From 8f92ae65d8aae6fa3e08c82a6dfd832136a0b6e6 Mon Sep 17 00:00:00 2001
From: Woody Folsom <Woody.Folsom@gatech.edu>
Date: Mon, 30 Apr 2012 17:37:37 -0400
Subject: [PATCH] Fixed unit tests, changed MDP generation to more reasonably
 seek the goal state, avoiding premature end of game. Removed unused
 google-code classes. Regenerate policy when AdaptiveComPlayer.setTarget() is
 called.

---
 src/aima/core/environment/cellworld/Cell.java |  87 -----------
 .../core/environment/cellworld/CellWorld.java | 123 ---------------
 .../cellworld/CellWorldAction.java            | 142 ------------------
 .../cellworld/CellWorldFactory.java           |  27 ----
 .../gridworld/GridWorldFactory.java           |   7 +-
 .../core/probability/example/MDPFactory.java  | 133 +---------------
 src/model/comPlayer/AdaptiveComPlayer.java    |   1 +
 src/model/mdp/Action.java                     |  18 ---
 src/model/mdp/MDP.java                        |  51 -------
 src/model/mdp/MDPSolver.java                  |   5 -
 src/model/mdp/Policy.java                     |   7 -
 src/model/mdp/Transition.java                 |  34 -----
 src/model/mdp/ValueIterationSolver.java       | 110 --------------
 test/PlayerModel.dat                          | Bin 0 -> 419207 bytes
 .../mdp/MarkovDecisionProcessTest.java        |  74 +++------
 .../probability/mdp/PolicyIterationTest.java  |  45 ++----
 .../probability/mdp/ValueIterationTest.java   |  64 --------
 .../probability/mdp/ValueIterationTest2.java  |  38 ++---
 test/model/mdp/ValueIterationSolverTest.java  |  26 ----
 19 files changed, 53 insertions(+), 939 deletions(-)
 delete mode 100644 src/aima/core/environment/cellworld/Cell.java
 delete mode 100644 src/aima/core/environment/cellworld/CellWorld.java
 delete mode 100644 src/aima/core/environment/cellworld/CellWorldAction.java
 delete mode 100644 src/aima/core/environment/cellworld/CellWorldFactory.java
 delete mode 100644 src/model/mdp/Action.java
 delete mode 100644 src/model/mdp/MDP.java
 delete mode 100644 src/model/mdp/MDPSolver.java
 delete mode 100644 src/model/mdp/Policy.java
 delete mode 100644 src/model/mdp/Transition.java
 delete mode 100644 src/model/mdp/ValueIterationSolver.java
 create mode 100644 test/PlayerModel.dat
 delete mode 100644 test/aima/core/probability/mdp/ValueIterationTest.java
 delete mode 100644 test/model/mdp/ValueIterationSolverTest.java

