コード例 #1
0
ファイル: zle_params.c プロジェクト: psych0tik/zsh
static void
set_rbuffer(UNUSED(Param pm), char *x)
{
    ZLE_STRING_T y;
    int len;

    if (x && *x != ZWC('\0'))
	y = stringaszleline(x, 0, &len, NULL, NULL);
    else
	y = ZWS(""), len = 0;
    sizeline(zlell = zlecs + len);
    ZS_memcpy(zleline + zlecs, y, len);
    zsfree(x);
    if (len)
	free(y);
    fixsuffix();
    menucmp = 0;
}
コード例 #2
0
ファイル: game.cpp プロジェクト: PanicSheep/Cassandra
int PVS(const uint64_t P, const uint64_t O, uint64_t& NodeCounter, const int alpha, const int beta, const int selectivity, const int depth, const int empties, CLine* pline)
{
	assert((P & O) == 0);
	assert(-64 <= alpha); assert(alpha <= 64);
	assert(-64 <= beta ); assert(beta  <= 64);
	assert(alpha <= beta);
	assert(0 <= depth); assert(depth <= 60);
	assert(0 <= empties); assert(empties <= 60); assert(empties == Empties(P, O));
	assert(depth <= empties);
	
	if (depth <= 2 && depth < empties) {
		if (depth == 2) return Midgame::PVS_2(P, O, NodeCounter, alpha, beta, pline);
		if (depth == 1) return Midgame::PVS_1(P, O, NodeCounter, alpha, beta, pline);
		if (depth == 0) return Midgame::Eval_0(P, O, NodeCounter);
	}
	if (empties <= A && depth == empties) return Endgame::PVS_A(P, O, NodeCounter, alpha, beta, empties, pline);

	int lower = alpha;
	int score;
	int bestscore = -65;
	uint8_t BestMove = 64;
	uint64_t BitBoardPossible = PossibleMoves(P, O);
	uint64_t LocalNodeCounter = NodeCounter;
	CHashTableValueType ttValue;
	NodeCounter++;

	if (!BitBoardPossible){
		if (HasMoves(O, P))
			return -PVS(O, P, NodeCounter, -beta, -alpha, selectivity, depth, empties, pline);
		else {
			if (pline) pline->NoMoves();
			return EvalGameOver(P, empties);
		}
	}

	if (!pline && StabilityCutoff_PVS(P, O, alpha, score)) return score;
	if (LookUpTTPV(P, O, ttValue) || LookUpTT(P, O, ttValue))
		if (USE_PV_TTCUT && !pline && UseTTValue(ttValue, alpha, beta, depth, selectivity, score))
			return score;
	if (USE_IID && ttValue.PV == 64) // IID
	{
		int reduced_depth = (depth == empties) ? depth - A : depth - 2;
		if (reduced_depth >= 3)
		{
			PVS(P, O, NodeCounter, -64, 64, 6, reduced_depth, empties, nullptr);
			if (LookUpTTPV(P, O, ttValue))
				if (USE_PV_TTCUT && !pline && UseTTValue(ttValue, alpha, beta, depth, selectivity, score))
					return score;
		}
	}

	CLine * line = nullptr;
	if (pline && pline->size) line = new CLine(pline->size-1);
	CMoveList mvList(P, O, NodeCounter, BitBoardPossible, depth, alpha, ttValue, true);
	for (const auto& mv : mvList)
	{
		if (bestscore == -65)
			score = -PVS(mv.P, mv.O, NodeCounter, -beta, -lower, selectivity, depth-1, empties-1, line);
		else
		{
			score = -ZWS(mv.P, mv.O, NodeCounter, -lower-1, selectivity, depth-1, empties-1);
			if (score > lower && score < beta)
				score = -PVS(mv.P, mv.O, NodeCounter, -beta, -lower, selectivity, depth-1, empties-1, line); // OPTIMIZATION: -lower -> -score
		}
		if (score > bestscore)
		{
			bestscore = score;
			BestMove = mv.move;
			if (line) pline->NewPV(mv.move, line);
			if (score >= beta) break;
			if (score > lower) lower = score;
		}
	}
	
