Probability pattern ditionary: Expect patterns ordered from least used to most used
[pachi.git] / uct / dynkomi.c
blob01958eec23763e5ab0ed7447566f39b48f0805e1
1 #define DEBUG
2 #include <assert.h>
3 #include <math.h>
4 #include <stdio.h>
5 #include <stdlib.h>
6 #include <string.h>
8 #include "board.h"
9 #include "debug.h"
10 #include "tactics/util.h"
11 #include "uct/dynkomi.h"
12 #include "uct/internal.h"
13 #include "uct/tree.h"
16 static void
17 generic_done(struct uct_dynkomi *d)
19 if (d->data) free(d->data);
20 free(d);
24 /* NONE dynkomi strategy - never fiddle with komi values. */
26 struct uct_dynkomi *
27 uct_dynkomi_init_none(struct uct *u, char *arg, struct board *b)
29 struct uct_dynkomi *d = calloc2(1, sizeof(*d));
30 d->uct = u;
31 d->permove = NULL;
32 d->persim = NULL;
33 d->done = generic_done;
34 d->data = NULL;
36 if (arg) {
37 fprintf(stderr, "uct: Dynkomi method none accepts no arguments\n");
38 exit(1);
41 return d;
45 /* LINEAR dynkomi strategy - Linearly Decreasing Handicap Compensation. */
46 /* At move 0, we impose extra komi of handicap_count*handicap_value, then
47 * we linearly decrease this extra komi throughout the game down to 0
48 * at @moves moves. Towards the end of the game the linear compensation
49 * becomes zero but we increase the extra komi when winning big. This reduces
50 * the number of point-wasting moves and makes the game more enjoyable for humans. */
52 struct dynkomi_linear {
53 int handicap_value[S_MAX];
54 int moves[S_MAX];
55 bool rootbased;
56 /* Increase the extra komi if my win ratio > green_zone but always
57 * keep extra_komi <= komi_ratchet. komi_ratchet starts infinite but decreases
58 * when we give too much extra komi and this puts us back < orange_zone.
59 * This is meant only to increase the territory margin when playing against
60 * weaker opponents. We never take negative komi when losing. The ratchet helps
61 * avoiding oscillations and keeping us above orange_zone.
62 * To disable the adaptive phase, set green_zone=2. */
63 floating_t komi_ratchet;
64 floating_t green_zone;
65 floating_t orange_zone;
66 floating_t drop_step;
69 static floating_t
70 linear_permove(struct uct_dynkomi *d, struct board *b, struct tree *tree)
72 struct dynkomi_linear *l = d->data;
73 enum stone color = d->uct->pondering ? tree->root_color : stone_other(tree->root_color);
74 int lmoves = l->moves[color];
75 floating_t extra_komi;
77 if (b->moves < lmoves) {
78 floating_t base_komi = board_effective_handicap(b, l->handicap_value[color]);
79 extra_komi = base_komi * (lmoves - b->moves) / lmoves;
80 return extra_komi;
81 } else {
82 extra_komi = floor(tree->extra_komi);
85 /* Do not take decisions on unstable value. */
86 if (tree->root->u.playouts < GJ_MINGAMES) return extra_komi;
88 floating_t my_value = tree_node_get_value(tree, 1, tree->root->u.value);
89 /* We normalize komi as in komi_by_value(), > 0 when winning. */
90 extra_komi = komi_by_color(extra_komi, color);
91 assert(extra_komi >= 0);
92 floating_t orig_komi = extra_komi;
94 if (my_value < 0.5 && l->komi_ratchet > 0 && l->komi_ratchet != INFINITY) {
95 if (DEBUGL(0))
96 fprintf(stderr, "losing %f extra %.1f ratchet %.1f -> 0\n",
97 my_value, extra_komi, l->komi_ratchet);
98 /* Disable dynkomi completely, too dangerous in this game. */
99 extra_komi = l->komi_ratchet = 0;
101 } else if (my_value < l->orange_zone && extra_komi > 0) {
102 extra_komi = l->komi_ratchet = fmax(extra_komi - l->drop_step, 0.0);
103 if (extra_komi != orig_komi && DEBUGL(3))
104 fprintf(stderr, "dropping to %f ratchet -> %.1f\n",
105 my_value, extra_komi);
107 } else if (my_value > l->green_zone && extra_komi +1 <= l->komi_ratchet) {
108 extra_komi += 1;
109 if (extra_komi != orig_komi && DEBUGL(3))
110 fprintf(stderr, "winning %f extra_komi -> %.1f, ratchet %.1f\n",
111 my_value, extra_komi, l->komi_ratchet);
113 return komi_by_color(extra_komi, color);
116 static floating_t
117 linear_persim(struct uct_dynkomi *d, struct board *b, struct tree *tree, struct tree_node *node)
119 struct dynkomi_linear *l = d->data;
120 if (l->rootbased)
121 return tree->extra_komi;
122 /* We don't reuse computed value from tree->extra_komi,
123 * since we want to use value correct for this node depth.
