path: root/include/ct1986.c

#include "ct1986.h"

// ===================================================================
// Globals
// ===================================================================

const float infty = 3.0;
char ct1986_ptn[9];
void (*ct1986_display_progress)(const uint8_t);

// ===================================================================
// Implementation of a small convolutional neural network
// ===================================================================

static float flattened[CONV_NUM+2];
static float dense1[DENSE1_NUM];
static float dense2[DENSE2_NUM];

#ifndef DETERMINISTIC
static uint32_t x = 1;
#define DOXORSHIFT { x ^= x << 13; x ^= x >> 17; x ^= x << 5; }
#define FUDGE (((float)(x&255))/255.0-0.5)*0.2
#endif

#define RELU(x) ((x) = ((x)<0)?0:(x))

float
ct1986_evaluate_black_win(void) {
	/* ------------------ *
	 *  Convolution layer *
	 * ------------------ */
	// for each kernel
	for (uint8_t kern = 0; kern < KERN_NUM; kern++) {
		// the stride is 1, march across the board
		for (uint8_t bx = 0; bx < KERN_OSIZE; bx++) {
			for (uint8_t by = 0; by < KERN_OSIZE; by++) {
				flattened[kern+KERN_NUM*(bx+by*KERN_OSIZE)] =
					conv2d_biases[kern];
				// Compute the convolution for this position
				for (uint8_t ky = 0; ky < KERN_SIZE; ky++) {
					for (uint8_t kx = 0; kx < KERN_SIZE; kx++) {
						for (uint8_t c = 0; c < KERN_CHAN; c++) {
							// Where we are on the board
							const uint8_t loc = kx+by+(ky+bx)*board_size;
							// Look up what's on the board at this location, and
							// multiply it. For c=0 we have to do some extra work
							float lookup = 0;
							if (COUNT_AT(loc)>c) {
								if (c==0) {
									if (STONE_AT(loc) == STONE_STANDING) {
										lookup = (colours[loc] & 1) ? +0.25 : -0.25;
									} else if (STONE_AT(loc) == STONE_CAPSTONE) {
										lookup = (colours[loc] & 1) ? +1.00 : -1.00;
									} else {
										lookup = (colours[loc] & 1) ? +0.50 : -0.50;
									}
								} else {
									lookup = (colours[loc] & (1<<c)) ? +0.50 : -0.50;
								}
							}
							flattened[kern+KERN_NUM*(bx+by*KERN_OSIZE)]
								+= lookup*conv2d_weights[kern][ky][kx][c];
						}
					}
				}
				RELU(flattened[kern+KERN_NUM*(bx+by*KERN_OSIZE)]);
			}
		}
	}
	// Add input of flat counts
	flattened[CONV_NUM]   = (float)(white_count & 127)/21.0;
	flattened[CONV_NUM+1] = (float)(black_count & 127)/21.0;
	/* ------------------ *
	 *  First dense layer *
	 * ------------------ */
	for (uint8_t d1 = 0; d1 < DENSE1_NUM; d1++) {
		dense1[d1] = dense1_biases[d1];
		for (uint8_t fl = 0; fl < CONV_NUM+2; fl++) {
			dense1[d1] += flattened[fl]*dense1_weights[d1][fl];
		}
		RELU(dense1[d1]);
	}
	/* ------------------- *
	 *  Second dense layer *
	 * ------------------- */
	for (uint8_t d2 = 0; d2 < DENSE2_NUM; d2++) {
		dense2[d2] = dense2_biases[d2];
		for (uint8_t d1 = 0; d1 < DENSE1_NUM; d1++) {
			dense2[d2] += dense1[d1]*dense2_weights[d2][d1];
		}
		RELU(dense2[d2]);
	}
	/* ------------- *
	 *  Output layer *
	 * ------------- */
	float output = output_bias;
	for (uint8_t d2 = 0; d2 < DENSE2_NUM; d2++) {
		output += dense2[d2]*output_weights[d2];
	}
	// Truncated Pade approximant of logistic function
	output = (12.0+output+50.0*output/(output*output+10.0))/24.0;
#ifndef DETERMINISTIC
	DOXORSHIFT;
	output += FUDGE;
#endif
	if (output > 1.0) return 1.0;
	else if (output < 0.0) return 0.0;

	return output;
}

// ===================================================================
// Minimax using the above evaluator
// ===================================================================

static void
previous_ply(void) {
	if (ply>0) ply--;
	if (ply == 1) {
		current_colour = C_WHITE;
	} else {
		if (current_colour == C_BLACK) current_colour = C_WHITE;
		else current_colour = C_BLACK;
	}
}

/*
 * static inline int
 * win_evaluate_or_recurse(const uint8_t cur_depth,
 *												const uint8_t max_depth, const uint8_t min,
 *												float* alpha, float* beta, float *optimal) {
 *	float this;
 *	enum WIN_TYPE w = 0xFF;
 */

static float val;
static enum WIN_TYPE w;