diff --git a/src/aima/core/environment/cellworld/Cell.java b/src/aima/core/environment/cellworld/Cell.java
deleted file mode 100644
index fa6c4ea..0000000
--- a/src/aima/core/environment/cellworld/Cell.java
+++ /dev/null
@@ -1,87 +0,0 @@
-package aima.core.environment.cellworld;
-
-/**
- * Artificial Intelligence A Modern Approach (3rd Edition): page 645.<br>
- * <br>
- * A representation of a Cell in the environment detailed in Figure 17.1.
- * 
- * @param <C>
- *            the content type of the cell.
- * 
- * @author Ciaran O'Reilly
- * @author Ravi Mohan
- */
-public class Cell<C> {
-	private int x = 1;
-	private int y = 1;
-	private C content = null;
-
-	/**
-	 * Construct a Cell.
-	 * 
-	 * @param x
-	 *            the x position of the cell.
-	 * @param y
-	 *            the y position of the cell.
-	 * @param content
-	 *            the initial content of the cell.
-	 */
-	public Cell(int x, int y, C content) {
-		this.x = x;
-		this.y = y;
-		this.content = content;
-	}
-
-	/**
-	 * 
-	 * @return the x position of the cell.
-	 */
-	public int getX() {
-		return x;
-	}
-
-	/**
-	 * 
-	 * @return the y position of the cell.
-	 */
-	public int getY() {
-		return y;
-	}
-
-	/**
-	 * 
-	 * @return the content of the cell.
-	 */
-	public C getContent() {
-		return content;
-	}
-
-	/**
-	 * Set the cell's content.
-	 * 
-	 * @param content
-	 *            the content to be placed in the cell.
-	 */
-	public void setContent(C content) {
-		this.content = content;
-	}
-
-	@Override
-	public String toString() {
-		return "<x=" + x + ", y=" + y + ", content=" + content + ">";
-	}
-
-	@Override
-	public boolean equals(Object o) {
-		if (o instanceof Cell<?>) {
-			Cell<?> c = (Cell<?>) o;
-			return x == c.x && y == c.y && content.equals(c.content);
-		}
-		return false;
-	}
-
-	@Override
-	public int hashCode() {
-		return x + 23 + y + 31 * content.hashCode();
-	}
-}
diff --git a/src/aima/core/environment/cellworld/CellWorld.java b/src/aima/core/environment/cellworld/CellWorld.java
deleted file mode 100644
index 20d8a78..0000000
--- a/src/aima/core/environment/cellworld/CellWorld.java
+++ /dev/null
@@ -1,123 +0,0 @@
-package aima.core.environment.cellworld;
-
-import java.util.HashMap;
-import java.util.LinkedHashSet;
-import java.util.Map;
-import java.util.Set;
-
-/**
- * Artificial Intelligence A Modern Approach (3rd Edition): page 645.<br>
- * <br>
- * 
- * A representation for the environment depicted in figure 17.1.<br>
- * <br>
- * <b>Note:<b> the x and y coordinates are always positive integers starting at
- * 1.<br>
- * <b>Note:<b> If looking at a rectangle - the coordinate (x=1, y=1) will be the
- * bottom left hand corner.<br>
- * 
- * 
- * @param <C>
- *            the type of content for the Cells in the world.
- * 
- * @author Ciaran O'Reilly
- * @author Ravi Mohan
- */
-public class CellWorld<C> {
-	private Set<Cell<C>> cells = new LinkedHashSet<Cell<C>>();
-	private Map<Integer, Map<Integer, Cell<C>>> cellLookup = new HashMap<Integer, Map<Integer, Cell<C>>>();
-
-	/**
-	 * Construct a Cell World with size xDimension * y Dimension cells, all with
-	 * their values set to a default content value.
-	 * 
-	 * @param xDimension
-	 *            the size of the x dimension.
-	 * @param yDimension
-	 *            the size of the y dimension.
-	 * 
-	 * @param defaultCellContent
-	 *            the default content to assign to each cell created.
-	 */
-	public CellWorld(int xDimension, int yDimension, C defaultCellContent) {
-		for (int x = 1; x <= xDimension; x++) {
-			Map<Integer, Cell<C>> xCol = new HashMap<Integer, Cell<C>>();
-			for (int y = 1; y <= yDimension; y++) {
-				Cell<C> c = new Cell<C>(x, y, defaultCellContent);
-				cells.add(c);
-				xCol.put(y, c);
-			}
-			cellLookup.put(x, xCol);
-		}
-	}
-
-	/**
-	 * 
-	 * @return all the cells in this world.
-	 */
-	public Set<Cell<C>> getCells() {
-		return cells;
-	}
-
-	/**
-	 * Determine what cell would be moved into if the specified action is
-	 * performed in the specified cell. Normally, this will be the cell adjacent
-	 * in the appropriate direction. However, if there is no cell in the
-	 * adjacent direction of the action then the outcome of the action is to
-	 * stay in the same cell as the action was performed in.
-	 * 
-	 * @param s
-	 *            the cell location from which the action is to be performed.
-	 * @param a
-	 *            the action to perform (Up, Down, Left, or Right).
-	 * @return the Cell an agent would end up in if they performed the specified
-	 *         action from the specified cell location.
-	 */
-	public Cell<C> result(Cell<C> s, CellWorldAction a) {
-		Cell<C> sDelta = getCellAt(a.getXResult(s.getX()), a.getYResult(s
-				.getY()));
-		if (null == sDelta) {
-			// Default to no effect
-			// (i.e. bumps back in place as no adjoining cell).
-			sDelta = s;
-		}
-
-		return sDelta;
-	}
-
-	/**
-	 * Remove the cell at the specified location from this Cell World. This
-	 * allows you to introduce barriers into different location.
-	 * 
-	 * @param x
-	 *            the x dimension of the cell to be removed.
-	 * @param y
-	 *            the y dimension of the cell to be removed.
-	 */
-	public void removeCell(int x, int y) {
-		Map<Integer, Cell<C>> xCol = cellLookup.get(x);
-		if (null != xCol) {
-			cells.remove(xCol.remove(y));
-		}
-	}
-
-	/**
-	 * Get the cell at the specified x and y locations.
-	 * 
-	 * @param x
-	 *            the x dimension of the cell to be retrieved.
-	 * @param y
-	 *            the y dimension of the cell to be retrieved.
-	 * @return the cell at the specified x,y location, null if no cell exists at
-	 *         this location.
-	 */
-	public Cell<C> getCellAt(int x, int y) {
-		Cell<C> c = null;
-		Map<Integer, Cell<C>> xCol = cellLookup.get(x);
-		if (null != xCol) {
-			c = xCol.get(y);
-		}
-
-		return c;
-	}
-}
diff --git a/src/aima/core/environment/cellworld/CellWorldAction.java b/src/aima/core/environment/cellworld/CellWorldAction.java
deleted file mode 100644
index ae14bd8..0000000
--- a/src/aima/core/environment/cellworld/CellWorldAction.java
+++ /dev/null
@@ -1,142 +0,0 @@
-package aima.core.environment.cellworld;
-
-import java.util.LinkedHashSet;
-import java.util.Set;
-
-import aima.core.agent.Action;
-
-/**
- * Artificial Intelligence A Modern Approach (3rd Edition): page 645.<br>
- * <br>
- * 
- * The actions in every state are Up, Down, Left, and Right.<br>
- * <br>
- * <b>Note:<b> Moving 'North' causes y to increase by 1, 'Down' y to decrease by
- * 1, 'Left' x to decrease by 1, and 'Right' x to increase by 1 within a Cell
- * World.
- * 
- * @author Ciaran O'Reilly
- * 
- */
-public enum CellWorldAction implements Action {
-	Up, Down, Left, Right, None;
-
-	private static final Set<CellWorldAction> _actions = new LinkedHashSet<CellWorldAction>();
-	static {
-		_actions.add(Up);
-		_actions.add(Down);
-		_actions.add(Left);
-		_actions.add(Right);
-		_actions.add(None);
-	}
-
-	/**
-	 * 
-	 * @return a set of the actual actions.
-	 */
-	public static final Set<CellWorldAction> actions() {
-		return _actions;
-	}
-	
-	//
-	// START-Action
-	//@Override
-	//public boolean isNoOp() {
-	//	if (None == this) {
-	//		return true;
-	//	}
-	//	return false;
-	//}
-	// END-Action
-	//
-
-	/**
-	 * 
-	 * @param curX
-	 *            the current x position.
-	 * @return the result on the x position of applying this action.
-	 */
-	public int getXResult(int curX) {
-		int newX = curX;
-
-		switch (this) {
-		case Left:
-			newX--;
-			break;
-		case Right:
-			newX++;
-			break;
-		}
-
-		return newX;
-	}
-
-	/**
-	 * 
-	 * @param curY
-	 *            the current y position.
-	 * @return the result on the y position of applying this action.
-	 */
-	public int getYResult(int curY) {
-		int newY = curY;
-
-		switch (this) {
-		case Up:
-			newY++;
-			break;
-		case Down:
-			newY--;
-			break;
-		}
-
-		return newY;
-	}
-
-	/**
-	 * 
-	 * @return the first right angled action related to this action.
-	 */
-	public CellWorldAction getFirstRightAngledAction() {
-		CellWorldAction a = null;
-
-		switch (this) {
-		case Up:
-		case Down:
-			a = Left;
-			break;
-		case Left:
-		case Right:
-			a = Down;
-			break;
-		case None:
-			a = None;
-			break;
-		}
-
-		return a;
-	}
-
-	/**
-	 * 
-	 * @return the second right angled action related to this action.
-	 */
-	public CellWorldAction getSecondRightAngledAction() {
-		CellWorldAction a = null;
-
-		switch (this) {
-		case Up:
-		case Down:
-			a = Right;
-			break;
-		case Left:
-		case Right:
-			a = Up;
-			break;
-		case None:
-			a = None;
-			break;
-		}
-
-		return a;
-	}
-}
diff --git a/src/aima/core/environment/cellworld/CellWorldFactory.java b/src/aima/core/environment/cellworld/CellWorldFactory.java
deleted file mode 100644
index 16ad6ac..0000000
--- a/src/aima/core/environment/cellworld/CellWorldFactory.java
+++ /dev/null
@@ -1,27 +0,0 @@
-package aima.core.environment.cellworld;
-
-/**
- * 
- * @author Ciaran O'Reilly
- * 
- */
-public class CellWorldFactory {
-
-	/**
-	 * Create the cell world as defined in Figure 17.1 in AIMA3e. (a) A simple 4
-	 * x 3 environment that presents the agent with a sequential decision
-	 * problem.
-	 * 
-	 * @return a cell world representation of Fig 17.1 in AIMA3e.
-	 */
-	public static CellWorld<Double> createCellWorldForFig17_1() {
-		CellWorld<Double> cw = new CellWorld<Double>(4, 3, -0.04);
-
-		cw.removeCell(2, 2);
-
-		cw.getCellAt(4, 3).setContent(1.0);
-		cw.getCellAt(4, 2).setContent(-1.0);
-
-		return cw;
-	}
-}
\ No newline at end of file
diff --git a/src/aima/core/environment/gridworld/GridWorldFactory.java b/src/aima/core/environment/gridworld/GridWorldFactory.java
index 35afccf..0d5f767 100644
--- a/src/aima/core/environment/gridworld/GridWorldFactory.java
+++ b/src/aima/core/environment/gridworld/GridWorldFactory.java
@@ -17,7 +17,12 @@ public class GridWorldFactory {
 		GridWorld<Double> cw = new GridWorld<Double>(maxTiles, maxScore, nonTerminalReward);
 
