# Questions tagged [deterministic-policy]

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

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### 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 ...
640 views

### What is the loss for policy gradients with continuous actions?

I know with policy gradients used in an environment with a discrete action space are updated with $$\Delta \theta_{t}=\alpha \nabla_{\theta} \log \pi_{\theta}\left(a_{t} \mid s_{t}\right) v_{t}$$ ...
6k 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?
418 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 ...
783 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 ...
48 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 ...
277 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 ...
193 views

### What is the motivation behind using a deterministic policy?

What is the motivation behind using a deterministic policy? Given that the environment is uncertain, it seems stochastic policy makes more sense.
Let M be an MDP with two states, A, B, A is the starting state and you always transit to the final state B using two possible actions. $A1$ gives you rewards which are normally distributed N(0, 1) and ...