Reinforcement learning

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How to learn how to strengthen learning? It is enough to read this article.

Little is known about how the brain works, but we know that the brain can learn through repeated attempts. When we make the right choices, we get rewards and we are punished when we make inappropriate choices. This is how we adapt to the environment. Today, we can use powerful computing power to model this specific process in software, which is intensive learning.

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Supervised learning × reinforcement learning, Facebook lets chat robots learn to negotiate

Facebook's artificial intelligence research organization FAIR has just opened up and publicly published chat bots have begun to negotiate and negotiate with humans for bargaining power. Through supervised learning + reinforcement learning, this chat robot can not only understand the correspondence between words and semantics, but also formulate strategies for their own goals and reach consensus with others.

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The concept of the three brothers of machine learning: "supervised learning", "unsupervised learning", "reinforcement learning"

In this article, we will help you better understand the implications of the definitions of supervised learning, unsupervised learning, and reinforcement learning, and explain their connection to machine learning from a broader perspective. A deep understanding of their connotations will not only help you to be embarrassed in the literature in this field, but also guide you to sharply capture the development of AI and the advancement of technological progress.