 		cw.getCellAt(maxTiles, maxScore).setContent(1.0);
-
+		for (int score = 1; score < maxScore; score++) {
+			cw.getCellAt(maxTiles, score).setContent(-0.2);
+		}
+		for (int tiles = 1; tiles < maxTiles; tiles++) {
+			cw.getCellAt(tiles, maxScore).setContent(-0.2);
+		}	
 		return cw;
 	}
 }
\ No newline at end of file
diff --git a/src/aima/core/probability/example/MDPFactory.java b/src/aima/core/probability/example/MDPFactory.java
index 5494a73..ab21fb0 100644
--- a/src/aima/core/probability/example/MDPFactory.java
+++ b/src/aima/core/probability/example/MDPFactory.java
@@ -6,9 +6,6 @@ import java.util.HashSet;
 import java.util.List;
 import java.util.Set;
 
-import aima.core.environment.cellworld.Cell;
-import aima.core.environment.cellworld.CellWorld;
-import aima.core.environment.cellworld.CellWorldAction;
 import aima.core.environment.gridworld.GridCell;
 import aima.core.environment.gridworld.GridWorld;
 import aima.core.environment.gridworld.GridWorldAction;
@@ -19,30 +16,11 @@ import aima.core.probability.mdp.TransitionProbabilityFunction;
 import aima.core.probability.mdp.impl.MDP;
 
 /**
- * 
- * @author Ciaran O'Reilly
- * @author Ravi Mohan
+ * Based on MDPFactory by Ciaran O'Reilly and Ravi Mohan.
+ * @author Woody
  */
 public class MDPFactory {
 
-	/**
-	 * Constructs an MDP that can be used to generate the utility values
-	 * detailed in Fig 17.3.
-	 * 
-	 * @param cw
-	 *            the cell world from figure 17.1.
-	 * @return an MDP that can be used to generate the utility values detailed
-	 *         in Fig 17.3.
-	 */
-	public static MarkovDecisionProcess<Cell<Double>, CellWorldAction> createMDPForFigure17_3(
-			final CellWorld<Double> cw) {
-
-		return new MDP<Cell<Double>, CellWorldAction>(cw.getCells(),
-				cw.getCellAt(1, 1), createActionsFunctionForFigure17_1(cw),
-				createTransitionProbabilityFunctionForFigure17_1(cw),
-				createRewardFunctionForFigure17_1());
-	}
-
 	public static MarkovDecisionProcess<GridCell<Double>, GridWorldAction> createMDPForTileGame(
 			final GridWorld<Double> cw, int maxTiles, int maxScore) {
 
@@ -52,36 +30,6 @@ public class MDPFactory {
 				createRewardFunctionForTileGame());
 	}
 	
-	/**
-	 * Returns the allowed actions from a specified cell within the cell world
-	 * described in Fig 17.1.
-	 * 
-	 * @param cw
-	 *            the cell world from figure 17.1.
-	 * @return the set of actions allowed at a particular cell. This set will be
-	 *         empty if at a terminal state.
-	 */
-	public static ActionsFunction<Cell<Double>, CellWorldAction> createActionsFunctionForFigure17_1(
-			final CellWorld<Double> cw) {
-		final Set<Cell<Double>> terminals = new HashSet<Cell<Double>>();
-		terminals.add(cw.getCellAt(4, 3));
-		terminals.add(cw.getCellAt(4, 2));
-
-		ActionsFunction<Cell<Double>, CellWorldAction> af = new ActionsFunction<Cell<Double>, CellWorldAction>() {
-
-			@Override
-			public Set<CellWorldAction> actions(Cell<Double> s) {
-				// All actions can be performed in each cell
-				// (except terminal states)
-				if (terminals.contains(s)) {
-					return Collections.emptySet();
-				}
-				return CellWorldAction.actions();
-			}
-		};
-		return af;
-	}
-	
 	public static ActionsFunction<GridCell<Double>, GridWorldAction> createActionsFunctionForTileGame(
 			final GridWorld<Double> cw, int maxTiles, int maxScore) {
 		final Set<GridCell<Double>> terminals = new HashSet<GridCell<Double>>();
@@ -102,59 +50,6 @@ public class MDPFactory {
 		
