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تسجيل مستخدم جديدOptimistic Simulated Exploration as an Incentive for Real Exploration
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Ivo Danihelka
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Many reinforcement learning exploration techniques are overly optimistic and try to explore every state. Such exploration is impossible in environments with the unlimited number of states. I propose to use simulated exploration with an optimistic model to discover promising paths for real exploration. This reduces the needs for the real exploration.
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