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The Brown-UMBC Reinforcement Learning and Planning (BURLAP) Java code library is for the use and development of single or multi-agent planning and learning algorithms and domains to accompany them. The library uses a highly flexible state/observation representation where you define states with your own Java classes, enabling support for domains that discrete, continuous, relational, or anything else. Planning and learning algorithms range from classic forward search planning to value-function-based stochastic planning and learning algorithms.

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package burlap.mdp.singleagent.common;

import burlap.mdp.core.action.Action;
import burlap.mdp.core.oo.propositional.PropositionalFunction;
import burlap.mdp.core.oo.state.OOState;
import burlap.mdp.core.state.State;
import burlap.mdp.singleagent.model.RewardFunction;


/**
 * This class defines a reward function that returns a goal reward when any grounded form of a propositional
 * function is true in the resulting state and a default non-goal reward otherwise.
 * @author James MacGlashan
 *
 */
public class SingleGoalPFRF implements RewardFunction {

	PropositionalFunction			pf;
	double							goalReward;
	double							nonGoalReward;
	
	
	
	/**
	 * Initializes the reward function to return 1 when any grounded from of pf is true in the resulting
	 * state.
	 * @param pf the propositional function that must have a true grounded version for the goal reward to be returned.
	 */
	public SingleGoalPFRF(PropositionalFunction pf){
		this.pf = pf;
		this.goalReward = 1.;
		this.nonGoalReward = 0.;
	}
	
	
	/**
	 * Initializes the reward function to return the specified goal reward when any grounded from of pf is true in the resulting
	 * state and the specified non-goal reward otherwise.
	 * @param pf the propositional function that must have a true grounded version for the goal reward to be returned.
	 * @param goalReward the goal reward value to be returned
	 * @param nonGoalReward the non goal reward value to be returned.
	 */
	public SingleGoalPFRF(PropositionalFunction pf, double goalReward, double nonGoalReward){
		this.pf = pf;
		this.goalReward = goalReward;
		this.nonGoalReward = nonGoalReward;
	}
	
	
	@Override
	public double reward(State s, Action a, State sprime) {
		
		if(this.pf.someGroundingIsTrue((OOState)sprime)){
			return goalReward;
		}
		return nonGoalReward;
		
		
	}

}