People who code: we want your input. Take the Survey

# Questions tagged [stochastic-policy]

For questions related to the concept of a stochastic policy (as defined in reinforcement learning), which is a function from a state to a probability distribution over actions (from that state).

10 questions
Filter by
Sorted by
Tagged with
1answer
39 views

I am reading Sutton & Bartos's Book "Introduction to reinforcement learning". In this book, the defined the optimal value function as: $$v_*(s) = \max_{\pi} v_\pi(s),$$ for all $s \in \... 1answer 44 views ### Is a learned policy, for a deterministic problem, trained in a supervised process, a stochastic policy? If I trained a neural network with 4 outputs (one for each action: move down, up, left, and right) to move an agent through a grid (deterministic problem). The output of the neural network is a ... 1answer 266 views ### Did Alphago zero actually beat Alphago 100 games to 0? tl;dr Did AlphaGo and AlphaGo play 100 repetitions of the same sequence of boards, or were there 100 different games? Background: Alphago was the first superhuman go player, but it had human tuning ... 1answer 287 views ### Why is tic-tac-toe considered a non-deterministic environment? I have been reading about deterministic and stochastic environments, when I came up with an article that states that tic-tac-toe is a non-deterministic environment. But why is that? An action will ... 1answer 59 views ### In the policy gradient equation, is$\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 ...
1answer
64 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 ...
1answer
109 views

### Is it possible for value-based methods to learn 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 ...
3answers
4k 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?
3answers
2k 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 ...
1answer
638 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 ...