Moggy: Remove old, dusty and ineffective assess_local
[pachi.git] / uct / dynkomi.c
blob1e1a9d5dc461256256853736f8a35f235ab1fffd
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. */
50 struct dynkomi_linear {
51 int handicap_value;
52 int moves;
53 bool rootbased;
56 static float
57 linear_permove(struct uct_dynkomi *d, struct board *b, struct tree *tree)
59 struct dynkomi_linear *l = d->data;
60 if (b->moves >= l->moves)
61 return 0;
63 float base_komi = board_effective_handicap(b, l->handicap_value);
64 float extra_komi = base_komi * (l->moves - b->moves) / l->moves;
65 return extra_komi;
68 static float
69 linear_persim(struct uct_dynkomi *d, struct board *b, struct tree *tree, struct tree_node *node)
71 struct dynkomi_linear *l = d->data;
72 if (l->rootbased)
73 return tree->extra_komi;
74 /* We don't reuse computed value from tree->extra_komi,
75 * since we want to use value correct for this node depth.
76 * This also means the values will stay correct after
77 * node promotion. */
78 return linear_permove(d, b, tree);
81 struct uct_dynkomi *
82 uct_dynkomi_init_linear(struct uct *u, char *arg, struct board *b)
84 struct uct_dynkomi *d = calloc2(1, sizeof(*d));
85 d->uct = u;
86 d->permove = linear_permove;
87 d->persim = linear_persim;
88 d->done = generic_done;
90 struct dynkomi_linear *l = calloc2(1, sizeof(*l));
91 d->data = l;
93 if (board_size(b) - 2 >= 19)
94 l->moves = 200;
95 l->handicap_value = 7;
97 if (arg) {
98 char *optspec, *next = arg;
99 while (*next) {
100 optspec = next;
101 next += strcspn(next, ":");
102 if (*next) { *next++ = 0; } else { *next = 0; }
104 char *optname = optspec;
105 char *optval = strchr(optspec, '=');
106 if (optval) *optval++ = 0;
108 if (!strcasecmp(optname, "moves") && optval) {
109 /* Dynamic komi in handicap game; linearly
110 * decreases to basic settings until move
111 * #optval. */
112 l->moves = atoi(optval);
113 } else if (!strcasecmp(optname, "handicap_value") && optval) {
114 /* Point value of single handicap stone,
115 * for dynkomi computation. */
116 l->handicap_value = atoi(optval);
117 } else if (!strcasecmp(optname, "rootbased")) {
118 /* If set, the extra komi applied will be
119 * the same for all simulations within a move,
120 * instead of being same for all simulations
121 * within the tree node. */
122 l->rootbased = !optval || atoi(optval);
123 } else {
124 fprintf(stderr, "uct: Invalid dynkomi argument %s or missing value\n", optname);
125 exit(1);
130 return d;
134 /* ADAPTIVE dynkomi strategy - Adaptive Situational Compensation */
135 /* We adapt the komi based on current situation:
136 * (i) score-based: We maintain the average score outcome of our
137 * games and adjust the komi by a fractional step towards the expected
138 * score;
139 * (ii) value-based: While winrate is above given threshold, adjust
140 * the komi by a fixed step in the appropriate direction.
141 * These adjustments can be
142 * (a) Move-stepped, new extra komi value is always set only at the
143 * beginning of the tree search for next move;
144 * (b) Continuous, new extra komi value is periodically re-determined
145 * and adjusted throughout a single tree search. */
147 struct dynkomi_adaptive {
148 /* Do not take measured average score into regard for
149 * first @lead_moves - the variance is just too much.
