Rule-Based System Against Reinforcement Learning*

Bozhan I. Orozov, D. Orozova
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Abstract

Reinforcement Learning is becoming an increasingly popular type of machine learning. In it, artificial intelligence learns what the best action in each given situation is and over time optimizes the decisions it makes. On the other hand, provided that sufficiently good rules are created, a Rule-Based System is a program task that can support very complex behavior. The aim of the authors in this study is to analyze and compare the behavior of two agents, realized on the basis of these two approaches.
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基于规则的系统对抗强化学习*
强化学习正在成为一种越来越受欢迎的机器学习类型。在其中,人工智能学习在每种给定情况下的最佳行动,并随着时间的推移优化其做出的决策。另一方面,只要创建了足够好的规则,基于规则的系统就是一个可以支持非常复杂行为的程序任务。作者在本研究中的目的是分析和比较基于这两种方法实现的两个代理的行为。
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