Merge branch 'master' of git+ssh://repo.or.cz/srv/git/pachi
[pachi/derm.git] / uct / dynkomi.c
blobe6e4152361bccff393ae4e8d4031c9bc144f3837
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.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 float (*indicator)(struct uct_dynkomi *d, struct board *b, struct tree *tree, enum stone color);
157 /* Value-based adaptation. */
158 float zone_red, zone_green;
159 int score_step;
160 float score_step_byavg; // use portion of average score as increment
161 bool use_komi_ratchet;
162 int komi_ratchet_maxage;
163 // runtime, not configuration:
164 int komi_ratchet_age;
165 float komi_ratchet;
167 /* Score-based adaptation. */
168 float (*adapter)(struct uct_dynkomi *d, struct board *b);
169 float adapt_base; // [0,1)
170 /* Sigmoid adaptation rate parameter; see below for details. */
171 float adapt_phase; // [0,1]
172 float adapt_rate; // [1,infty)
173 bool adapt_aport; // alternative game portion determination
174 /* Linear adaptation rate parameter. */
175 int adapt_moves;
176 float adapt_dir; // [-1,1]
178 #define TRUSTWORTHY_KOMI_PLAYOUTS 200
180 static float
181 adapter_sigmoid(struct uct_dynkomi *d, struct board *b)
183 struct dynkomi_adaptive *a = d->data;
184 /* Figure out how much to adjust the komi based on the game
185 * stage. The adaptation rate is 0 at the beginning,
186 * at game stage a->adapt_phase crosses though 0.5 and
187 * approaches 1 at the game end; the slope is controlled
188 * by a->adapt_rate. */
189 float game_portion;
190 if (!a->adapt_aport) {
191 int total_moves = b->moves + 2 * board_estimated_moves_left(b);
192 game_portion = (float) b->moves / total_moves;
193 } else {
194 int brsize = board_size(b) - 2;
195 game_portion = 1.0 - (float) b->flen / (brsize * brsize);
197 float l = game_portion - a->adapt_phase;
198 return 1.0 / (1.0 + exp(-a->adapt_rate * l));
201 static float
202 adapter_linear(struct uct_dynkomi *d, struct board *b)
204 struct dynkomi_adaptive *a = d->data;
205 /* Figure out how much to adjust the komi based on the game
206 * stage. We just linearly increase/decrease the adaptation
207 * rate for first N moves. */
208 if (b->moves > a->adapt_moves)
209 return 0;
210 if (a->adapt_dir < 0)
211 return 1 - (- a->adapt_dir) * b->moves / a->adapt_moves;
212 else
213 return a->adapt_dir * b->moves / a->adapt_moves;
216 static float
217 komi_by_score(struct uct_dynkomi *d, struct board *b, struct tree *tree, enum stone color)
219 struct dynkomi_adaptive *a = d->data;
220 if (d->score.playouts < TRUSTWORTHY_KOMI_PLAYOUTS)
221 return tree->extra_komi;
223 struct move_stats score = d->score;
224 /* Almost-reset tree->score to gather fresh stats. */
225 d->score.playouts = 1;
227 /* Look at average score and push extra_komi in that direction. */
228 float p = a->adapter(d, b);
229 p = a->adapt_base + p * (1 - a->adapt_base);
230 if (p > 0.9) p = 0.9; // don't get too eager!
231 float extra_komi = tree->extra_komi + p * score.value;
232 if (DEBUGL(3))
233 fprintf(stderr, "mC += %f * %f\n", p, score.value);
234 return extra_komi;
237 static float
238 komi_by_value(struct uct_dynkomi *d, struct board *b, struct tree *tree, enum stone color)
240 struct dynkomi_adaptive *a = d->data;
241 if (d->value.playouts < TRUSTWORTHY_KOMI_PLAYOUTS)
242 return tree->extra_komi;
244 struct move_stats value = d->value;
245 /* Almost-reset tree->value to gather fresh stats. */
246 d->value.playouts = 1;
247 /* Correct color POV. */
248 if (color == S_WHITE)
249 value.value = 1 - value.value;
251 /* We have three "value zones":
252 * red zone | yellow zone | green zone
253 * ~45% ~60%
254 * red zone: reduce komi
255 * yellow zone: do not touch komi
256 * green zone: enlage komi.