124 * This also means the values will stay correct after
125 * node promotion. */
126 return linear_permove(d, b, tree);
129 struct uct_dynkomi *
130 uct_dynkomi_init_linear(struct uct *u, char *arg, struct board *b)
132 struct uct_dynkomi *d = calloc2(1, sizeof(*d));
133 d->uct = u;
134 d->permove = linear_permove;
135 d->persim = linear_persim;
136 d->done = generic_done;
138 struct dynkomi_linear *l = calloc2(1, sizeof(*l));
139 d->data = l;
141 /* Force white to feel behind and try harder, but not to the
142 * point of resigning immediately in high handicap games.
143 * By move 100 white should still be behind but should have
144 * caught up enough to avoid resigning. */
145 if (board_large(b)) {
146 l->moves[S_BLACK] = 100;
147 l->moves[S_WHITE] = 50;
149 /* The real value of one stone is twice the komi so about 15 points.
150 * But use a lower value to avoid being too pessimistic as black
151 * or too optimistic as white. */
152 l->handicap_value[S_BLACK] = 8;
153 l->handicap_value[S_WHITE] = 1;
155 l->komi_ratchet = INFINITY;
156 l->green_zone = 0.85;
157 l->orange_zone = 0.8;
158 l->drop_step = 4.0;
160 if (arg) {
161 char *optspec, *next = arg;
162 while (*next) {
163 optspec = next;
164 next += strcspn(next, ":");
165 if (*next) { *next++ = 0; } else { *next = 0; }
167 char *optname = optspec;
168 char *optval = strchr(optspec, '=');
169 if (optval) *optval++ = 0;
171 if (!strcasecmp(optname, "moves") && optval) {
172 /* Dynamic komi in handicap game; linearly
173 * decreases to basic settings until move
174 * #optval. moves=blackmoves%whitemoves */
175 for (int i = S_BLACK; *optval && i <= S_WHITE; i++) {
176 l->moves[i] = atoi(optval);
177 optval += strcspn(optval, "%");
178 if (*optval) optval++;
180 } else if (!strcasecmp(optname, "handicap_value") && optval) {
181 /* Point value of single handicap stone,
182 * for dynkomi computation. */
183 for (int i = S_BLACK; *optval && i <= S_WHITE; i++) {
184 l->handicap_value[i] = atoi(optval);
185 optval += strcspn(optval, "%");
186 if (*optval) optval++;
188 } else if (!strcasecmp(optname, "rootbased")) {
189 /* If set, the extra komi applied will be
190 * the same for all simulations within a move,
191 * instead of being same for all simulations
192 * within the tree node. */
193 l->rootbased = !optval || atoi(optval);
194 } else if (!strcasecmp(optname, "green_zone") && optval) {
195 /* Increase komi when win ratio is above green_zone */
196 l->green_zone = atof(optval);
197 } else if (!strcasecmp(optname, "orange_zone") && optval) {
198 /* Decrease komi when > 0 and win ratio is below orange_zone */
199 l->orange_zone = atof(optval);
200 } else if (!strcasecmp(optname, "drop_step") && optval) {
201 /* Decrease komi by drop_step points */
202 l->drop_step = atof(optval);
203 } else {
204 fprintf(stderr, "uct: Invalid dynkomi argument %s or missing value\n", optname);
205 exit(1);
210 return d;
214 /* ADAPTIVE dynkomi strategy - Adaptive Situational Compensation */
215 /* We adapt the komi based on current situation:
216 * (i) score-based: We maintain the average score outcome of our
217 * games and adjust the komi by a fractional step towards the expected
218 * score;
219 * (ii) value-based: While winrate is above given threshold, adjust
220 * the komi by a fixed step in the appropriate direction.