 		return af;
 	}
-	
-	/**
-	 * Figure 17.1 (b) Illustration of the transition model of the environment:
-	 * the 'intended' outcome occurs with probability 0.8, but with probability
-	 * 0.2 the agent moves at right angles to the intended direction. A
-	 * collision with a wall results in no movement.
-	 * 
-	 * @param cw
-	 *            the cell world from figure 17.1.
-	 * @return the transition probability function as described in figure 17.1.
-	 */
-	public static TransitionProbabilityFunction<Cell<Double>, CellWorldAction> createTransitionProbabilityFunctionForFigure17_1(
-			final CellWorld<Double> cw) {
-		TransitionProbabilityFunction<Cell<Double>, CellWorldAction> tf = new TransitionProbabilityFunction<Cell<Double>, CellWorldAction>() {
-			private double[] distribution = new double[] { 0.8, 0.1, 0.1 };
-
-			@Override
-			public double probability(Cell<Double> sDelta, Cell<Double> s,
-					CellWorldAction a) {
-				double prob = 0;
-
-				List<Cell<Double>> outcomes = possibleOutcomes(s, a);
-				for (int i = 0; i < outcomes.size(); i++) {
-					if (sDelta.equals(outcomes.get(i))) {
-						// Note: You have to sum the matches to
-						// sDelta as the different actions
-						// could have the same effect (i.e.
-						// staying in place due to there being
-						// no adjacent cells), which increases
-						// the probability of the transition for
-						// that state.
-						prob += distribution[i];
-					}
-				}
-
-				return prob;
-			}
-			
-			private List<Cell<Double>> possibleOutcomes(Cell<Double> c,
-					CellWorldAction a) {
-				// There can be three possible outcomes for the planned action
-				List<Cell<Double>> outcomes = new ArrayList<Cell<Double>>();
-
-				outcomes.add(cw.result(c, a));
-				outcomes.add(cw.result(c, a.getFirstRightAngledAction()));
-				outcomes.add(cw.result(c, a.getSecondRightAngledAction()));
-
-				return outcomes;
-			}
-		};
-
-		return tf;
-	}
 
 	public static TransitionProbabilityFunction<GridCell<Double>, GridWorldAction> createTransitionProbabilityFunctionForTileGame(
 			final GridWorld<Double> cw) {
@@ -170,13 +65,6 @@ public class MDPFactory {
 				List<GridCell<Double>> outcomes = possibleOutcomes(s, a);
 				for (int i = 0; i < outcomes.size(); i++) {
 					if (sDelta.equals(outcomes.get(i))) {
-						// Note: You have to sum the matches to
-						// sDelta as the different actions
-						// could have the same effect (i.e.
-						// staying in place due to there being
-						// no adjacent cells), which increases
-						// the probability of the transition for
-						// that state.
 						prob += distribution[i];
 					}
 				}
@@ -198,7 +86,7 @@ public class MDPFactory {
 			}
 			private List<GridCell<Double>> possibleOutcomes(GridCell<Double> c,
 					GridWorldAction a) {
-				// There can be three possible outcomes for the planned action
+				
 				List<GridCell<Double>> outcomes = new ArrayList<GridCell<Double>>();
 
