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June 23, 2022, 5:14 p.m. | /u/Embarrassed-Fee5513

Reinforcement Learning reddit.com

Reinforcement learning (RL) requires exploration of the environment. Exploration is even more critical when extrinsic incentives are few or difficult to obtain. Due to the massive size of the environment, it is impractical to visit every location in rich settings due to the range of helpful exploration paths. Consequently, the question is: how can an agent decide which areas of the environment are worth exploring? Curiosity-driven exploration is a viable approach to tackle this problem. It entails learning a world …

algorithm deepmind exploration learning observable power reinforcementlearning researchers self-supervised learning supervised learning

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