public override QState Initialize()
{
WriteOutput("Dimensions: " + width + "x" + height);
self = new Point(start.X, start.Y);
score = 0;
walls = new Point[] { };
// Generate Walls Randomly
if (wallDensity > 0)
{
HashSet<Point> bestPathSoFar = new HashSet<Point>();
WriteOutput("Generating walls randomly with density target of " + wallDensity + "...");
for (int w = 0; w < width; w++)
{
for (int h = 0; h < height; h++)
{
double r = random.NextDouble();
//WriteOutput("Wall Probability for " + w + "x" + h + ": " + r+" vs threshold "+walls);
if (r < wallDensity)
{
//WriteOutput("Wall created at " + w + "x" + h);
Point newWall = new Point(w, h);
if (start == newWall || goal == newWall) continue;
Point[] tempWalls = walls.Concat(new Point[] { newWall }).ToArray();
QState tempState = new Maze() { maze = maze, self = self, goal = goal, width = width, height = height, walls = tempWalls};
if (!bestPathSoFar.Any() || bestPathSoFar.Contains(newWall))
{
QSearchResult path = new QSearch().AStar(tempState);
if (path != null)
{
bestPathSoFar.Clear();
foreach (QState q in path.QStatesList)
bestPathSoFar.Add(((Maze)q).self);
walls = tempWalls;
}
}
else walls = tempWalls;
}
}
}
WriteOutput("Maze generation complete.");
}
opponent = new List<Point>();
for (int i = 0; i < opponents; i++)
opponent.Add(new Point(goal.X, goal.Y));
if (!HideOutput)
{
ManualResetEvent wait = new ManualResetEvent(false);
ThreadPool.QueueUserWorkItem(new WaitCallback(CreateGUI), new object[] { width, height, self.X, self.Y, goal.X, goal.Y, walls, this, wait });
wait.WaitOne();
}
return new Maze() { width = width, height = height, self = self, goal = goal, walls = walls, wallDensity = wallDensity, opponent = opponent, opponentDifficulty = opponentDifficulty, random = random, maze = maze, start = start, opponents = opponents, bestOpponentPath = bestOpponentPath, score = score };
}
public override Dictionary<QFeature, decimal> GetFeatures(QAction action)
{
Point self = ((Maze)GetNewState(action)).self;
QSearch qsearch = new QSearch(this);
Maze simpleMaze = new Maze() { maze = maze, self = self, goal = goal, width = width, height = height, walls = walls.ToArray() };
QSearchResult bestPath = qsearch.AStar(simpleMaze);
List<Point> bestOppMoves = new List<Point>();
foreach (Point o in opponent)
{
bestOppMoves.Add(o);
bestOppMoves.Add(new Point(o.X + 1, o.Y));
bestOppMoves.Add(new Point(o.X - 1, o.Y));
bestOppMoves.Add(new Point(o.X, o.Y + 1));
bestOppMoves.Add(new Point(o.X, o.Y - 1));
}
foreach (Point o in bestOppMoves.ToArray())
{
bestOppMoves.Add(new Point(o.X + 1, o.Y));
bestOppMoves.Add(new Point(o.X - 1, o.Y));
bestOppMoves.Add(new Point(o.X, o.Y + 1));
bestOppMoves.Add(new Point(o.X, o.Y - 1));
}
Maze safeMaze = new Maze() { maze = maze, self = self, goal = goal, width = width, height = height, walls = walls.Concat(bestOppMoves).ToArray() };
QSearchResult safePath = qsearch.AStar(safeMaze);
Dictionary<string, decimal> features = new Dictionary<string, decimal>() {
//{this.GetHashCode().ToString()+"_"+action, 1}, // Identity to convert this back to QLearning
{"Goal", goal==self? 1:0},
{"Direct_Distance_To_Goal", bestPath==null? 1:(decimal) bestPath.Count / (decimal)(width * height)},
{"Safe_Distance_To_Goal", (safePath==null? 1: (decimal)safePath.Count/ (decimal)(width * height))}
};
decimal distanceToOpponent = decimal.MaxValue;
if (opponent.Any())
{
features["Opponent"] = goal!=self && opponent.Where(p => (Math.Abs(p.X - self.X) <= 1 && p.Y == self.Y) || (Math.Abs(p.Y - self.Y) <= 1 && p.X == self.X)).Any() ? 1 : 0;
distanceToOpponent = opponent.Select(o => qsearch.AStar(new Maze() { maze = maze, self = self, goal = o, width = width, height = height, walls = walls })).Select(x=>x==null? width*height:x.Count).Min();
features["Distance_To_Opponent"] = distanceToOpponent>=5? 1:distanceToOpponent / (decimal)(width * height);
if (goal != self)
{
