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Results tagged with reinforcement-learning
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user 53149
For questions related to reinforcement learning, i.e. a machine learning technique where we imagine an agent that interacts with an environment (composed of states) in time steps by taking actions and receiving rewards (or reinforcements), then, based on these interactions, the agent tries to find a policy (i.e. a behavioural strategy) that maximizes the cumulative reward (in the long run), so the goal of the agent is to maximize the reward.
3
votes
How should I model all available actions of a chess game in deep Q-learning?
The accepted answer severely overcounts the actual action space because of the assumption that any piece can move a maximum of 7 squares in any direction from any square on the board. The calculation …
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