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Results tagged with reinforcement-learning
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user 52027
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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In Policy Gradient methods, why are actions always chosen from a Gaussian in the literature?
In Sutton's 2020 Reinforcement Learning text (in chapter 13.7 Policy Parameterization for Continuous Actions) it's stated
actions [may be] chosen from a normal (Gaussian) distribution.
However, I ca …
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