public MCTree(GameState game)
{
GameState state = game.DeepCopy();
root = new MCNode(true, state);
Expand(root);
}
public MCNode(bool turn, GameState game, MCNode parentNode = null)
{
parent = parentNode;
player = turn;
state = game.DeepCopy();
wins = plays = 0;
}
void deleteParents(MCNode newRoot)
{
if (newRoot.parent.parent != null)
{
deleteParents(newRoot.parent);
}
newRoot.parent = null;
return;
}
public bool changeRoot(GameState newState)
{
foreach (MCNode c in root.children)
{
if (c.state.Board == newState.Board)
{
root = c;
deleteParents(root);
return(true);
}
}
return(false);
}
//recursively updates each node from the leaf to the root the success or failure of a given path
void backProp(MCNode node, bool winner)
{
while (node.parent != null)
{
if (winner)
{
node.wins = node.wins + 1;
}
node.plays++;
return;
}
return;
}
//uses above functions to perform an n-play MTCS
public string MCTS(int n)
{
for (int i = 0; i < n; i++)
{
MCNode chosen = Selection();
Expand(chosen);
bool result = simulate(chosen);
backProp(chosen, result);
}
float maxWins = 0F;
int winIndex = 0;
float maxPlays = 0;
var ai = new TakAI_V4(root.state.Size, maxDepth: 0);
var evaluator = ai.Evaluator;
bool gameOver;
int eval;
//chooses highest win rate (or winning move if available)
for (int i = 0; i < root.children.Count; i++)
{
evaluator.Evaluate(root.children[i].state, out eval, out gameOver);
if (gameOver)
{
return(root.legalMoves[i].Notate());
}
if (root.children[i].winRate() > maxWins)
{
if (root.children[i].plays > maxPlays)
{
maxPlays = root.children[i].plays;
}
maxWins = root.children[i].wins;
winIndex = i;
}
}
return(root.legalMoves[winIndex].Notate());
}
//performs MCTS selection step (do not call if an available move is a win state)
MCNode Selection()
{
var ai = new TakAI_V4(root.state.Size, maxDepth: 0);
var evaluator = ai.Evaluator;
//random selection for testing purposes
Random r = new Random();
int index = r.Next(root.children.Count);
MCNode iterator = root.children[index];
List <MCNode> iteratorChildren = iterator.children;
//looks for unexpanded node
while (iterator.children.Count > 0)
{
bool gameOver;
int eval; //irrelivant, only exists to call evaluate function to look for gameover states
//random
int iteratorIndex = r.Next(iteratorChildren.Count);
//avoid repeating pre-evaluated win states
evaluator.Evaluate(iteratorChildren[iteratorIndex].state, out eval, out gameOver);
if (!gameOver)
{
iterator = iteratorChildren[iteratorIndex];
iteratorChildren = iterator.children;
}
else
{
//avoids using the same value twice
iteratorChildren.RemoveAt(iteratorIndex);
}
}
return(iterator);
}
//enumerates all available moves at a given node
void Expand(MCNode leaf)
{
var ai = new TakAI_V4(root.state.Size, maxDepth: 4);
var evaluator = ai.Evaluator;
List <IMove> moves = moveOptions(leaf.state);
TakEngine.Notation.MoveNotation notated;
foreach (var m in moves)
{
GameState tempState = leaf.state.DeepCopy();
TakEngine.Notation.MoveNotation.TryParse(m.Notate(), out notated);
var match = notated.MatchLegalMove(moves);
match.MakeMove(tempState);
tempState.Ply++;
leaf.children.Add(new MCNode(!leaf.player, tempState, leaf));
leaf.legalMoves.Add(m);
evaluator.Evaluate(leaf.children[leaf.children.Count - 1].state, out eval, out gameOver);
if (gameOver)
{
