Package org.tweetyproject.machinelearning.rl.mdp.algorithms

Interface PolicyEvaluation<S extends State,A extends Action>

Type Parameters:

S - The type of states in the MDP.

A - The type of actions in the MDP.

All Known Implementing Classes:

IterativePolicyEvaluation

public interface PolicyEvaluation<S extends State,A extends Action>

The `PolicyEvaluation` interface provides methods to evaluate the utility of states in a Markov Decision Process (MDP) with respect to a given policy.

Author:

Matthias Thimm

Method Summary

Modifier and Type	Method	Description
Map<S,Double>	getUtilities(MarkovDecisionProcess<S,A> mdp, Policy<S,A> pi, double gamma)	Determines the utilities of the states in the MDP wrt.

Method Details

getUtilities

Map<S,Double> getUtilities(MarkovDecisionProcess<S,A> mdp,
 Policy<S,A> pi,
 double gamma)

Determines the utilities of the states in the MDP wrt. the given policy.

Parameters:

mdp - some MDP

pi - some policy

gamma - the discount factor

Returns:

the utilities of the states of the MDP.