 				switch (a) {
@@ -224,21 +112,6 @@ public class MDPFactory {
 		return tf;
 	}
 	
-	/**
-	 * 
-	 * @return the reward function which takes the content of the cell as being
-	 *         the reward value.
-	 */
-	public static RewardFunction<Cell<Double>> createRewardFunctionForFigure17_1() {
-		RewardFunction<Cell<Double>> rf = new RewardFunction<Cell<Double>>() {
-			@Override
-			public double reward(Cell<Double> s) {
-				return s.getContent();
-			}
-		};
-		return rf;
-	}
-	
 	public static RewardFunction<GridCell<Double>> createRewardFunctionForTileGame() {
 		RewardFunction<GridCell<Double>> rf = new RewardFunction<GridCell<Double>>() {
 			@Override
diff --git a/src/model/comPlayer/AdaptiveComPlayer.java b/src/model/comPlayer/AdaptiveComPlayer.java
index 5413f1b..03725c5 100644
--- a/src/model/comPlayer/AdaptiveComPlayer.java
+++ b/src/model/comPlayer/AdaptiveComPlayer.java
@@ -119,5 +119,6 @@ public class AdaptiveComPlayer implements Player {
 	@Override
 	public void setGameGoal(GameGoal target) {
 		this.target = target;
+		this.calculatePolicy = true;
 	}
 }
\ No newline at end of file
diff --git a/src/model/mdp/Action.java b/src/model/mdp/Action.java
deleted file mode 100644
index cda7b6d..0000000
--- a/src/model/mdp/Action.java
+++ /dev/null
@@ -1,18 +0,0 @@
-package model.mdp;
-
-public class Action {
-	public static Action playToWin = new Action("PlayToWin");
-	public static Action playToLose = new Action("PlayToLose");
-	//public static Action maintainScore = new Action();
-	
-	private final String name;
-	
-	public Action(String name) {
-		this.name = name;
-	}
-	
-	@Override
-	public String toString() {
-		return name;
-	}
-}
diff --git a/src/model/mdp/MDP.java b/src/model/mdp/MDP.java
deleted file mode 100644
index fe534b7..0000000
--- a/src/model/mdp/MDP.java
+++ /dev/null
@@ -1,51 +0,0 @@
-package model.mdp;
-
-public class MDP {
-	public static final double nonTerminalReward = -0.25;
-
-	public enum MODE {
-		CEIL, FLOOR
-	}
-
-	private final int maxScore;
-	private final int maxTiles;
-	private final MODE mode;
-
-	public MDP(int maxScore, int maxTiles, MODE mode) {
-		this.maxScore = maxScore;
-		this.maxTiles = maxTiles;
-		this.mode = mode;
-	}
-
-	public Action[] getActions(int i, int j) {
-		if (i == maxScore) {
-			return new Action[0];
-		}
-		if (j == maxTiles) {
-			return new Action[0];
-		}
-		return new Action[]{Action.playToLose,Action.playToWin};
-	}
-	
-	public int getMaxScore() {
-		return maxScore;
-	}
-
-	public int getMaxTiles() {
-		return maxTiles;
-	}
-
-	public double getReward(int score, int tiles) {
-		if (score == maxScore && tiles == maxTiles) {
-			return 10.0;
-		}
-		// TODO scale linearly?
-		if (score == maxScore) {
-			return -1.0;
-		}
-		if (tiles == maxTiles) {
-			return -5.0;
-		}
-		return nonTerminalReward;
-	}
-}
\ No newline at end of file
diff --git a/src/model/mdp/MDPSolver.java b/src/model/mdp/MDPSolver.java
deleted file mode 100644
index 812fed2..0000000
--- a/src/model/mdp/MDPSolver.java
+++ /dev/null
@@ -1,5 +0,0 @@
-package model.mdp;
-
-public interface MDPSolver {
-	Policy solve(MDP mdp);
-}
diff --git a/src/model/mdp/Policy.java b/src/model/mdp/Policy.java
deleted file mode 100644
index 66b9b0c..0000000
--- a/src/model/mdp/Policy.java
+++ /dev/null
@@ -1,7 +0,0 @@
-package model.mdp;
-
-import java.util.ArrayList;
-
-public class Policy extends ArrayList<Action>{
-
-}
diff --git a/src/model/mdp/Transition.java b/src/model/mdp/Transition.java
deleted file mode 100644
index 5148b8f..0000000
--- a/src/model/mdp/Transition.java
+++ /dev/null
@@ -1,34 +0,0 @@
-package model.mdp;
-
-public class Transition {
-	private double prob;
-	private int scoreChange;
-	private int tileCountChange;
-	
-	public Transition(double prob, int scoreChange, int tileCountChange) {
-		super();
-		this.prob = prob;
-		this.scoreChange = scoreChange;
-		this.tileCountChange = tileCountChange;
-	}
-	
-	public double getProb() {
-		return prob;
-	}
-	public void setProb(double prob) {
-		this.prob = prob;
-	}
-	public int getScoreChange() {
-		return scoreChange;
-	}
-	public void setScoreChange(int scoreChange) {
-		this.scoreChange = scoreChange;
-	}
-	public int getTileCountChange() {
-		return tileCountChange;
-	}
-	public void setTileCountChange(int tileCountChange) {
-		this.tileCountChange = tileCountChange;
-	}
-	
-}
\ No newline at end of file
diff --git a/src/model/mdp/ValueIterationSolver.java b/src/model/mdp/ValueIterationSolver.java
deleted file mode 100644
index 35e9d87..0000000
--- a/src/model/mdp/ValueIterationSolver.java
+++ /dev/null
@@ -1,110 +0,0 @@
-package model.mdp;
-
-import java.text.DecimalFormat;
-import java.util.ArrayList;
-import java.util.List;
-
-public class ValueIterationSolver implements MDPSolver {
-	public int maxIterations = 10;
-	public final double DEFAULT_EPS = 0.1;
-	public final double GAMMA = 0.9; //discount
-	
-	private DecimalFormat fmt = new DecimalFormat("##.00");
-	public Policy solve(MDP mdp) {
-		Policy policy = new Policy();
-		
-		double[][] utility = new double[mdp.getMaxScore()+1][mdp.getMaxTiles()+1];
-		double[][] utilityPrime = new double[mdp.getMaxScore()+1][mdp.getMaxTiles()+1];
-		
-		for (int i = 0; i <= mdp.getMaxScore(); i++) {
-			//StringBuilder sb = new StringBuilder();
-			for (int j = 0; j <= mdp.getMaxTiles(); j++) {
-				utilityPrime[i][j] = mdp.getReward(i, j);
-				//sb.append(fmt.format(utility[i][j]));
-				//sb.append(" ");
-			}
-			//System.out.println(sb);
-		}
-		
-		converged:
-		for (int iteration = 0; iteration < maxIterations; iteration++) {
-			for (int i = 0; i <= mdp.getMaxScore(); i++) {
-				for (int j = 0; j <= mdp.getMaxTiles(); j++) {
-					utility[i][j] = utilityPrime[i][j];
-				}
-			}
-			for (int i = 0; i <= mdp.getMaxScore(); i++) {
-				for (int j = 0; j <= mdp.getMaxTiles(); j++) {
-					Action[] actions = mdp.getActions(i,j);
-					
-					double aMax;
-					if (actions.length > 0) {
-						aMax = Double.NEGATIVE_INFINITY;
-					} else {
-						aMax = 0;
-					}
-					
-					for (Action action : actions){
-						List<Transition> transitions = getTransitions(action,mdp,i,j);
-						double aSum = 0.0;
-						for (Transition transition : transitions) {
-							int transI = transition.getScoreChange();
-							int transJ = transition.getTileCountChange();
-							if (i+transI >= 0 && i+transI <= mdp.getMaxScore()
-									&& j+transJ >= 0 && j+transJ <= mdp.getMaxTiles())
-							aSum += utility[i+transI][j+transJ];
-						}
-						if (aSum > aMax) {
-							aMax = aSum;
-						}
-					}
-					utilityPrime[i][j] = mdp.getReward(i,j) + GAMMA * aMax;
-				}
-			}
-			double maxDiff = getMaxDiff(utility,utilityPrime);
-			System.out.println("Max diff |U - U'| = " + maxDiff);
-			if (maxDiff < DEFAULT_EPS) {
-				System.out.println("Solution to MDP converged: " + maxDiff);
-				break converged;
-			}
-		}
-		
-		for (int i = 0; i < utility.length; i++) {
-			StringBuilder sb = new StringBuilder();
-			for (int j = 0; j < utility[i].length; j++) {
-				sb.append(fmt.format(utility[i][j]));
-				sb.append(" ");
-			}
-			System.out.println(sb);
-		}
-		
-		//utility is now the utility Matrix
-		//get the policy
-		return policy;
-	}
-	
-	double getMaxDiff(double[][]u, double[][]uPrime) {
-		double maxDiff = 0;
-		for (int i = 0; i < u.length; i++) {
-			for (int j = 0; j < u[i].length; j++) {
-				maxDiff = Math.max(maxDiff,Math.abs(u[i][j] - uPrime[i][j]));
-			}
-		}
-		return maxDiff;
-	}
-	
-	private List<Transition> getTransitions(Action action, MDP mdp, int score, int tiles) {
-		List<Transition> transitions = new ArrayList<Transition>();
-		if (Action.playToWin == action) {
-			transitions.add(new Transition(0.9,1,1));
-			transitions.add(new Transition(0.1,1,-3));
-		} else if (Action.playToLose == action) {
-			transitions.add(new Transition(0.9,1,1));
-			transitions.add(new Transition(0.1,1,-3));			
-		} /*else if (Action.maintainScore == action) {
-			transitions.add(new Transition(0.5,1,1));
-			transitions.add(new Transition(0.5,1,-3));				
-		}*/
-		return transitions;
-	}
-}
\ No newline at end of file
diff --git a/test/PlayerModel.dat b/test/PlayerModel.dat
new file mode 100644
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diff --git a/test/aima/core/probability/mdp/MarkovDecisionProcessTest.java b/test/aima/core/probability/mdp/MarkovDecisionProcessTest.java
index e266e92..200c644 100644
--- a/test/aima/core/probability/mdp/MarkovDecisionProcessTest.java
+++ b/test/aima/core/probability/mdp/MarkovDecisionProcessTest.java
@@ -5,91 +5,57 @@ import junit.framework.Assert;
 import org.junit.Before;
 import org.junit.Test;
 
-import aima.core.environment.cellworld.Cell;
-import aima.core.environment.cellworld.CellWorld;
-import aima.core.environment.cellworld.CellWorldAction;
-import aima.core.environment.cellworld.CellWorldFactory;
+import aima.core.environment.gridworld.GridCell;
+import aima.core.environment.gridworld.GridWorld;
+import aima.core.environment.gridworld.GridWorldAction;
+import aima.core.environment.gridworld.GridWorldFactory;
 import aima.core.probability.example.MDPFactory;
 import aima.core.probability.mdp.MarkovDecisionProcess;
 
