A complete list of books published in the Adaptive Computation and Machine Learning series appears at the back of this book. The cover design is based on the ...
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As we outlined in Chapter 1, the idea of TD learning has its early roots in animal learning psychology and artificial intelligence, most notably the work of ...
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How does reinforcement learning differ from other types of machine learning, such as supervised and unsupervised learning? What are some advantages and ...
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r/reinforcementlearning: Reinforcement learning is a subfield of AI/statistics focused on exploring/understanding complicated environments and…
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May 23, 2017 · In this paper, we present a learning algorithm that explicitly considers safety, defined in terms of stability guarantees. Specifically, we ...
Safe RL can be defined as the process of learning policies that maximize the expectation of the return in problems in which it is important to ensure reasonable ...
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Reinforcement Learning: An Introduction. Small book cover. Richard S. Sutton and Andrew G. Barto. Second Edition (see here for the first edition)
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Abstract:Reinforcement learning agents have demonstrated remarkable achievements in simulated environments. Data efficiency poses an ...
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