221 * These adjustments can be
222 * (a) Move-stepped, new extra komi value is always set only at the
223 * beginning of the tree search for next move;
224 * (b) Continuous, new extra komi value is periodically re-determined
225 * and adjusted throughout a single tree search. */
227 struct dynkomi_adaptive {
228 /* Do not take measured average score into regard for
229 * first @lead_moves - the variance is just too much.
230 * (Instead, we consider the handicap-based komi provided
231 * by linear dynkomi.) */
232 int lead_moves;
233 /* Maximum komi to pretend the opponent to give. */
234 floating_t max_losing_komi;
235 /* Game portion at which losing komi is not allowed anymore. */
236 floating_t losing_komi_stop;
237 /* Alternative game portion determination. */
238 bool adapt_aport;
239 floating_t (*indicator)(struct uct_dynkomi *d, struct board *b, struct tree *tree, enum stone color);
241 /* Value-based adaptation. */
242 floating_t zone_red, zone_green;
243 int score_step;
244 floating_t score_step_byavg; // use portion of average score as increment
245 bool use_komi_ratchet;
246 bool losing_komi_ratchet; // ratchet even losing komi
247 int komi_ratchet_maxage;
248 // runtime, not configuration:
249 int komi_ratchet_age;
250 floating_t komi_ratchet;
252 /* Score-based adaptation. */
253 floating_t (*adapter)(struct uct_dynkomi *d, struct board *b);
254 floating_t adapt_base; // [0,1)
255 /* Sigmoid adaptation rate parameter; see below for details. */
256 floating_t adapt_phase; // [0,1]
257 floating_t adapt_rate; // [1,infty)
258 /* Linear adaptation rate parameter. */
259 int adapt_moves;
260 floating_t adapt_dir; // [-1,1]
262 #define TRUSTWORTHY_KOMI_PLAYOUTS 200
264 static floating_t
265 board_game_portion(struct dynkomi_adaptive *a, struct board *b)
267 if (!a->adapt_aport) {
268 int total_moves = b->moves + 2 * board_estimated_moves_left(b);
269 return (floating_t) b->moves / total_moves;
270 } else {
271 int brsize = board_size(b) - 2;
272 return 1.0 - (floating_t) b->flen / (brsize * brsize);
276 static floating_t
277 adapter_sigmoid(struct uct_dynkomi *d, struct board *b)
279 struct dynkomi_adaptive *a = d->data;
280 /* Figure out how much to adjust the komi based on the game
281 * stage. The adaptation rate is 0 at the beginning,
282 * at game stage a->adapt_phase crosses though 0.5 and
283 * approaches 1 at the game end; the slope is controlled
284 * by a->adapt_rate. */
285 floating_t game_portion = board_game_portion(a, b);
286 floating_t l = game_portion - a->adapt_phase;
287 return 1.0 / (1.0 + exp(-a->adapt_rate * l));
290 static floating_t
291 adapter_linear(struct uct_dynkomi *d, struct board *b)
293 struct dynkomi_adaptive *a = d->data;
294 /* Figure out how much to adjust the komi based on the game
295 * stage. We just linearly increase/decrease the adaptation
296 * rate for first N moves. */
297 if (b->moves > a->adapt_moves)
298 return 0;
299 if (a->adapt_dir < 0)
300 return 1 - (- a->adapt_dir) * b->moves / a->adapt_moves;
301 else
302 return a->adapt_dir * b->moves / a->adapt_moves;
305 static floating_t
306 komi_by_score(struct uct_dynkomi *d, struct board *b, struct tree *tree, enum stone color)
308 struct dynkomi_adaptive *a = d->data;
309 if (d->score.playouts < TRUSTWORTHY_KOMI_PLAYOUTS)
310 return tree->extra_komi;
312 struct move_stats score = d->score;
313 /* Almost-reset tree->score to gather fresh stats. */
314 d->score.playouts = 1;
316 /* Look at average score and push extra_komi in that direction. */
317 floating_t p = a->adapter(d, b);
318 p = a->adapt_base + p * (1 - a->adapt_base);
319 if (p > 0.9) p = 0.9; // don't get too eager!