 /**
- * 
- * @author Ciaran O'Reilly
- * @author Ravi Mohan
- *
+ * Based on MarkovDecisionProcessTest by Ciaran O'Reilly and Ravi Mohan.  Used under MIT license.
  */
 public class MarkovDecisionProcessTest {
 	public static final double DELTA_THRESHOLD = 1e-3;
 
-	private CellWorld<Double> cw = null;
-	private MarkovDecisionProcess<Cell<Double>, CellWorldAction> mdp = null;
+	private double nonTerminalReward = -0.04;
+	private GridWorld<Double> gw = null;
+	private MarkovDecisionProcess<GridCell<Double>, GridWorldAction> mdp = null;
 
 	@Before
 	public void setUp() {
-		cw = CellWorldFactory.createCellWorldForFig17_1();
-		mdp = MDPFactory.createMDPForFigure17_3(cw);
+		int maxTiles = 6;
+		int maxScore = 10;
+		
+		gw = GridWorldFactory.createGridWorldForTileGame(maxTiles, maxScore, nonTerminalReward);
+		mdp = MDPFactory.createMDPForTileGame(gw, maxTiles, maxScore);
 	}
 
 	@Test
 	public void testActions() {
 		// Ensure all actions can be performed in each cell
 		// except for the terminal states.
-		for (Cell<Double> s : cw.getCells()) {
-			if (4 == s.getX() && (3 == s.getY() || 2 == s.getY())) {
+		for (GridCell<Double> s : gw.getCells()) {
+			if (6 == s.getX() && 10 == s.getY()) {
 				Assert.assertEquals(0, mdp.actions(s).size());
 			} else {
-				Assert.assertEquals(5, mdp.actions(s).size());
+				Assert.assertEquals(3, mdp.actions(s).size());
 			}
 		}
 	}
 
 	@Test
 	public void testMDPTransitionModel() {
-		Assert.assertEquals(0.8, mdp.transitionProbability(cw.getCellAt(1, 2),
-				cw.getCellAt(1, 1), CellWorldAction.Up), DELTA_THRESHOLD);
-		Assert.assertEquals(0.1, mdp.transitionProbability(cw.getCellAt(1, 1),
-				cw.getCellAt(1, 1), CellWorldAction.Up), DELTA_THRESHOLD);
-		Assert.assertEquals(0.1, mdp.transitionProbability(cw.getCellAt(2, 1),
-				cw.getCellAt(1, 1), CellWorldAction.Up), DELTA_THRESHOLD);
-		Assert.assertEquals(0.0, mdp.transitionProbability(cw.getCellAt(1, 3),
-				cw.getCellAt(1, 1), CellWorldAction.Up), DELTA_THRESHOLD);
-
-		Assert.assertEquals(0.9, mdp.transitionProbability(cw.getCellAt(1, 1),
-				cw.getCellAt(1, 1), CellWorldAction.Down), DELTA_THRESHOLD);
-		Assert.assertEquals(0.1, mdp.transitionProbability(cw.getCellAt(2, 1),
-				cw.getCellAt(1, 1), CellWorldAction.Down), DELTA_THRESHOLD);
-		Assert.assertEquals(0.0, mdp.transitionProbability(cw.getCellAt(3, 1),
-				cw.getCellAt(1, 1), CellWorldAction.Down), DELTA_THRESHOLD);
-		Assert.assertEquals(0.0, mdp.transitionProbability(cw.getCellAt(1, 2),
-				cw.getCellAt(1, 1), CellWorldAction.Down), DELTA_THRESHOLD);
-
-		Assert.assertEquals(0.9, mdp.transitionProbability(cw.getCellAt(1, 1),
-				cw.getCellAt(1, 1), CellWorldAction.Left), DELTA_THRESHOLD);
-		Assert.assertEquals(0.0, mdp.transitionProbability(cw.getCellAt(2, 1),
-				cw.getCellAt(1, 1), CellWorldAction.Left), DELTA_THRESHOLD);
-		Assert.assertEquals(0.0, mdp.transitionProbability(cw.getCellAt(3, 1),
-				cw.getCellAt(1, 1), CellWorldAction.Left), DELTA_THRESHOLD);
-		Assert.assertEquals(0.1, mdp.transitionProbability(cw.getCellAt(1, 2),
-				cw.getCellAt(1, 1), CellWorldAction.Left), DELTA_THRESHOLD);
-
-		Assert.assertEquals(0.8, mdp.transitionProbability(cw.getCellAt(2, 1),
-				cw.getCellAt(1, 1), CellWorldAction.Right), DELTA_THRESHOLD);
-		Assert.assertEquals(0.1, mdp.transitionProbability(cw.getCellAt(1, 1),
-				cw.getCellAt(1, 1), CellWorldAction.Right), DELTA_THRESHOLD);
-		Assert.assertEquals(0.1, mdp.transitionProbability(cw.getCellAt(1, 2),
-				cw.getCellAt(1, 1), CellWorldAction.Right), DELTA_THRESHOLD);
-		Assert.assertEquals(0.0, mdp.transitionProbability(cw.getCellAt(1, 3),
-				cw.getCellAt(1, 1), CellWorldAction.Right), DELTA_THRESHOLD);
+		Assert.assertEquals(0.66, mdp.transitionProbability(gw.getCellAt(2, 2),
+				gw.getCellAt(1, 1), GridWorldAction.AddTile), DELTA_THRESHOLD);
 	}
 
 	@Test
 	public void testRewardFunction() {
 		// Ensure all actions can be performed in each cell.
-		for (Cell<Double> s : cw.getCells()) {
-			if (4 == s.getX() && 3 == s.getY()) {
+		for (GridCell<Double> s : gw.getCells()) {
+			if (6 == s.getX() && 10 == s.getY()) {
 				Assert.assertEquals(1.0, mdp.reward(s), DELTA_THRESHOLD);
-			} else if (4 == s.getX() && 2 == s.getY()) {
-				Assert.assertEquals(-1.0, mdp.reward(s), DELTA_THRESHOLD);
 			} else {
 				Assert.assertEquals(-0.04, mdp.reward(s), DELTA_THRESHOLD);
 			}
diff --git a/test/aima/core/probability/mdp/PolicyIterationTest.java b/test/aima/core/probability/mdp/PolicyIterationTest.java
index 255f403..f9cbe22 100644
--- a/test/aima/core/probability/mdp/PolicyIterationTest.java
+++ b/test/aima/core/probability/mdp/PolicyIterationTest.java
@@ -1,15 +1,8 @@
 package aima.core.probability.mdp;
 
