classifier System in Robot Navigation

机译:使用Tages分类器系统中的反应学习符号规则,在机器人导航中

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Classifier System are special production systems where conditions and actions are codified in order to learn new rules by means of Genetic Algorithms (GA). These systems combine the execution capabilities of symbolic systems and the learning capabilities of Genetic Algorithms. the Reactive with Tags Classifier System (RTCS) is able to learn symbolic rules that allow to generate sequence of actions, chaining rules among diferent time instants, and react to new environmental situations, considering the last environmental situation to take a decision. The capacity of RTCS to learn good rules has been prove in robotics navigation problem. results show the suitablity of this aproximation to the navigation problem and the coherence of extracted rules.
机译:分类系统是特殊生产系统,其中条件和行动是通过遗传算法(GA)学习新规则的条件和行动。这些系统结合了符号系统的执行能力和遗传算法的学习能力。具有标签分类器系统(RTC)的反应性能够学习符号规则,允许生成动作的序列,不同时间瞬间中的规则,以及对新的环境情况作出反应,考虑到最后的环境情况来做出决定。 RTC学习良好规则的能力已在机器人导航问题中证明。结果表明,该特征到导航问题的合适和提取规则的连贯性。

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