320 floating_t extra_komi = tree->extra_komi + p * score.value;
321 if (DEBUGL(3))
322 fprintf(stderr, "mC += %f * %f\n", p, score.value);
323 return extra_komi;
326 static floating_t
327 komi_by_value(struct uct_dynkomi *d, struct board *b, struct tree *tree, enum stone color)
329 struct dynkomi_adaptive *a = d->data;
330 if (d->value.playouts < TRUSTWORTHY_KOMI_PLAYOUTS)
331 return tree->extra_komi;
333 struct move_stats value = d->value;
334 /* Almost-reset tree->value to gather fresh stats. */
335 d->value.playouts = 1;
336 /* Correct color POV. */
337 if (color == S_WHITE)
338 value.value = 1 - value.value;
340 /* We have three "value zones":
341 * red zone | yellow zone | green zone
342 * ~45% ~60%
343 * red zone: reduce komi
344 * yellow zone: do not touch komi
345 * green zone: enlage komi.
347 * Also, at some point komi will be tuned in such way
348 * that it will be in green zone but increasing it will
349 * be unfeasible. Thus, we have a _ratchet_ - we will
350 * remember the last komi that has put us into the
351 * red zone, and not use it or go over it. We use the
352 * ratchet only when giving extra komi, we always want
353 * to try to reduce extra komi we take.
355 * TODO: Make the ratchet expire after a while. */
357 /* We use komi_by_color() first to normalize komi
358 * additions/subtractions, then apply it again on
359 * return value to restore original komi parity. */
360 /* Positive extra_komi means that we are _giving_
361 * komi (winning), negative extra_komi is _taking_
362 * komi (losing). */
363 floating_t extra_komi = komi_by_color(tree->extra_komi, color);
364 int score_step_red = -a->score_step;
365 int score_step_green = a->score_step;
367 if (a->score_step_byavg != 0) {
368 struct move_stats score = d->score;
369 /* Almost-reset tree->score to gather fresh stats. */
370 d->score.playouts = 1;
371 /* Correct color POV. */
372 if (color == S_WHITE)
373 score.value = - score.value;
374 if (score.value > 0)
375 score_step_green = round(score.value * a->score_step_byavg);
376 else
377 score_step_red = round(-score.value * a->score_step_byavg);
378 if (score_step_green < 0 || score_step_red > 0) {
379 /* The steps are in bad direction - keep still. */
380 return komi_by_color(extra_komi, color);
384 /* Wear out the ratchet. */
385 if (a->use_komi_ratchet && a->komi_ratchet_maxage > 0) {
386 a->komi_ratchet_age += value.playouts;
387 if (a->komi_ratchet_age > a->komi_ratchet_maxage) {
388 a->komi_ratchet = 1000;
389 a->komi_ratchet_age = 0;
393 if (value.value < a->zone_red) {
394 /* Red zone. Take extra komi. */
395 if (DEBUGL(3))
396 fprintf(stderr, "[red] %f, step %d | komi ratchet %f age %d/%d -> %f\n",
397 value.value, score_step_red, a->komi_ratchet, a->komi_ratchet_age, a->komi_ratchet_maxage, extra_komi);
398 if (a->losing_komi_ratchet || extra_komi > 0) {
399 a->komi_ratchet = extra_komi;
400 a->komi_ratchet_age = 0;
402 extra_komi += score_step_red;
403 return komi_by_color(extra_komi, color);
405 } else if (value.value < a->zone_green) {
