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Results tagged with q-learning
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user 30959
For questions related to the Q-learning algorithm, which is a model-free and temporal-difference reinforcement learning algorithm that attempts to approximate the Q function, which is a function that, given a state s and an action a, returns a real number that represents the return (or value) of state s when action a is taken from s. Q-learning was introduced in the PhD thesis "Learning from Delayed Rewards" (1989) by Watkins.
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2
answers
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How does one know that a problem is "model-free" in reinforcement learning?
Consider this slide from a Stanford lecture on reinforcement learning. It states that a model is
the agent's representation of how the world changes in response to the agent's action.
I've been expe …
- 187
1
vote
1
answer
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Can tabular Q-learning converge even if it doesn't explore all state-action pairs?
My understanding of tabular Q-learning is that it essentially builds a dictionary of state-action pairs, so as to maximize the Markovian (i.e., step-wise, history-agnostic?) reward. This incremental u …
- 187