Questions tagged [stochastic-policy]

For questions related to the concept of a "stochastic policy" (as defined in reinforcement learning).

Filter by
Sorted by
Tagged with
3
votes
1answer
52 views

In the policy gradient equation, is $\pi(a_{t} | s_{t}, \theta)$ a distribution or a function?

I am learning about policy gradient methods from the Deep RL Bootcamp by Peter Abbeel and I am a bit stumbled by the math presented. In the lecture, he derives the gradient logarithm likelihood of a ...
3
votes
1answer
44 views

What's the value of making the RL agent's output stochastic opposed to deterministic?

I have a question about a reinforcement learning problem. I'm training an agent to add or delete pixels in a [12 x 12] 2D space (going to be 3D in the future). Its action space consists of two ...
1
vote
1answer
28 views

Value-based methods for stochastic policies

Is it possible for value-based methods to learn stochastic policies? I'm trying to get a clear picture of the different categories for RL algorithms, and while doing so I started to think about ...
1
vote
3answers
727 views

What is the difference between a stochastic and a deterministic policy?

In reinforcement learning, there are the concepts of stochastic (or probabilistic) and deterministic policies. What is the difference between them?
10
votes
3answers
1k views

Is the optimal policy always stochastic if the environment is also stochastic?

Is the optimal policy always stochastic (that is, a map from states to a probability distribution over actions) if the environment is also stochastic? Intuitively, if the environment is ...
3
votes
1answer
307 views

Can Q-learning be used to derive a stochastic policy?

In my understanding, Q-learning gives you a deterministic policy. However, can we use some technique to build a meaningful stochastic policy from the learned Q values? I think that simply using a ...