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AIMA-Java Core Algorithms from the book Artificial Intelligence a Modern Approach 3rd Ed.

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package aima.core.probability.mdp;

import aima.core.agent.Action;

/**
 * Artificial Intelligence A Modern Approach (3rd Edition): page 647.
*
* * A solution to a Markov decision process is called a policy. It * specifies what the agent should do for any state that the agent might reach. * It is traditional to denote a policy by π, and π(s) is the action * recommended by the policy π for state s. If the agent has a complete * policy, then no matter what the outcome of any action, the agent will always * know what to do next. * * @param * the state type. * @param * the action type. * * @author Ciaran O'Reilly * @author Ravi Mohan * */ public interface Policy { /** * π(s) is the action recommended by the policy π for state s. * * @param s * the state s * @return the action recommended by the policy π for state s. */ A action(S s); }




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