Maze deadEnd = new Maze() { maze = maze, self = self, goal = goal, width = width, height = height, walls = walls.Concat(new Point[] { new Point(this.self.X - 1, this.self.Y), new Point(this.self.X + 1, this.self.Y), new Point(this.self.X, this.self.Y - 1), new Point(this.self.X, this.self.Y + 1) }).ToArray() };
QSearchResult deadPath = qsearch.Depth_First(deadEnd);
if (deadPath == null)
{
features["Dead_End"] = 1;
}
}
}
return QFeature_String.FromStringDecimalDictionary(features);
}
public override void Step()
{
if (!HideOutput && maze!=null)
{
try
{
maze.SetSelf(self.X, self.Y);
}
catch (Exception e)
{
WriteOutput("" + e, true);
}
}
if (opponent.Any() && goal!=self)
{
for (int i = 0; i < opponent.Count; i++)
{
QState tempState = new Maze() { maze = maze, self = opponent[i], goal = self, width = width, height = height, walls = walls};
QSearchResult opponentPath;
if (bestOpponentPath.ContainsKey(tempState)) opponentPath = bestOpponentPath[tempState];
else
{
opponentPath = new QSearch().AStar(tempState);
bestOpponentPath[tempState] = opponentPath;
}
if (opponentPath!=null && opponentPath.Any())
{
int newX = opponent[i].X, newY = opponent[i].Y;
QAction action = opponentPath.actionsList.First();
if (random.NextDouble() > opponentDifficulty)
{
QAction[] allActions = tempState.GetActions();
action = allActions.ElementAt(random.Next(allActions.Length));
}
// Translate decision to new coordinate
if (action.ToString() == "up") newY--;
else if (action.ToString() == "down") newY++;
else if (action.ToString() == "left") newX--;
else if (action.ToString() == "right") newX++;
//WriteOutput("Moving adversary at " + opponent[i] + " " + action + " to "+newX+", "+newY+"...");
opponent[i] = new Point(newX, newY);
if (!HideOutput && maze!=null)
{
maze.SetOpponent(i, newX, newY);
}
}
}
}
if (goal == self)
{
score += 100;
}
else if (opponent.Contains(self))
{
score -= 100;
}
if (!HideOutput && CurrentMode == AWAKEN) Thread.Sleep(100);
}
public override Dictionary <QFeature, decimal> GetFeatures(QAction action)
{
Point self = ((Maze)GetNewState(action)).self;
QSearch qsearch = new QSearch(this);
Maze simpleMaze = new Maze()
{
maze = maze, self = self, goal = goal, width = width, height = height, walls = walls.ToArray()
};
QSearchResult bestPath = qsearch.AStar(simpleMaze);
List <Point> bestOppMoves = new List <Point>();
foreach (Point o in opponent)
{
bestOppMoves.Add(o);
bestOppMoves.Add(new Point(o.X + 1, o.Y));
bestOppMoves.Add(new Point(o.X - 1, o.Y));
bestOppMoves.Add(new Point(o.X, o.Y + 1));
bestOppMoves.Add(new Point(o.X, o.Y - 1));
}
foreach (Point o in bestOppMoves.ToArray())
{
bestOppMoves.Add(new Point(o.X + 1, o.Y));
bestOppMoves.Add(new Point(o.X - 1, o.Y));
bestOppMoves.Add(new Point(o.X, o.Y + 1));
bestOppMoves.Add(new Point(o.X, o.Y - 1));
}
Maze safeMaze = new Maze()
{
maze = maze, self = self, goal = goal, width = width, height = height, walls = walls.Concat(bestOppMoves).ToArray()
};
QSearchResult safePath = qsearch.AStar(safeMaze);
Dictionary <string, decimal> features = new Dictionary <string, decimal>()
{
//{this.GetHashCode().ToString()+"_"+action, 1}, // Identity to convert this back to QLearning
{ "Goal", goal == self? 1:0 },
{ "Direct_Distance_To_Goal", bestPath == null? 1:(decimal)bestPath.Count / (decimal)(width * height) },
{ "Safe_Distance_To_Goal", (safePath == null? 1: (decimal)safePath.Count / (decimal)(width * height)) }
};
decimal distanceToOpponent = decimal.MaxValue;
if (opponent.Any())
{
features["Opponent"] = goal != self && opponent.Where(p => (Math.Abs(p.X - self.X) <= 1 && p.Y == self.Y) || (Math.Abs(p.Y - self.Y) <= 1 && p.X == self.X)).Any() ? 1 : 0;
distanceToOpponent = opponent.Select(o => qsearch.AStar(new Maze()
{
maze = maze, self = self, goal = o, width = width, height = height, walls = walls
})).Select(x => x == null? width * height:x.Count).Min();
features["Distance_To_Opponent"] = distanceToOpponent >= 5? 1:distanceToOpponent / (decimal)(width * height);