150 * (Instead, we consider the handicap-based komi provided
151 * by linear dynkomi.) */
152 int lead_moves;
153 /* Maximum komi to pretend the opponent to give. */
154 float max_losing_komi;
155 /* Game portion at which losing komi is not allowed anymore. */
156 float losing_komi_stop;
157 /* Alternative game portion determination. */
158 bool adapt_aport;
159 float (*indicator)(struct uct_dynkomi *d, struct board *b, struct tree *tree, enum stone color);
161 /* Value-based adaptation. */
162 float zone_red, zone_green;
163 int score_step;
164 float score_step_byavg; // use portion of average score as increment
165 bool use_komi_ratchet;
166 bool losing_komi_ratchet; // ratchet even losing komi
167 int komi_ratchet_maxage;
168 // runtime, not configuration:
169 int komi_ratchet_age;
170 float komi_ratchet;
172 /* Score-based adaptation. */
173 float (*adapter)(struct uct_dynkomi *d, struct board *b);
174 float adapt_base; // [0,1)
175 /* Sigmoid adaptation rate parameter; see below for details. */
176 float adapt_phase; // [0,1]
177 float adapt_rate; // [1,infty)
178 /* Linear adaptation rate parameter. */
179 int adapt_moves;
180 float adapt_dir; // [-1,1]
182 #define TRUSTWORTHY_KOMI_PLAYOUTS 200
184 static float
185 board_game_portion(struct dynkomi_adaptive *a, struct board *b)
187 if (!a->adapt_aport) {
188 int total_moves = b->moves + 2 * board_estimated_moves_left(b);
189 return (float) b->moves / total_moves;
190 } else {
191 int brsize = board_size(b) - 2;
192 return 1.0 - (float) b->flen / (brsize * brsize);
196 static float
197 adapter_sigmoid(struct uct_dynkomi *d, struct board *b)
199 struct dynkomi_adaptive *a = d->data;
200 /* Figure out how much to adjust the komi based on the game
201 * stage. The adaptation rate is 0 at the beginning,
202 * at game stage a->adapt_phase crosses though 0.5 and
203 * approaches 1 at the game end; the slope is controlled
204 * by a->adapt_rate. */
205 float game_portion = board_game_portion(a, b);
206 float l = game_portion - a->adapt_phase;
207 return 1.0 / (1.0 + exp(-a->adapt_rate * l));
210 static float
211 adapter_linear(struct uct_dynkomi *d, struct board *b)
213 struct dynkomi_adaptive *a = d->data;
214 /* Figure out how much to adjust the komi based on the game
215 * stage. We just linearly increase/decrease the adaptation
216 * rate for first N moves. */
217 if (b->moves > a->adapt_moves)
218 return 0;
219 if (a->adapt_dir < 0)
220 return 1 - (- a->adapt_dir) * b->moves / a->adapt_moves;
221 else
222 return a->adapt_dir * b->moves / a->adapt_moves;
225 static float
226 komi_by_score(struct uct_dynkomi *d, struct board *b, struct tree *tree, enum stone color)
228 struct dynkomi_adaptive *a = d->data;
229 if (d->score.playouts < TRUSTWORTHY_KOMI_PLAYOUTS)
230 return tree->extra_komi;
232 struct move_stats score = d->score;
233 /* Almost-reset tree->score to gather fresh stats. */
234 d->score.playouts = 1;
236 /* Look at average score and push extra_komi in that direction. */
237 float p = a->adapter(d, b);
238 p = a->adapt_base + p * (1 - a->adapt_base);
239 if (p > 0.9) p = 0.9; // don't get too eager!
240 float extra_komi = tree->extra_komi + p * score.value;
241 if (DEBUGL(3))
242 fprintf(stderr, "mC += %f * %f\n", p, score.value);
243 return extra_komi;
246 static float
247 komi_by_value(struct uct_dynkomi *d, struct board *b, struct tree *tree, enum stone color)
249 struct dynkomi_adaptive *a = d->data;
250 if (d->value.playouts < TRUSTWORTHY_KOMI_PLAYOUTS)
251 return tree->extra_komi;
253 struct move_stats value = d->value;
254 /* Almost-reset tree->value to gather fresh stats. */
255 d->value.playouts = 1;
256 /* Correct color POV. */
257 if (color == S_WHITE)
258 value.value = 1 - value.value;
260 /* We have three "value zones":
261 * red zone | yellow zone | green zone
262 * ~45% ~60%
263 * red zone: reduce komi
264 * yellow zone: do not touch komi
265 * green zone: enlage komi.
267 * Also, at some point komi will be tuned in such way
268 * that it will be in green zone but increasing it will
269 * be unfeasible. Thus, we have a _ratchet_ - we will
270 * remember the last komi that has put us into the
271 * red zone, and not use it or go over it. We use the
272 * ratchet only when giving extra komi, we always want
273 * to try to reduce extra komi we take.