#define WIN_EVALUATE_OR_RECURSE(store) { \
	w = 0xFF; \
	if (ply >= 2*board_size - 2) w = check_win();  \
	if (w < 0xFF) { \
		/* Somebody won, assign weights accordingly */ \
		if (min == 0) { \
			if (w == WIN_ROAD_BLACK || w == WIN_FLAT_BLACK) \
				val = infty; \
			else val = -infty; \
		} else { \
			if (w == WIN_ROAD_WHITE || w == WIN_FLAT_WHITE) \
				val = -infty; \
			else val = infty; \
		} \
	} else if (cur_depth == max_depth) { \
		/* We're at the bottom, evaluate */ \
		val = ct1986_evaluate_black_win(); \
		if ((ply & 1) == 0) val = val - 1.0; \
	} else { \
		/* We're not at the bottom, recurse first */ \
		next_ply(); \
		val = ct1986_minimax(cur_depth + 1, max_depth, 1-min, alpha, beta); \
		previous_ply(); \
	} \
	/* Update the optimal value */ \
	if (((min > 0) && (val < optimal)) \
			|| ((min == 0) && (val > optimal))) { \
		optimal = val; \
		if (cur_depth == 0) (store); \
	} \
	/* Update alpha and beta */ \
	if (min) { \
		if (optimal < beta) beta = optimal; \
	} else { \
		if (optimal > alpha) alpha = optimal; \
	} \
}

float
ct1986_minimax(const uint8_t cur_depth, const uint8_t max_depth,
							 const uint8_t min, float alpha, float beta) {

	enum E_RESULT r;
	const uint8_t white_count_backup = white_count,
		black_count_backup = black_count;

	// 1.0 is a `certain' black win, -1.0 is a `certain' white win.
	float optimal = (min) ? infty : -infty;

	// Step across the board
	for (uint8_t row = 0; row < 5; row++) {
		for (uint8_t col = 0; col < 5; col++) {
			// Try all valid actions for this square. Is it empty?
			const uint8_t loc = THE_COORDS(col, row);
			const uint8_t count = COUNT_AT(loc);
			// Only try moves after CPS
			if (count && ((colours[loc] & 1) == current_colour) && ply>2) {
				// There are stones, can we move them in a given direction?
				// I'm not a huge fan of looping through enums, but it's
				// better than manually unrolling this. Sufficiently smart
				// compilers?

				uint16_t colours_backup[5];
				uint8_t celldat_backup[5], drops[5-1];
				// Back up the row of the board
				for (uint8_t y = 0; y < 5; y++) {
					colours_backup[y] = colours[THE_COORDS(col, y)];
					celldat_backup[y] = celldat[THE_COORDS(col, y)];
				}
				for (enum MOVE_DIRECTION dir = M_UP; dir <= M_RIGHT; dir++) {
					// Back-up the column once we start looking horizontally
					if (dir == M_LEFT) {
						for (uint8_t x = 0; x < 5; x++) {
							colours_backup[x] = colours[THE_COORDS(x, row)];
							celldat_backup[x] = celldat[THE_COORDS(x, row)];
						}
					}
					// We don't do anything terribly efficient or smart here,
					// just try everything...

					// For every number of steps
					for (uint8_t steps = 1; steps < 5 && steps <= count; steps++) {
						uint8_t idx, carry;
						for (idx = 0; idx < steps; idx++) drops[idx]=0;
						idx = 0;
						while (idx < steps) {
							// Increment the drop sequence
							carry = 0;
							drops[idx]++;
							do {
								if (carry) { drops[++idx]++; carry = 0;}
								if (drops[idx] > count || drops[idx] > 5) {
									drops[idx] = 1; carry = 1;
								}
							} while (carry && idx < steps);
							// If carry is still set here we're done
							if (carry == 0) {
								// Try it, and note that try_move will never return
								// GAME_END. It does not check for winners, but we do
								// manually.
								r = try_move(loc, dir, steps, drops);
								if (r == ACT_OK) {
									// First check for wins, if we're at the bottom
									// evaluate, otherwise recurse
									WIN_EVALUATE_OR_RECURSE({
											// If we did update the optimal value, store
											// this move
											generate_move(loc, dir, steps, drops, ct1986_ptn);
										});
									// Reset the board data
									if (dir <= M_DOWN) {
										for (uint8_t y = 0; y < 5; y++) {
											colours[THE_COORDS(col, y)] = colours_backup[y];
											celldat[THE_COORDS(col, y)] = celldat_backup[y];
										}
									} else {
										for (uint8_t x = 0; x < 5; x++) {
											colours[THE_COORDS(x, row)] = colours_backup[x];
											celldat[THE_COORDS(x, row)] = celldat_backup[x];
										}
									}
								}
								// Prune
								if (alpha >= beta) return optimal;
							}
						}
					}
				}
			} else if (count == 0) {
				// Empty square, try the three placements. Again, looping
				// through enums, sigh.
				for (enum STONE_VARIANT stone = STONE_FLAT;
						 stone <= STONE_CAPSTONE; stone++) {
					// try_place will never check for winning, and we don't do
					// that either here
					r = try_place(loc, current_colour, stone);
					// Legal placement, evaluate it
					if (r == ACT_OK) {
						// First check for wins, if we're at the bottom
						// evaluate, otherwise recurse
						WIN_EVALUATE_OR_RECURSE({
								// If we did update the optimal value, store
								// this move
								generate_place(loc, stone, ct1986_ptn);
							});
						// Reset the state
						celldat[loc] = 0;
						white_count = white_count_backup;
						black_count = black_count_backup;
						// Prune
						if (alpha >= beta) return optimal;
					}
				}
			}
			ct1986_display_progress(cur_depth);
		}
	}
	return optimal;
}

inline float
ct1986_generate(const uint8_t max_depth) {
	return ct1986_minimax(0, max_depth, (ply & 1) ? 0 : 1, -infty, infty);
}