406 /* Yellow zone, do nothing. */
407 return komi_by_color(extra_komi, color);
409 } else {
410 /* Green zone. Give extra komi. */
411 if (DEBUGL(3))
412 fprintf(stderr, "[green] %f, step %d | komi ratchet %f age %d/%d\n",
413 value.value, score_step_green, a->komi_ratchet, a->komi_ratchet_age, a->komi_ratchet_maxage);
414 extra_komi += score_step_green;
415 if (a->use_komi_ratchet && extra_komi >= a->komi_ratchet)
416 extra_komi = a->komi_ratchet - 1;
417 return komi_by_color(extra_komi, color);
421 static floating_t
422 bounded_komi(struct dynkomi_adaptive *a, struct board *b,
423 enum stone color, floating_t komi, floating_t max_losing_komi)
425 /* At the end of game, disallow losing komi. */
426 if (komi_by_color(komi, color) < 0
427 && board_game_portion(a, b) > a->losing_komi_stop)
428 return 0;
430 /* Get lower bound on komi we take so that we don't underperform
431 * too much. */
432 floating_t min_komi = komi_by_color(- max_losing_komi, color);
434 if (komi_by_color(komi - min_komi, color) > 0)
435 return komi;
436 else
437 return min_komi;
440 static floating_t
441 adaptive_permove(struct uct_dynkomi *d, struct board *b, struct tree *tree)
443 /* We do not use extra komi at the game end - we are not
444 * to fool ourselves at this point. */
445 if (board_estimated_moves_left(b) <= MIN_MOVES_LEFT) {
446 tree->use_extra_komi = false;
447 return 0;
449 struct dynkomi_adaptive *a = d->data;
450 enum stone color = stone_other(tree->root_color);
451 if (DEBUGL(3))
452 fprintf(stderr, "m %d/%d ekomi %f permove %f/%d\n",
453 b->moves, a->lead_moves, tree->extra_komi,
454 d->score.value, d->score.playouts);
456 if (b->moves <= a->lead_moves)
457 return bounded_komi(a, b, color,
458 board_effective_handicap(b, 7 /* XXX */),
459 a->max_losing_komi);
461 floating_t komi = a->indicator(d, b, tree, color);
462 if (DEBUGL(3))
463 fprintf(stderr, "dynkomi: %f -> %f\n", tree->extra_komi, komi);
464 return bounded_komi(a, b, color, komi, a->max_losing_komi);
467 static floating_t
468 adaptive_persim(struct uct_dynkomi *d, struct board *b, struct tree *tree, struct tree_node *node)
470 return tree->extra_komi;
473 struct uct_dynkomi *
474 uct_dynkomi_init_adaptive(struct uct *u, char *arg, struct board *b)
476 struct uct_dynkomi *d = calloc2(1, sizeof(*d));
477 d->uct = u;
478 d->permove = adaptive_permove;
479 d->persim = adaptive_persim;
480 d->done = generic_done;
482 struct dynkomi_adaptive *a = calloc2(1, sizeof(*a));
483 d->data = a;
485 a->lead_moves = board_large(b) ? 20 : 4; // XXX
486 a->max_losing_komi = 30;
487 a->losing_komi_stop = 1.0f;
488 a->indicator = komi_by_value;
490 a->adapter = adapter_sigmoid;
491 a->adapt_rate = -18;
492 a->adapt_phase = 0.65;
493 a->adapt_moves = 200;
494 a->adapt_dir = -0.5;
496 a->zone_red = 0.45;
497 a->zone_green = 0.50;
498 a->score_step = 1;
499 a->use_komi_ratchet = true;
500 a->komi_ratchet_maxage = 0;
501 a->komi_ratchet = 1000;
503 if (arg) {
504 char *optspec, *next = arg;
505 while (*next) {
506 optspec = next;
507 next += strcspn(next, ":");