275 * TODO: Make the ratchet expire after a while. */
277 /* We use komi_by_color() first to normalize komi
278 * additions/subtractions, then apply it again on
279 * return value to restore original komi parity. */
280 /* Positive extra_komi means that we are _giving_
281 * komi (winning), negative extra_komi is _taking_
282 * komi (losing). */
283 float extra_komi = komi_by_color(tree->extra_komi, color);
284 int score_step_red = -a->score_step;
285 int score_step_green = a->score_step;
287 if (a->score_step_byavg != 0) {
288 struct move_stats score = d->score;
289 /* Almost-reset tree->score to gather fresh stats. */
290 d->score.playouts = 1;
291 /* Correct color POV. */
292 if (color == S_WHITE)
293 score.value = - score.value;
294 if (score.value > 0)
295 score_step_green = round(score.value * a->score_step_byavg);
296 else
297 score_step_red = round(-score.value * a->score_step_byavg);
298 if (score_step_green < 0 || score_step_red > 0) {
299 /* The steps are in bad direction - keep still. */
300 return komi_by_color(extra_komi, color);
304 /* Wear out the ratchet. */
305 if (a->use_komi_ratchet && a->komi_ratchet_maxage > 0) {
306 a->komi_ratchet_age += value.playouts;
307 if (a->komi_ratchet_age > a->komi_ratchet_maxage) {
308 a->komi_ratchet = 1000;
309 a->komi_ratchet_age = 0;
313 if (value.value < a->zone_red) {
314 /* Red zone. Take extra komi. */
315 if (DEBUGL(3))
316 fprintf(stderr, "[red] %f, step %d | komi ratchet %f age %d/%d -> %f\n",
317 value.value, score_step_red, a->komi_ratchet, a->komi_ratchet_age, a->komi_ratchet_maxage, extra_komi);
318 if (a->losing_komi_ratchet || extra_komi > 0) {
319 a->komi_ratchet = extra_komi;
320 a->komi_ratchet_age = 0;
322 extra_komi += score_step_red;
323 return komi_by_color(extra_komi, color);
325 } else if (value.value < a->zone_green) {
326 /* Yellow zone, do nothing. */
327 return komi_by_color(extra_komi, color);
329 } else {
330 /* Green zone. Give extra komi. */
331 if (DEBUGL(3))
332 fprintf(stderr, "[green] %f, step %d | komi ratchet %f age %d/%d\n",
333 value.value, score_step_green, a->komi_ratchet, a->komi_ratchet_age, a->komi_ratchet_maxage);
334 extra_komi += score_step_green;
335 if (a->use_komi_ratchet && extra_komi >= a->komi_ratchet)
336 extra_komi = a->komi_ratchet - 1;
337 return komi_by_color(extra_komi, color);
341 static float
342 bounded_komi(struct dynkomi_adaptive *a, struct board *b,
343 enum stone color, float komi, float max_losing_komi)
345 /* At the end of game, disallow losing komi. */
346 if (komi_by_color(komi, color) < 0
347 && board_game_portion(a, b) > a->losing_komi_stop)
348 return 0;
350 /* Get lower bound on komi we take so that we don't underperform
351 * too much. */
352 float min_komi = komi_by_color(- max_losing_komi, color);
354 if (komi_by_color(komi - min_komi, color) > 0)
355 return komi;
356 else
357 return min_komi;
360 static float
361 adaptive_permove(struct uct_dynkomi *d, struct board *b, struct tree *tree)
363 struct dynkomi_adaptive *a = d->data;
364 enum stone color = stone_other(tree->root_color);
365 if (DEBUGL(3))
366 fprintf(stderr, "m %d/%d ekomi %f permove %f/%d\n",
367 b->moves, a->lead_moves, tree->extra_komi,
368 d->score.value, d->score.playouts);
370 if (b->moves <= a->lead_moves)
371 return bounded_komi(a, b, color,
372 board_effective_handicap(b, 7 /* XXX */),
373 a->max_losing_komi);
375 float komi = a->indicator(d, b, tree, color);
376 if (DEBUGL(3))
377 fprintf(stderr, "dynkomi: %f -> %f\n", tree->extra_komi, komi);
378 return bounded_komi(a, b, color, komi, a->max_losing_komi);
381 static float
382 adaptive_persim(struct uct_dynkomi *d, struct board *b, struct tree *tree, struct tree_node *node)
384 return tree->extra_komi;
387 struct uct_dynkomi *
388 uct_dynkomi_init_adaptive(struct uct *u, char *arg, struct board *b)
390 struct uct_dynkomi *d = calloc2(1, sizeof(*d));