if (goal != self)
{
Maze deadEnd = new Maze()
{
maze = maze, self = self, goal = goal, width = width, height = height, walls = walls.Concat(new Point[] { new Point(this.self.X - 1, this.self.Y), new Point(this.self.X + 1, this.self.Y), new Point(this.self.X, this.self.Y - 1), new Point(this.self.X, this.self.Y + 1) }).ToArray()
};
QSearchResult deadPath = qsearch.Depth_First(deadEnd);
if (deadPath == null)
{
features["Dead_End"] = 1;
}
}
}
return(QFeature_String.FromStringDecimalDictionary(features));
}
public override QState Initialize()
{
WriteOutput("Dimensions: " + width + "x" + height);
self = new Point(start.X, start.Y);
score = 0;
walls = new Point[] { };
// Generate Walls Randomly
if (wallDensity > 0)
{
HashSet <Point> bestPathSoFar = new HashSet <Point>();
WriteOutput("Generating walls randomly with density target of " + wallDensity + "...");
for (int w = 0; w < width; w++)
{
for (int h = 0; h < height; h++)
{
double r = random.NextDouble();
//WriteOutput("Wall Probability for " + w + "x" + h + ": " + r+" vs threshold "+walls);
if (r < wallDensity)
{
//WriteOutput("Wall created at " + w + "x" + h);
Point newWall = new Point(w, h);
if (start == newWall || goal == newWall)
{
continue;
}
Point[] tempWalls = walls.Concat(new Point[] { newWall }).ToArray();
QState tempState = new Maze()
{
maze = maze, self = self, goal = goal, width = width, height = height, walls = tempWalls
};
if (!bestPathSoFar.Any() || bestPathSoFar.Contains(newWall))
{
QSearchResult path = new QSearch().AStar(tempState);
if (path != null)
{
bestPathSoFar.Clear();
foreach (QState q in path.QStatesList)
{
bestPathSoFar.Add(((Maze)q).self);
}
walls = tempWalls;
}
}
else
{
walls = tempWalls;
}
}
}
}
WriteOutput("Maze generation complete.");
}
opponent = new List <Point>();
for (int i = 0; i < opponents; i++)
{
opponent.Add(new Point(goal.X, goal.Y));
}
if (!HideOutput)
{
ManualResetEvent wait = new ManualResetEvent(false);
ThreadPool.QueueUserWorkItem(new WaitCallback(CreateGUI), new object[] { width, height, self.X, self.Y, goal.X, goal.Y, walls, this, wait });
wait.WaitOne();
}
return(new Maze()
{
width = width, height = height, self = self, goal = goal, walls = walls, wallDensity = wallDensity, opponent = opponent, opponentDifficulty = opponentDifficulty, random = random, maze = maze, start = start, opponents = opponents, bestOpponentPath = bestOpponentPath, score = score
});
}
public override void Step()
{
if (!HideOutput && maze != null)
{
try
{
maze.SetSelf(self.X, self.Y);
}
catch (Exception e)
{
WriteOutput("" + e, true);
}
}
if (opponent.Any() && goal != self)
{
for (int i = 0; i < opponent.Count; i++)
{
QState tempState = new Maze()
{
maze = maze, self = opponent[i], goal = self, width = width, height = height, walls = walls
};
QSearchResult opponentPath;
if (bestOpponentPath.ContainsKey(tempState))
{
opponentPath = bestOpponentPath[tempState];
}
else
{
opponentPath = new QSearch().AStar(tempState);
bestOpponentPath[tempState] = opponentPath;
}
if (opponentPath != null && opponentPath.Any())
{
int newX = opponent[i].X, newY = opponent[i].Y;
QAction action = opponentPath.actionsList.First();
if (random.NextDouble() > opponentDifficulty)
{
QAction[] allActions = tempState.GetActions();
action = allActions.ElementAt(random.Next(allActions.Length));
}
// Translate decision to new coordinate
if (action.ToString() == "up")
{
newY--;
}
else if (action.ToString() == "down")
{
newY++;
}
else if (action.ToString() == "left")
{
newX--;
}
else if (action.ToString() == "right")
{
newX++;
}
//WriteOutput("Moving adversary at " + opponent[i] + " " + action + " to "+newX+", "+newY+"...");
opponent[i] = new Point(newX, newY);
if (!HideOutput && maze != null)
{
maze.SetOpponent(i, newX, newY);
}
}
}
}
if (goal == self)
{
score += 100;
}
else if (opponent.Contains(self))
{
score -= 100;
}
if (!HideOutput && CurrentMode == AWAKEN)
{
Thread.Sleep(100);
}
}
