Questions tagged [stochastic-policy]

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1answer
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Policy improvement in SARSA and Q learning

I have a rather trivial doubt in SARSA and Q learning. Looking at the pseudocode of the two algorithms in Sutton&Barto book, I see the policy improvement step is missing. How will I get the ...
1
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1answer
31 views

How do measure how different two policies are?

I have two agents that both follow a baseline behavioral policy pi(a|s). If I then modify the state-action distribution for the two agents (resulting in two new policies), is there a standard measure ...
1
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0answers
15 views

ε-Greedy with Q learning / SARSA can have stochastic policy?

Hello I'm now studying Q learning and SARSA with ε-Greedy , Softmax startegies. And have a question about my readings. In my readings, when SARSA with ε-Greedy, SARSA causes value-function ...
0
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0answers
79 views

What is difference between epsilon greedy and epsilon soft policies?

I found that epsilon soft policies are the policies which give a probability of e/|A(s)| for a non greedy action and a probability of 1-e for a greedy action. Heree sum of probablities is equals to ...
0
votes
1answer
63 views

Discrete and continuous actions in the same environment

I am working on a RL environment that requires both discrete and continuous actions as input from the agent. I currently have a fine implementation of DDPG which I would like to use for the continuous ...
1
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0answers
54 views

Why the Monte Carlo Control algorithm is written this way?

I am having trouble to understand this algorithm, since this is not how I would have written it. To me, we should first start to fix a policy. Then, we evaluate the Q values associated with this ...
3
votes
1answer
545 views

Proof that any $\epsilon-$greedy policy is an improvement over any $\epsilon-$soft policy

In the book by Richard Sutton and Andrew Barto, "Reinforcement Learning - An Introduction", 2ed edition, at page 101 there is a proof, and I don't understand 1 passage of it. We want to prove that ...
8
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2answers
8k views

Is a policy always deterministic in reinforcement learning?

In reinforcement learning, is a policy always deterministic, or is it a probability distribution over actions (from which we sample)? If the policy is deterministic, why is not the value function, ...