backProp(leaf.children[leaf.children.Count - 1], !leaf.player);
}
}
}
public float evaluate(MCNode node)
{
float positionValue = 0;
int flatCount = 0;
int highestCap = 0;
int maxCap = 0, maxCapEnemy = 0;
int losingState = 0;
//Set coefficient values here for ease of parameter tuning
float flatCo = 1F;
float capCo = 5F;
float lossCo = 1000F;
//check if position is one move away from an enemy win state
List <IMove> moves = moveOptions(node.state);
var ai = new TakAI_V4(root.state.Size, maxDepth: 0);
var evaluator = ai.Evaluator;
bool gameOver;
int eval;
TakEngine.Notation.MoveNotation notated;
GameState state = node.state.DeepCopy();
foreach (var m in moves)
{
TakEngine.Notation.MoveNotation.TryParse(m.Notate(), out notated);
var match = notated.MatchLegalMove(moves);
match.MakeMove(state);
state.Ply++;
evaluator.Evaluate(state, out eval, out gameOver);
if (gameOver)
{
losingState = 1;
}
m.TakeBackMove(state);
}
//count the number of flat stones
for (int i = 0; i < node.state.Size; i++)
{
for (int j = 0; j < node.state.Size; j++)
{
if (node.state.Board[i, j].Count > 0)
{
var piece = node.state.Board[i, j][node.state.Board[i, j].Count - 1];
if (Piece.GetStone(piece) == Piece.Stone_Flat)
{
if ((Piece.GetPlayerID(piece) == 1 && !node.player) || (Piece.GetPlayerID(piece) == 0 && node.player))
{
flatCount++;
}
else
{
//Account for enemy flat stones, making the heuristic a differential rather than a simple count
flatCount--;
}
}
//check for highest capstone
if (Piece.GetStone(piece) == Piece.Stone_Cap)
{
if (Piece.GetPlayerID(piece) == 1 && !node.player)
{
maxCapEnemy = node.state.Board[i, j].Count;
}
else if (Piece.GetPlayerID(piece) == 0 && node.player)
{
maxCap = node.state.Board[i, j].Count;
}
}
}
}
}
//check which (if either) player has the highest capstone
if (maxCap > maxCapEnemy)
{
highestCap = 1;
}
else if (maxCap < maxCapEnemy)
{
highestCap = -1;
}
positionValue = flatCount * flatCo + highestCap * capCo + losingState * lossCo;
return(positionValue);
}
bool simulate(MCNode start)
{
int eval = 0;
bool gameOver;
var ai = new TakAI_V4(start.state.Size, maxDepth: 3);
var evaluator = ai.Evaluator;
List <IMove> moves = moveOptions(start.state);
Expand(start);
//check for end of game
evaluator.Evaluate(start.state, out eval, out gameOver);
if (gameOver)
{
return(!start.player);
}
List <float> evaluations = new List <float>();
//random play
for (int i = 0; i < moves.Count; i++)
{
MCNode m = start.children[i];
float f = evaluate(m);
//Console.WriteLine(f);
if (f >= 0F)
{
evaluations.Add(f);
}
}
if (evaluations.Count == 0)
{
return(false);
}
float sum = evaluations.Sum();
Random r = new Random();
double selectValue = r.NextDouble();
float selection = 0F;
int moveIndex = 0;
while (selection < selectValue)
{
//Console.WriteLine(evaluations.Count.ToString() + "," + moveIndex.ToString());
selection += evaluations[moveIndex] / sum;
moveIndex++;
}
MCNode tempNode = new MCNode(!start.player, start.state.DeepCopy());
TakEngine.Notation.MoveNotation notated;
//Console.WriteLine(moveIndex.ToString() + "," + evaluations.Count.ToString() + "," + moves.Count.ToString());
TakEngine.Notation.MoveNotation.TryParse(moves[moveIndex - 1].Notate(), out notated);
var match = notated.MatchLegalMove(moves);
match.MakeMove(tempNode.state);
tempNode.state.Ply++;
return(simulate(tempNode));
}