258 * Also, at some point komi will be tuned in such way
259 * that it will be in green zone but increasing it will
260 * be unfeasible. Thus, we have a _ratchet_ - we will
261 * remember the last komi that has put us into the
262 * red zone, and not use it or go over it. We use the
263 * ratchet only when giving extra komi, we always want
264 * to try to reduce extra komi we take.
266 * TODO: Make the ratchet expire after a while. */
267 /* We use komi_by_color() first to normalize komi
268 * additions/subtractions, then apply it again on
269 * return value to restore original komi parity. */
270 float extra_komi = komi_by_color(tree->extra_komi, color);
271 int score_step = a->score_step;
273 if (a->score_step_byavg != 0) {
274 struct move_stats score = d->score;
275 /* Almost-reset tree->score to gather fresh stats. */
276 d->score.playouts = 1;
277 /* Correct color POV. */
278 if (color == S_WHITE)
279 score.value = - score.value;
280 if (score.value >= 0)
281 score_step = round(score.value * a->score_step_byavg);
284 if (value.value < a->zone_red) {
285 /* Red zone. Take extra komi. */
286 if (DEBUGL(3))
287 fprintf(stderr, "[red] %f, -= %d | komi ratchet %f -> %f\n",
288 value.value, score_step, a->komi_ratchet, extra_komi);
289 if (extra_komi > 0) a->komi_ratchet = extra_komi;
290 extra_komi -= score_step;
291 return komi_by_color(extra_komi, color);
293 } else if (value.value < a->zone_green) {
294 /* Yellow zone, do nothing. */
295 return komi_by_color(extra_komi, color);
297 } else {
298 /* Green zone. Give extra komi. */
299 extra_komi += score_step;
300 if (DEBUGL(3))
301 fprintf(stderr, "[green] %f, += %d | komi ratchet %f age %d\n",
302 value.value, score_step, a->komi_ratchet, a->komi_ratchet_age);
303 if (a->komi_ratchet_maxage > 0 && a->komi_ratchet_age > a->komi_ratchet_maxage) {
304 a->komi_ratchet = 1000;
305 a->komi_ratchet_age = 0;
307 if (a->use_komi_ratchet && extra_komi >= a->komi_ratchet) {
308 extra_komi = a->komi_ratchet - 1;
309 a->komi_ratchet_age++;
311 return komi_by_color(extra_komi, color);
315 static float
316 adaptive_permove(struct uct_dynkomi *d, struct board *b, struct tree *tree)
318 struct dynkomi_adaptive *a = d->data;
319 if (DEBUGL(3))
320 fprintf(stderr, "m %d/%d ekomi %f permove %f/%d\n",
321 b->moves, a->lead_moves, tree->extra_komi,
322 d->score.value, d->score.playouts);
323 if (b->moves <= a->lead_moves)
324 return board_effective_handicap(b, 7 /* XXX */);
326 enum stone color = stone_other(tree->root_color);
327 /* Get lower bound on komi we take so that we don't underperform
328 * too much. */
329 float min_komi = komi_by_color(- a->max_losing_komi, color);
331 float komi = a->indicator(d, b, tree, color);
332 if (DEBUGL(3))
333 fprintf(stderr, "dynkomi: %f -> %f\n", tree->extra_komi, komi);
334 return komi_by_color(komi - min_komi, color) > 0 ? komi : min_komi;
337 static float
338 adaptive_persim(struct uct_dynkomi *d, struct board *b, struct tree *tree, struct tree_node *node)
340 return tree->extra_komi;
343 struct uct_dynkomi *
344 uct_dynkomi_init_adaptive(struct uct *u, char *arg, struct board *b)
346 struct uct_dynkomi *d = calloc2(1, sizeof(*d));
347 d->uct = u;
348 d->permove = adaptive_permove;
349 d->persim = adaptive_persim;
350 d->done = generic_done;
352 struct dynkomi_adaptive *a = calloc2(1, sizeof(*a));
353 d->data = a;
355 if (board_size(b) - 2 >= 19)