391 d->uct = u;
392 d->permove = adaptive_permove;
393 d->persim = adaptive_persim;
394 d->done = generic_done;
396 struct dynkomi_adaptive *a = calloc2(1, sizeof(*a));
397 d->data = a;
399 if (board_size(b) - 2 >= 19)
400 a->lead_moves = 20;
401 else
402 a->lead_moves = 4; // XXX
403 a->max_losing_komi = 30;
404 a->losing_komi_stop = 1.0f;
405 a->indicator = komi_by_value;
407 a->adapter = adapter_sigmoid;
408 a->adapt_rate = -18;
409 a->adapt_phase = 0.65;
410 a->adapt_moves = 200;
411 a->adapt_dir = -0.5;
413 a->zone_red = 0.45;
414 a->zone_green = 0.50;
415 a->score_step = 1;
416 a->use_komi_ratchet = true;
417 a->komi_ratchet_maxage = 0;
418 a->komi_ratchet = 1000;
420 if (arg) {
421 char *optspec, *next = arg;
422 while (*next) {
423 optspec = next;
424 next += strcspn(next, ":");
425 if (*next) { *next++ = 0; } else { *next = 0; }
427 char *optname = optspec;
428 char *optval = strchr(optspec, '=');
429 if (optval) *optval++ = 0;
431 if (!strcasecmp(optname, "lead_moves") && optval) {
432 /* Do not adjust komi adaptively for first
433 * N moves. */
434 a->lead_moves = atoi(optval);
435 } else if (!strcasecmp(optname, "max_losing_komi") && optval) {
436 a->max_losing_komi = atof(optval);
437 } else if (!strcasecmp(optname, "losing_komi_stop") && optval) {
438 a->losing_komi_stop = atof(optval);
439 } else if (!strcasecmp(optname, "indicator")) {
440 /* Adaptatation indicator - how to decide
441 * the adaptation rate and direction. */
442 if (!strcasecmp(optval, "value")) {
443 /* Winrate w/ komi so far. */
444 a->indicator = komi_by_value;
445 } else if (!strcasecmp(optval, "score")) {
446 /* Expected score w/ current komi. */
447 a->indicator = komi_by_score;
448 } else {
449 fprintf(stderr, "UCT: Invalid indicator %s\n", optval);
450 exit(1);
453 /* value indicator settings */
454 } else if (!strcasecmp(optname, "zone_red") && optval) {
455 a->zone_red = atof(optval);
456 } else if (!strcasecmp(optname, "zone_green") && optval) {
457 a->zone_green = atof(optval);
458 } else if (!strcasecmp(optname, "score_step") && optval) {
459 a->score_step = atoi(optval);
460 } else if (!strcasecmp(optname, "score_step_byavg") && optval) {
461 a->score_step_byavg = atof(optval);
462 } else if (!strcasecmp(optname, "use_komi_ratchet")) {
463 a->use_komi_ratchet = !optval || atoi(optval);
464 } else if (!strcasecmp(optname, "losing_komi_ratchet")) {
465 a->losing_komi_ratchet = !optval || atoi(optval);
466 } else if (!strcasecmp(optname, "komi_ratchet_age") && optval) {
467 a->komi_ratchet_maxage = atoi(optval);
469 /* score indicator settings */
470 } else if (!strcasecmp(optname, "adapter") && optval) {
471 /* Adaptatation method. */
472 if (!strcasecmp(optval, "sigmoid")) {
473 a->adapter = adapter_sigmoid;
474 } else if (!strcasecmp(optval, "linear")) {
475 a->adapter = adapter_linear;
476 } else {
477 fprintf(stderr, "UCT: Invalid adapter %s\n", optval);
478 exit(1);
480 } else if (!strcasecmp(optname, "adapt_base") && optval) {
481 /* Adaptation base rate; see above. */
482 a->adapt_base = atof(optval);
483 } else if (!strcasecmp(optname, "adapt_rate") && optval) {
484 /* Adaptation slope; see above. */
485 a->adapt_rate = atof(optval);
486 } else if (!strcasecmp(optname, "adapt_phase") && optval) {
487 /* Adaptation phase shift; see above. */
488 a->adapt_phase = atof(optval);
489 } else if (!strcasecmp(optname, "adapt_moves") && optval) {
490 /* Adaptation move amount; see above. */
491 a->adapt_moves = atoi(optval);
492 } else if (!strcasecmp(optname, "adapt_aport")) {
493 a->adapt_aport = !optval || atoi(optval);
494 } else if (!strcasecmp(optname, "adapt_dir") && optval) {
495 /* Adaptation direction vector; see above. */
496 a->adapt_dir = atof(optval);
498 } else {
499 fprintf(stderr, "uct: Invalid dynkomi argument %s or missing value\n", optname);
500 exit(1);
505 return d;