	if (empties-1 <= B)
	{
		UpdateTTPV(P, O, NodeCounter - LocalNodeCounter, alpha, beta, bestscore, depth, NO_SELECTIVITY, BestMove, mvList.BestMove(), mvList.NextBestMove());
		UpdateTT(P, O, NodeCounter - LocalNodeCounter, alpha, beta, bestscore, depth, NO_SELECTIVITY, BestMove, mvList.BestMove(), mvList.NextBestMove());
	}
	else
	{
		UpdateTTPV(P, O, NodeCounter - LocalNodeCounter, alpha, beta, bestscore, depth, selectivity, BestMove, mvList.BestMove(), mvList.NextBestMove());
		UpdateTT(P, O, NodeCounter - LocalNodeCounter, alpha, beta, bestscore, depth, selectivity, BestMove, mvList.BestMove(), mvList.NextBestMove());
	}
	delete line;
	return bestscore;
}
コード例 #3
0
ファイル: game.cpp プロジェクト: PanicSheep/Cassandra
int ZWS(const uint64_t P, const uint64_t O, uint64_t& NodeCounter, const int alpha, const int selectivity, const int depth, const int empties)
{
	assert((P & O) == 0);
	assert(-64 <= alpha); assert(alpha <= 64);
	assert(0 <= depth); assert(depth <= 60);
	assert(0 <= empties); assert(empties <= 60); assert(empties == Empties(P, O));
	assert(depth <= empties);
	
	if (depth <= 3 && depth < empties) {
		if (depth == 3) return Midgame::ZWS_3(P, O, NodeCounter, alpha);
		if (depth == 2) return Midgame::ZWS_2(P, O, NodeCounter, alpha);
		if (depth == 1) return Midgame::ZWS_1(P, O, NodeCounter, alpha);
		if (depth == 0) return Midgame::Eval_0(P, O, NodeCounter);
	}
	if (empties <= B && depth == empties) return Endgame::ZWS_B(P, O, NodeCounter, alpha, empties);

	int score;
	int bestscore = -64;
	uint8_t BestMove = 64;
	uint64_t BitBoardPossible = PossibleMoves(P, O);
	uint64_t LocalNodeCounter = NodeCounter;
	CHashTableValueType ttValue;
	NodeCounter++;

	if (!BitBoardPossible){
		if (HasMoves(O, P))
			return -ZWS(O, P, NodeCounter, -alpha - 1, selectivity, depth, empties);
		else
			return EvalGameOver(P, empties);
	}

	if (StabilityCutoff_ZWS(P, O, alpha, score)) return score;
	if (LookUpTT(P, O, ttValue) && UseTTValue(ttValue, alpha, alpha+1, depth, selectivity, score)) return score;
	if (MPC(P, O, NodeCounter, alpha, selectivity, depth, empties, score)) return score;
		
	CMoveList mvList(P, O, NodeCounter, BitBoardPossible, depth, alpha, ttValue, false);
	for (const auto& mv : mvList) // ETC
	{
		if (StabilityCutoff_ZWS(mv.P, mv.O, -alpha - 1, score)) {
			UpdateTT(P, O, 0, alpha, alpha + 1, -score, depth, NO_SELECTIVITY, mv.move, mvList.BestMove(), mvList.NextBestMove());
			return -score;
		}
		if (LookUpTT(mv.P, mv.O, ttValue) && UseTTValue(ttValue, -alpha - 1, -alpha, depth - 1, selectivity, score) && (-score > alpha)) {
			UpdateTT(P, O, 0, alpha, alpha+1, -score, depth, selectivity, mv.move, mvList.BestMove(), mvList.NextBestMove());
			return -score;
		}
	}
	for (const auto& mv : mvList)
	{
		score = -ZWS(mv.P, mv.O, NodeCounter, -alpha-1, selectivity, depth-1, empties-1);
		if (score > bestscore)
		{
			bestscore = score;
			BestMove = mv.move;
			if (score > alpha) break;
		}
	}
	
