Questions tagged [epsilon-greedy]

For questions about the $\epsilon$-greedy policy, which is typically used as a behavioural policy (i.e. a policy used to interact with the environment) during the interaction of reinforcement learning agents with the environment.

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Can we stop training as soon as epsilon is small?

I'm new to reinforcement learning. As it is common in RL, $\epsilon$-greedy search for the behavior/exploration is used. So, at the beginning of the training, $\epsilon$ is high, and therefore a lot ...
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23 views

Understanding GLIE conditions for epsilon greedy approach

I was going through this course on reignforcement learning (the course has two lecture videos and corresponding slides) and I had a doubt. On slide 18 of this pdf, it states following condition for an ...
4
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1answer
74 views

What does the term $|\mathcal{A}(s)|$ mean in the $\epsilon$-greedy policy?

I've been looking online for a while for a source that explains these computations but I can't find anywhere what does the $|A(s)|$ mean. I guess $A$ is the action set but I'm not sure about that ...
4
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1answer
121 views

What happens when you select actions using softmax instead of epsilon greedy in DQN?

I understand the two major branches of RL are Q-Learning and Policy Gradient methods. From my understanding (correct me if I'm wrong), policy gradient methods have an inherent exploration built-in as ...
0
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1answer
91 views

Why am I getting better performance with Thompson sampling than with UCB or $\epsilon$-greedy in a multi-armed bandit problem? [closed]

I ran a test using 3 strategies for multi-armed bandit: UCB, $\epsilon$-greedy, and Thompson sampling. The results for the rewards I got are as follows: Thompson sampling had the highest average ...