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

Interface PolicyEvaluation<S extends State,A extends Action>

Type Parameters:
S - The type of states
A - The type of actions
All Known Implementing Classes:
IterativePolicyEvaluation
public interface PolicyEvaluation<S extends State,A extends Action>
Author:
Matthias Thimm

  • 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.