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Results tagged with reinforcement-learning
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user 83973
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.
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Can a trained RL network outperforms the best training sample?
I'm working on solving a problem where I need to determine the optimal set of actions to find the path that yields the maximum reward. I'm currently using a Deep Q-Network (DQN) for this task. However …
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