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Analyzing the Effects of Reinforcement Learning to Develop Humanoid Robots

机译:分析加固学习效果开发人形机器人的影响

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摘要

Reinforcement learning is a flourishing machine learning concept that has greatly influenced how robots are designed and taught to solve problems without human intervention. Robotics is not an alien discipline anymore, and we have several great innovations in this field that promise to impact lives for the better. However, humanoid robots are still a baffling concept for scientists, although we have managed to develop a few great inventions which look, talk, work, and behave very similarly to humans. But, can these machines actually exhibit the cognitive abilities of judgment, problem-solving, and perception as well as humans? In this article, the authors analyzed the probable impact and aspects of robots and their potential to behave like humans in every possible way through reinforcement learning techniques. The paper also discusses the gap between 'natural' and 'artificial' knowledge.
机译:强化学习是一种繁荣的机器学习概念,极大地影响了机器人的设计和教导来解决没有人为干预的问题。机器人不再是外星人纪律,我们在这一领域有几个伟大的创新,这承诺影响生活更好。然而,人形机器人仍然是科学家的困惑的概念,尽管我们已经设法制定了一些看起来,谈话,工作的伟大发明,并且与人类非常相似。但是,这些机器可以实际上表现出判断,问题解决和感知以及人类的认知能力吗?在本文中,作者分析了机器人的可能影响和方面,并通过加强学习技术以各种可能的方式表现出人类。本文还讨论了“自然”与“人为”知识之间的差距。

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