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978-3-642-32039-2Springer-Verlag Berlin Heidelberg 2013嫌恶 发表于 2025-3-23 22:50:29
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irst start with the basic definitions and concepts of reinforcement learning, including the agent, environment, action, and state, as well as the reward function. Then, we describe a classical reinforcement learning problem, the bandit problem, to provide the readers with a basic understanding of th连词 发表于 2025-3-24 07:57:54
Norbert Donner-Banzhoff,Stefan Bösnerex decision-making tasks that were previously out of reach for a machine, and famously contributed to the success of AlphaGo. Furthermore, it opens up numerous new applications in domains such as healthcare, robotics, smart grids and finance. .Divided into three main parts, this book provides a compCrater 发表于 2025-3-24 13:02:45
Norbert Donner-Banzhoff,Stefan Bösnerirst start with the basic definitions and concepts of reinforcement learning, including the agent, environment, action, and state, as well as the reward function. Then, we describe a classical reinforcement learning problem, the bandit problem, to provide the readers with a basic understanding of th新鲜 发表于 2025-3-24 17:39:52
Norbert Donner-Banzhoff,Stefan Bösnerg, to state-of-the-art multi-agent and meta learning..RevealDeep reinforcement learning has attracted considerable attention recently. Impressive results have been achieved in such diverse fields as autonomous driving, game playing, molecular recombination, and robotics. In all these fields, computecumber 发表于 2025-3-24 20:30:56
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Norbert Donner-Banzhoff,Stefan Bösnerve significant impacts on mobile social networks (MSNs). MSNs can leverage these new paradigms to provide a new mechanism for users to share resources (e.g., information, computation-based services). In this chapter, we exploit the intrinsic nature of social networks, i.e., the trust formed through