	if (empties-1 <= B)
		UpdateTT(P, O, NodeCounter-LocalNodeCounter, alpha, alpha+1, bestscore, depth, NO_SELECTIVITY, BestMove, mvList.BestMove(), mvList.NextBestMove());
	else
		UpdateTT(P, O, NodeCounter-LocalNodeCounter, alpha, alpha+1, bestscore, depth, selectivity, BestMove, mvList.BestMove(), mvList.NextBestMove());
	return bestscore;
}
コード例 #4
0
ファイル: game.cpp プロジェクト: PanicSheep/Cassandra
bool MPC(uint64_t P, uint64_t O, uint64_t& NodeCounter, int alpha, int selectivity, int depth, int empties, int& value)
{
	assert((P & O) == 0);
	assert(-64 <= alpha); assert(alpha <= 64);
	assert(0 <= depth); assert(depth <= 60);
	assert(0 <= empties); assert(empties <= 60); assert(empties == Empties(P, O));
	assert(depth <= empties);

	if (selectivity)
	{
		const int beta = alpha + 1;
		const double t = SelectivityTable[selectivity].T;
		const int zero_eval = Midgame::Eval_0(P, O, NodeCounter);
		double probcut_sigma = sigma(depth, 0, empties);
		int probcut_beta = beta + t * probcut_sigma;
		int probcut_alpha = probcut_beta - 1;

		if (empties <= 21)
		{
			if (zero_eval >= beta + t * probcut_sigma) { value = beta; return true; }
			if (zero_eval < alpha - t * probcut_sigma) { value = alpha; return true; }
		}

		probcut_sigma = sigma(depth, (depth % 2 == 0 ? 2 : 1), empties);

		if (zero_eval >= beta + t * probcut_sigma)
		{
			for (int probcut_depth = (depth % 2 == 0 ? 2 : 1)+2; probcut_depth <= depth / 2; probcut_depth += 2)
			{
				double probcut_sigma = sigma(depth, probcut_depth, empties);
				int probcut_beta = beta + t * probcut_sigma;
				int probcut_alpha = probcut_beta - 1;
				if (probcut_beta <= 64)
				{
					int score = ZWS(P, O, NodeCounter, probcut_alpha, NO_SELECTIVITY, probcut_depth, empties);
					if (score >= probcut_beta) { value = beta; return true; }
				}
			}
		}
		if (zero_eval < alpha - t * probcut_sigma)
		{
			for (int probcut_depth = (depth % 2 == 0 ? 2 : 1)+2; probcut_depth <= depth / 2; probcut_depth += 2)
			{
				int probcut_sigma = sigma(depth, probcut_depth, empties);
				int probcut_alpha = alpha - t * probcut_sigma;
				if (probcut_alpha >= -64)
				{
					int score = ZWS(P, O, NodeCounter, probcut_alpha, NO_SELECTIVITY, probcut_depth, empties);
					if (score <= probcut_alpha) { value = alpha; return true; }
				}
			}
		}

		//for (int probcut_depth = depth % 2 ? 1 : 2; probcut_depth <= depth / 2; probcut_depth++)
		//{
		//	double probcut_sigma = sigma(depth, probcut_depth, empties);
		//	int probcut_beta = RoundInt(beta + t * probcut_sigma);
		//	int probcut_alpha = probcut_beta - 1;
		//	int score;

		//	if (zero_eval >= beta && probcut_beta <= 64)
		//	{
		//		score = ZWS(P, O, NodeCounter, probcut_alpha, NO_SELECTIVITY, probcut_depth, empties);
		//		if (score >= probcut_beta) { value = beta; return true; }
		//	}

		//	probcut_alpha = RoundInt(alpha - t * probcut_sigma);
		//	if (zero_eval < alpha && probcut_alpha >= -64)
		//	{
		//		score = ZWS(P, O, NodeCounter, probcut_alpha, NO_SELECTIVITY, probcut_depth, empties);
		//		if (score <= probcut_alpha) { value = alpha; return true; }
		//	}
		//}
	}
	return false;
}