# Questions tagged [stochastic-policy]

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An agent receives an extrinsic reward $r_{ext}$ and an intrinsic reward $r_{int}$ and a Q-function approximation is trained using TD learning such that $Q(s,a)$ approximates the expected return of $r_{... 0 votes 0 answers 29 views ### How to prove that stochastic policy iteration converges? I was reading Sutton's book Reinforcement Learning: An Introduction, especially policy iteration part. There was a proof for convergence of policy iteration with deterministic policy. So i tried to ... 0 votes 1 answer 98 views ### Are the two$\epsilon$-greedy policies different? I found 2 diffefent versions of$\epsilon$Greedy policy for monte carlo and q learning: For monte carlo:$\pi (a|s)=\epsilon /m +1-\epsilon$to choose the best action and$\pi =\epsilon /m$for other ... • 1 2 votes 1 answer 343 views ### Policy improvement in SARSA and Q learning I have a rather trivial doubt in SARSA and Q learning. Looking at the pseudocode of the two algorithms in Sutton&Barto book, I see the policy improvement step is missing. How will I get the ... • 391 1 vote 1 answer 74 views ### How do measure how different two policies are? I have two agents that both follow a baseline behavioral policy pi(a|s). If I then modify the state-action distribution for the two agents (resulting in two new policies), is there a standard measure ... • 111 1 vote 0 answers 31 views ### ε-Greedy with Q learning / SARSA can have stochastic policy? Hello I'm now studying Q learning and SARSA with ε-Greedy , Softmax startegies. And have a question about my readings. In my readings, when SARSA with ε-Greedy, SARSA causes value-function ... • 11 1 vote 1 answer 219 views ### Discrete and continuous actions in the same environment I am working on a RL environment that requires both discrete and continuous actions as input from the agent. I currently have a fine implementation of DDPG which I would like to use for the continuous ... • 11 1 vote 0 answers 131 views ### Why the Monte Carlo Control algorithm is written this way? I am having trouble to understand this algorithm, since this is not how I would have written it. To me, we should first start to fix a policy. Then, we evaluate the Q values associated with this ... 3 votes 1 answer 843 views ### Proof that any$\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 ...
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