# Questions tagged [policy]

For questions related to policies (as defined in reinforcement learning or other AI sub-fields).

8 questions with no upvoted or accepted answers
Filter by
Sorted by
Tagged with
31 views

### Representation of state space, action space and reward system for Reinforcement Learning problem

I am trying to solve the problem of an agent dynamically discovering(start with no information about the environment) the environment and to explore as much of the environment as possible without ...
29 views

### Can the importance sampling estimator have a non-stationary behaviour policy even if the target policy is stationary?

The inverse propensity score (IPS) estimator, which is used for off-policy evaluation in a contextual bandit problem, is well explained in the paper Doubly Robust Policy Evaluation and Optimization. ...
44 views

### AlphaGo Zero: Does the policy head give a probability for every possible move?

If I understood correctly, the AlphaGo Zero network returns two values: a vector of logit probabilities p and a value v. My question is: in this vector that it is outputted, do we have a probability ...
38 views

### Finding optimal Value function and Policy for an MDP

I am solving an RL MDP problem which is model based. I have an MDP which has four possible states S1-S4 and four different actions A1-A4, with S4 being terminal state and S1 is the beginning state. ...
30 views

### Measure grid-world environments difference for reinforcement learning

I'd like to measure the difference between 2 grid-worlds to determine the generalization capacity of my agent using tabular Q-learning. Example (OpenAI Frozen Lake) : SFFF FHFH FFFH HFFG and : ...
33 views

### Where does the expectation term in the derivative of the soft-max policy come from?

At slide 17 of the David Silver's series, the soft-max policy is defined as follows $$\pi_\theta(s, a) \propto e^{\phi(s, a)^T \theta}$$ that is, the probability of an action $a$ (in state $s$) is ...