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Clemens Heitzinger (Technische Universität Wien)
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Reinforcement learning is an appealing subject. Firstly, it is a very general concept: an agent interacts with an environment with the goal to maximize
the rewards it receives from the environment. The environment is random and provides states and rewards to the agent, while the agent chooses actions according to a possibly random policy. The goal is to find policies that maximise the expected value of all future rewards. Because reinforcement learning is such a general concept, it encompasses many real-world applications of machine learning and artificial intelligence
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