356 a->lead_moves = 20;
357 else
358 a->lead_moves = 4; // XXX
359 a->max_losing_komi = 0;
360 a->indicator = komi_by_score;
362 a->adapter = adapter_sigmoid;
363 a->adapt_rate = -18;
364 a->adapt_phase = 0.65;
365 a->adapt_moves = 200;
366 a->adapt_dir = -0.5;
368 a->zone_red = 0.45;
369 a->zone_green = 0.55;
370 a->score_step = 2;
371 a->use_komi_ratchet = true;
372 a->komi_ratchet_maxage = 0;
373 a->komi_ratchet = 1000;
375 if (arg) {
376 char *optspec, *next = arg;
377 while (*next) {
378 optspec = next;
379 next += strcspn(next, ":");
380 if (*next) { *next++ = 0; } else { *next = 0; }
382 char *optname = optspec;
383 char *optval = strchr(optspec, '=');
384 if (optval) *optval++ = 0;
386 if (!strcasecmp(optname, "lead_moves") && optval) {
387 /* Do not adjust komi adaptively for first
388 * N moves. */
389 a->lead_moves = atoi(optval);
390 } else if (!strcasecmp(optname, "max_losing_komi") && optval) {
391 a->max_losing_komi = atof(optval);
392 } else if (!strcasecmp(optname, "indicator")) {
393 /* Adaptatation indicator - how to decide
394 * the adaptation rate and direction. */
395 if (!strcasecmp(optval, "value")) {
396 /* Winrate w/ komi so far. */
397 a->indicator = komi_by_value;
398 } else if (!strcasecmp(optval, "score")) {
399 /* Expected score w/ current komi. */
400 a->indicator = komi_by_score;
401 } else {
402 fprintf(stderr, "UCT: Invalid indicator %s\n", optval);
403 exit(1);
406 /* value indicator settings */
407 } else if (!strcasecmp(optname, "zone_red") && optval) {
408 a->zone_red = atof(optval);
409 } else if (!strcasecmp(optname, "zone_green") && optval) {
410 a->zone_green = atof(optval);
411 } else if (!strcasecmp(optname, "score_step") && optval) {
412 a->score_step = atoi(optval);
413 } else if (!strcasecmp(optname, "score_step_byavg") && optval) {
414 a->score_step_byavg = atof(optval);
415 } else if (!strcasecmp(optname, "use_komi_ratchet")) {
416 a->use_komi_ratchet = !optval || atoi(optval);
417 } else if (!strcasecmp(optname, "komi_ratchet_age") && optval) {
418 a->komi_ratchet_maxage = atoi(optval);
420 /* score indicator settings */
421 } else if (!strcasecmp(optname, "adapter") && optval) {
422 /* Adaptatation method. */
423 if (!strcasecmp(optval, "sigmoid")) {
424 a->adapter = adapter_sigmoid;
425 } else if (!strcasecmp(optval, "linear")) {
426 a->adapter = adapter_linear;
427 } else {
428 fprintf(stderr, "UCT: Invalid adapter %s\n", optval);
429 exit(1);
431 } else if (!strcasecmp(optname, "adapt_base") && optval) {
432 /* Adaptation base rate; see above. */
433 a->adapt_base = atof(optval);
434 } else if (!strcasecmp(optname, "adapt_rate") && optval) {
435 /* Adaptation slope; see above. */
436 a->adapt_rate = atof(optval);
437 } else if (!strcasecmp(optname, "adapt_phase") && optval) {
438 /* Adaptation phase shift; see above. */
439 a->adapt_phase = atof(optval);
440 } else if (!strcasecmp(optname, "adapt_moves") && optval) {
441 /* Adaptation move amount; see above. */
442 a->adapt_moves = atoi(optval);
443 } else if (!strcasecmp(optname, "adapt_aport")) {
444 a->adapt_aport = !optval || atoi(optval);
445 } else if (!strcasecmp(optname, "adapt_dir") && optval) {
446 /* Adaptation direction vector; see above. */
447 a->adapt_dir = atof(optval);
449 } else {
450 fprintf(stderr, "uct: Invalid dynkomi argument %s or missing value\n", optname);
451 exit(1);
456 return d;