-import java.util.Map;
-
-import org.junit.Assert;
 import org.junit.Before;
 import org.junit.Test;
 
-import aima.core.environment.cellworld.Cell;
-import aima.core.environment.cellworld.CellWorld;
-import aima.core.environment.cellworld.CellWorldAction;
-import aima.core.environment.cellworld.CellWorldFactory;
 import aima.core.environment.gridworld.GridCell;
 import aima.core.environment.gridworld.GridWorld;
 import aima.core.environment.gridworld.GridWorldAction;
@@ -18,7 +11,6 @@ import aima.core.probability.example.MDPFactory;
 import aima.core.probability.mdp.MarkovDecisionProcess;
 import aima.core.probability.mdp.impl.ModifiedPolicyEvaluation;
 import aima.core.probability.mdp.search.PolicyIteration;
-import aima.core.probability.mdp.search.ValueIteration;
 
 /**
  * @author Ravi Mohan
@@ -29,28 +21,31 @@ public class PolicyIterationTest {
 	public static final double DELTA_THRESHOLD = 1e-3;
 
 	private GridWorld<Double> gw = null;
-	private MarkovDecisionProcess<GridCell<Double>, GridWorldAction> mdp = null;	
+	private MarkovDecisionProcess<GridCell<Double>, GridWorldAction> mdp = null;
 	private PolicyIteration<GridCell<Double>, GridWorldAction> pi = null;
 
 	final int maxTiles = 6;
 	final int maxScore = 10;
-	
+
 	@Before
 	public void setUp() {
-		//take 10 turns to place 6 tiles
+		// take 10 turns to place 6 tiles
 		double defaultPenalty = -0.04;
-		
-		gw = GridWorldFactory.createGridWorldForTileGame(maxTiles,maxScore,defaultPenalty);
+
+		gw = GridWorldFactory.createGridWorldForTileGame(maxTiles, maxScore,
+				defaultPenalty);
 		mdp = MDPFactory.createMDPForTileGame(gw, maxTiles, maxScore);
-				
-		//gamma = 1.0
-		PolicyEvaluation<GridCell<Double>,GridWorldAction> pe = new ModifiedPolicyEvaluation<GridCell<Double>, GridWorldAction>(100,0.9);
+
+		// gamma = 1.0
+		PolicyEvaluation<GridCell<Double>, GridWorldAction> pe = new ModifiedPolicyEvaluation<GridCell<Double>, GridWorldAction>(
+				100, 0.9);
 		pi = new PolicyIteration<GridCell<Double>, GridWorldAction>(pe);
 	}
 
 	@Test
 	public void testPolicyIterationForTileGame() {
-		Policy<GridCell<Double>, GridWorldAction> policy = pi.policyIteration(mdp);
+		Policy<GridCell<Double>, GridWorldAction> policy = pi
+				.policyIteration(mdp);
 
 		for (int j = maxScore; j >= 1; j--) {
 			StringBuilder sb = new StringBuilder();
@@ -60,21 +55,5 @@ public class PolicyIterationTest {
 			}
 			System.out.println(sb.toString());
 		}
-		
-		//Assert.assertEquals(0.705, U.get(gw.getCellAt(1, 1)), DELTA_THRESHOLD);
-		/*
-		Assert.assertEquals(0.762, U.get(cw1.getCellAt(1, 2)), DELTA_THRESHOLD);
-		Assert.assertEquals(0.812, U.get(cw1.getCellAt(1, 3)), DELTA_THRESHOLD);
-
-		Assert.assertEquals(0.655, U.get(cw1.getCellAt(2, 1)), DELTA_THRESHOLD);
-		Assert.assertEquals(0.868, U.get(cw1.getCellAt(2, 3)), DELTA_THRESHOLD);
-
-		Assert.assertEquals(0.611, U.get(cw1.getCellAt(3, 1)), DELTA_THRESHOLD);
-		Assert.assertEquals(0.660, U.get(cw1.getCellAt(3, 2)), DELTA_THRESHOLD);
-		Assert.assertEquals(0.918, U.get(cw1.getCellAt(3, 3)), DELTA_THRESHOLD);
-
-		Assert.assertEquals(0.388, U.get(cw1.getCellAt(4, 1)), DELTA_THRESHOLD);
-		Assert.assertEquals(-1.0, U.get(cw1.getCellAt(4, 2)), DELTA_THRESHOLD);
-		Assert.assertEquals(1.0, U.get(cw1.getCellAt(4, 3)), DELTA_THRESHOLD);*/
 	}
 }
diff --git a/test/aima/core/probability/mdp/ValueIterationTest.java b/test/aima/core/probability/mdp/ValueIterationTest.java
deleted file mode 100644
index 9d1215e..0000000
--- a/test/aima/core/probability/mdp/ValueIterationTest.java
+++ /dev/null
@@ -1,64 +0,0 @@
-package aima.core.probability.mdp;
-
-import java.util.Map;
-
-import org.junit.Assert;
-import org.junit.Before;
-import org.junit.Test;
-
-import aima.core.environment.cellworld.Cell;
-import aima.core.environment.cellworld.CellWorld;
-import aima.core.environment.cellworld.CellWorldAction;
-import aima.core.environment.cellworld.CellWorldFactory;
-import aima.core.probability.example.MDPFactory;
-import aima.core.probability.mdp.MarkovDecisionProcess;
-import aima.core.probability.mdp.search.ValueIteration;
-
-/**
- * @author Ravi Mohan
- * @author Ciaran O'Reilly
- * 
- */
-public class ValueIterationTest {
-	public static final double DELTA_THRESHOLD = 1e-3;
-
-	private CellWorld<Double> cw = null;
-	private MarkovDecisionProcess<Cell<Double>, CellWorldAction> mdp = null;
-	private ValueIteration<Cell<Double>, CellWorldAction> vi = null;
-
-	@Before
-	public void setUp() {
-		cw = CellWorldFactory.createCellWorldForFig17_1();
-		mdp = MDPFactory.createMDPForFigure17_3(cw);
-		vi = new ValueIteration<Cell<Double>, CellWorldAction>(1.0);
-	}
-
-	@Test
-	public void testValueIterationForFig17_3() {
-		Map<Cell<Double>, Double> U = vi.valueIteration(mdp, 0.0001);
-
-		Assert.assertEquals(0.705, U.get(cw.getCellAt(1, 1)), DELTA_THRESHOLD);
-		Assert.assertEquals(0.762, U.get(cw.getCellAt(1, 2)), DELTA_THRESHOLD);
-		Assert.assertEquals(0.812, U.get(cw.getCellAt(1, 3)), DELTA_THRESHOLD);
-
-		Assert.assertEquals(0.655, U.get(cw.getCellAt(2, 1)), DELTA_THRESHOLD);
-		Assert.assertEquals(0.868, U.get(cw.getCellAt(2, 3)), DELTA_THRESHOLD);
-
-		Assert.assertEquals(0.611, U.get(cw.getCellAt(3, 1)), DELTA_THRESHOLD);
-		Assert.assertEquals(0.660, U.get(cw.getCellAt(3, 2)), DELTA_THRESHOLD);
-		Assert.assertEquals(0.918, U.get(cw.getCellAt(3, 3)), DELTA_THRESHOLD);
-
-		Assert.assertEquals(0.388, U.get(cw.getCellAt(4, 1)), DELTA_THRESHOLD);
-		Assert.assertEquals(-1.0, U.get(cw.getCellAt(4, 2)), DELTA_THRESHOLD);
-		Assert.assertEquals(1.0, U.get(cw.getCellAt(4, 3)), DELTA_THRESHOLD);
-		
-		for (int j = 3; j >= 1; j--) {
-			StringBuilder sb = new StringBuilder();
-			for (int i = 1; i <= 4; i++) {
-				sb.append(U.get(cw.getCellAt(i, j)));
-				sb.append(" ");
-			}
-			System.out.println(sb.toString());
-		}
-	}
-}
diff --git a/test/aima/core/probability/mdp/ValueIterationTest2.java b/test/aima/core/probability/mdp/ValueIterationTest2.java
index a0c6ce1..7b1e0e2 100644
--- a/test/aima/core/probability/mdp/ValueIterationTest2.java
+++ b/test/aima/core/probability/mdp/ValueIterationTest2.java
@@ -6,10 +6,6 @@ import org.junit.Assert;
 import org.junit.Before;
 import org.junit.Test;
 
