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Results tagged with reinforcement-learning
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user 27777
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.
2
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0
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What are some approaches to estimate the transition and observation probabilities in POMDP?
What are some common approaches to estimate the transition or observation probabilities, when the probabilities are not exactly known?
When realizing a POMDP model, the state model needs additional …
- 445
1
vote
1
answer
293
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How to estimate the error during training in deep reinforcement learning
How do I calculate the error during the training phase for deep reinforcement learning models?
Deep reinforcement learning is not supervised learning as far as I know. So how can the model know wheth …
- 445
3
votes
1
answer
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What does the Markov assumption say about the history of state sequences?
Does the Markov assumption say that the conditional probability of the next state only depends on the current state or does it say that the conditional probability depends on a fixed finite number of …
- 445