# What are optimal policies?

## What are optimal policies?

An optimal policy, is a policy which is as good as or better than all the other policies. That is, an optimal policy will have the highest possible value in every state. There’s always at least one optimal policy, but there may be more than one.

### How do you find optimal policy?

Finding an Optimal policy : We find an optimal policy by maximizing over q*(s, a) i.e. our optimal state-action value function. We solve q*(s,a) and then we pick the action that gives us most optimal state-action value function(q*(s,a)).

What is optimal policy reinforcement learning?

Reinforcement learning is primarily concerned with how to obtain the optimal policy when such a model is not known in advance. The agent must interact with its environment directly to obtain information which, by means of an appropriate algorithm, can be processed to produce an optimal policy.

Does optimal policy always exist for MDP?

The results below assume finite state, action space and bounded rewards. Theorem 1 (Puterman [1994], Theorem 6.2. 7). For any infinite horizon discounted MDP, there always exists a deterministic stationary policy π that is optimal.

## Is optimal policy unique?

From the classical point of view, it is important to determine if in a Markov decision process (MDP), besides their existence, the uniqueness of the optimal policies is guaranteed. It is well known that uniqueness does not always hold in optimization problems (for instance, in linear programming).

### Is optimal policy unique in MDP?

For finite MDPs, the Bellman optimality equation (3.15) has a unique solution independent of the policy. The Bellman optimality equation is actually a system of equations, one for each state, so if there are states, then there are equations in unknowns.

Are optimal policies deterministic?

A deterministic policy is a function from states to actions. The optimal deterministic policy is the policy that maximizes the expected discounted sum of rewards ( ∑tγtrt) if the agent acts according to that policy.

Is the optimal policy deterministic?

It is proved that if the reward function is deterministic, the optimal policy exists and is also deterministic.

## What does optimal value mean?

(definition) Definition: The minimum (or maximum) value of the objective function over the feasible region of an optimization problem. See also optimal solution.

### Can there be more than one optimal policy?

There can be more than one optimal policy. T(s, a, s )V ∗(s )) . An optimal action for a state s ∈ S is an action a ∈ A such that Q(s, a) = V ∗(s). A strategy σ is optimal if and only if for all states s σ(s) is an optimal action.

What is optimal function?

the highest possible level of functioning, especially in relationships, work, education, and subjective well-being.

What is optimal point of a function?

It is a necessary condition for a differentiable function to have a maximum of minimum at a point in its domain. Stationary points can be local or global maxima or minima, or an inflection point. We can find the nature of stationary points by using the first derivative.

## Which is the best definition of optimal policy?

optimal policy. [′äp·tə·məl ′päl·ə·sē] (mathematics) In optimization problems of systems, a sequence of decisions changing the states of a system in such a manner that a given criterion function is minimized.

### Why does the optimal policy exist in MDP?

Why does the optimal policy exist? In a finite Markov Decision Process (MDP), the optimal policy is defined as a policy that maximizes the value of all states at the same time¹.

How to calculate the optimal policy for each state?

Time is added to each variable with a subscript. Then, given a policy and an MDP, and given the initial state (at time t=1) s, for any T > 1, the joint distribution of states, actions, and reward values is Given a policy π and a discount factor 0 ≤ γ < 1, the value of each state is defined as

How is an M-optimal cost policy determined?

The set of m-optimal or nearly optimal policies with α = 0+, are called guaranteed cost policies. These policies can be determined by fuzzy dynamic programming as shown in references [4] and [5]. Model-based optimisation was used for developing time-optimal policies for distillation columns.