Exploring RL projects

RL is a programming paradigm that processes algorithms that are capable of learning and adapting to changes in the environment. At the base of this programming technique, there is the interaction with the environment, where the agent receives stimuli from the outside according to the choices of the algorithm. A correct choice will provide a reward, while an incorrect choice will provide a penalty. The best possible result is achieved by maximizing the rewards that are obtained by the system. For example, the computer learns to beat an opponent in a game by performing a certain task, with the goal of maximizing the reward. This means that the system learns from the mistakes it made previously, improving on performance ...

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