com.github.chen0040.rl.learning.rlearn.RAgent Maven / Gradle / Ivy

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package com.github.chen0040.rl.learning.rlearn;

import com.github.chen0040.rl.utils.IndexValue;

import java.io.Serializable;
import java.util.Random;
import java.util.Set;


/**
 * Created by xschen on 9/27/2015 0027.
 */
public class RAgent implements Serializable{
    private RLearner learner;
    private int currentState;
    private int currentAction;
    private double currentValue;

    public int getCurrentState(){
        return currentState;
    }

    public int getCurrentAction(){
        return currentAction;
    }

    public void start(int currentState){
        this.currentState = currentState;
    }

    public RAgent makeCopy(){
        RAgent clone = new RAgent();
        clone.copy(this);
        return clone;
    }

    public void copy(RAgent rhs){
        currentState = rhs.currentState;
        currentAction = rhs.currentAction;
        learner.copy(rhs.learner);
    }

    @Override
    public boolean equals(Object obj){
        if(obj != null && obj instanceof RAgent){
            RAgent rhs = (RAgent)obj;
            if(!learner.equals(rhs.learner)) return false;
            if(currentAction != rhs.currentAction) return false;
            return currentState == rhs.currentState;
        }
        return false;
    }

    public IndexValue selectAction(){
        return selectAction(null);
    }

    public IndexValue selectAction(Set actionsAtState){

        if(currentAction==-1){
            IndexValue iv = learner.selectAction(currentState, actionsAtState);
            currentAction = iv.getIndex();
            currentValue = iv.getValue();
        }
        return new IndexValue(currentAction, currentValue);
    }

    public void update(int newState, double immediateReward){
        update(newState, null, immediateReward);
    }

    public void update(int newState, Set actionsAtState, double immediateReward){
        if(currentAction != -1) {
            learner.update(currentState, currentAction, newState, actionsAtState, immediateReward);
            currentState = newState;
            currentAction = -1;
        }
    }

    public RAgent(){

    }



    public RLearner getLearner(){
        return learner;
    }

    public void setLearner(RLearner learner){
        this.learner = learner;
    }

    public RAgent(int stateCount, int actionCount, double alpha, double beta, double rho, double initialQ){
        learner = new RLearner(stateCount, actionCount, alpha, beta, rho, initialQ);
    }

    public RAgent(int stateCount, int actionCount){
        learner = new RLearner(stateCount, actionCount);
    }
}