-import aima.core.environment.cellworld.Cell;
-import aima.core.environment.cellworld.CellWorld;
-import aima.core.environment.cellworld.CellWorldAction;
-import aima.core.environment.cellworld.CellWorldFactory;
 import aima.core.environment.gridworld.GridCell;
 import aima.core.environment.gridworld.GridWorld;
 import aima.core.environment.gridworld.GridWorldAction;
@@ -19,29 +15,30 @@ import aima.core.probability.mdp.MarkovDecisionProcess;
 import aima.core.probability.mdp.search.ValueIteration;
 
 /**
- * @author Ravi Mohan
- * @author Ciaran O'Reilly
  * 
+ * @author Woody
+ *
  */
 public class ValueIterationTest2 {
 	public static final double DELTA_THRESHOLD = 1e-3;
 
 	private GridWorld<Double> gw = null;
-	private MarkovDecisionProcess<GridCell<Double>, GridWorldAction> mdp = null;	
+	private MarkovDecisionProcess<GridCell<Double>, GridWorldAction> mdp = null;
 	private ValueIteration<GridCell<Double>, GridWorldAction> vi = null;
 
 	final int maxTiles = 6;
 	final int maxScore = 10;
-	
+
 	@Before
 	public void setUp() {
-		//take 10 turns to place 6 tiles
+		// take 10 turns to place 6 tiles
 		double defaultPenalty = -0.04;
-		
-		gw = GridWorldFactory.createGridWorldForTileGame(maxTiles,maxScore,defaultPenalty);
+
+		gw = GridWorldFactory.createGridWorldForTileGame(maxTiles, maxScore,
+				defaultPenalty);
 		mdp = MDPFactory.createMDPForTileGame(gw, maxTiles, maxScore);
-				
-		//gamma = 1.0
+
+		// gamma = 1.0
 		vi = new ValueIteration<GridCell<Double>, GridWorldAction>(0.9);
 	}
 
@@ -57,20 +54,7 @@ public class ValueIterationTest2 {
 			}
 			System.out.println(sb.toString());
 		}
-		
-		Assert.assertEquals(0.705, U.get(gw.getCellAt(1, 1)), DELTA_THRESHOLD);/*
-		Assert.assertEquals(0.762, U.get(cw1.getCellAt(1, 2)), DELTA_THRESHOLD);
-		Assert.assertEquals(0.812, U.get(cw1.getCellAt(1, 3)), DELTA_THRESHOLD);
 
-		Assert.assertEquals(0.655, U.get(cw1.getCellAt(2, 1)), DELTA_THRESHOLD);
-		Assert.assertEquals(0.868, U.get(cw1.getCellAt(2, 3)), DELTA_THRESHOLD);
-
-		Assert.assertEquals(0.611, U.get(cw1.getCellAt(3, 1)), DELTA_THRESHOLD);
-		Assert.assertEquals(0.660, U.get(cw1.getCellAt(3, 2)), DELTA_THRESHOLD);
-		Assert.assertEquals(0.918, U.get(cw1.getCellAt(3, 3)), DELTA_THRESHOLD);
-
-		Assert.assertEquals(0.388, U.get(cw1.getCellAt(4, 1)), DELTA_THRESHOLD);
-		Assert.assertEquals(-1.0, U.get(cw1.getCellAt(4, 2)), DELTA_THRESHOLD);
-		Assert.assertEquals(1.0, U.get(cw1.getCellAt(4, 3)), DELTA_THRESHOLD);*/
+		Assert.assertEquals(-0.1874236, U.get(gw.getCellAt(1, 1)), DELTA_THRESHOLD);
 	}
 }
diff --git a/test/model/mdp/ValueIterationSolverTest.java b/test/model/mdp/ValueIterationSolverTest.java
deleted file mode 100644
index dac3656..0000000
--- a/test/model/mdp/ValueIterationSolverTest.java
+++ /dev/null
@@ -1,26 +0,0 @@
-package model.mdp;
-
-import static org.junit.Assert.assertTrue;
-import model.mdp.MDP.MODE;
-
-import org.junit.Test;
-
-public class ValueIterationSolverTest {
-
-	@Test
-	public void testSolve() {
-		MDPSolver solver = new ValueIterationSolver();
-		
-		//solve for a score of 25 in at most 35 turns
-		int maxScore = 6;
-		int maxTurns = 10;
-		
-		MDP mdp = new MDP(maxScore,maxTurns,MODE.CEIL);
-		Policy policy = solver.solve(mdp);
-		
-		assertTrue(policy.size() >= maxScore);
-		assertTrue(policy.size() <= maxTurns);
-		
-		System.out.println("Policy: " + policy);
-	}
-}