508 if (*next) { *next++ = 0; } else { *next = 0; }
510 char *optname = optspec;
511 char *optval = strchr(optspec, '=');
512 if (optval) *optval++ = 0;
514 if (!strcasecmp(optname, "lead_moves") && optval) {
515 /* Do not adjust komi adaptively for first
516 * N moves. */
517 a->lead_moves = atoi(optval);
518 } else if (!strcasecmp(optname, "max_losing_komi") && optval) {
519 a->max_losing_komi = atof(optval);
520 } else if (!strcasecmp(optname, "losing_komi_stop") && optval) {
521 a->losing_komi_stop = atof(optval);
522 } else if (!strcasecmp(optname, "indicator")) {
523 /* Adaptatation indicator - how to decide
524 * the adaptation rate and direction. */
525 if (!strcasecmp(optval, "value")) {
526 /* Winrate w/ komi so far. */
527 a->indicator = komi_by_value;
528 } else if (!strcasecmp(optval, "score")) {
529 /* Expected score w/ current komi. */
530 a->indicator = komi_by_score;
531 } else {
532 fprintf(stderr, "UCT: Invalid indicator %s\n", optval);
533 exit(1);
536 /* value indicator settings */
537 } else if (!strcasecmp(optname, "zone_red") && optval) {
538 a->zone_red = atof(optval);
539 } else if (!strcasecmp(optname, "zone_green") && optval) {
540 a->zone_green = atof(optval);
541 } else if (!strcasecmp(optname, "score_step") && optval) {
542 a->score_step = atoi(optval);
543 } else if (!strcasecmp(optname, "score_step_byavg") && optval) {
544 a->score_step_byavg = atof(optval);
545 } else if (!strcasecmp(optname, "use_komi_ratchet")) {
546 a->use_komi_ratchet = !optval || atoi(optval);
547 } else if (!strcasecmp(optname, "losing_komi_ratchet")) {
548 a->losing_komi_ratchet = !optval || atoi(optval);
549 } else if (!strcasecmp(optname, "komi_ratchet_age") && optval) {
550 a->komi_ratchet_maxage = atoi(optval);
552 /* score indicator settings */
553 } else if (!strcasecmp(optname, "adapter") && optval) {
554 /* Adaptatation method. */
555 if (!strcasecmp(optval, "sigmoid")) {
556 a->adapter = adapter_sigmoid;
557 } else if (!strcasecmp(optval, "linear")) {
558 a->adapter = adapter_linear;
559 } else {
560 fprintf(stderr, "UCT: Invalid adapter %s\n", optval);
561 exit(1);
563 } else if (!strcasecmp(optname, "adapt_base") && optval) {
564 /* Adaptation base rate; see above. */
565 a->adapt_base = atof(optval);
566 } else if (!strcasecmp(optname, "adapt_rate") && optval) {
567 /* Adaptation slope; see above. */
568 a->adapt_rate = atof(optval);
569 } else if (!strcasecmp(optname, "adapt_phase") && optval) {
570 /* Adaptation phase shift; see above. */
571 a->adapt_phase = atof(optval);
572 } else if (!strcasecmp(optname, "adapt_moves") && optval) {
573 /* Adaptation move amount; see above. */
574 a->adapt_moves = atoi(optval);
575 } else if (!strcasecmp(optname, "adapt_aport")) {
576 a->adapt_aport = !optval || atoi(optval);
577 } else if (!strcasecmp(optname, "adapt_dir") && optval) {
578 /* Adaptation direction vector; see above. */
579 a->adapt_dir = atof(optval);
581 } else {
582 fprintf(stderr, "uct: Invalid dynkomi argument %s or missing value\n", optname);
583 exit(1);
588 return d;