10 #include "tactics/util.h"
11 #include "uct/dynkomi.h"
12 #include "uct/internal.h"
17 generic_done(struct uct_dynkomi
*d
)
19 if (d
->data
) free(d
->data
);
24 /* NONE dynkomi strategy - never fiddle with komi values. */
27 uct_dynkomi_init_none(struct uct
*u
, char *arg
, struct board
*b
)
29 struct uct_dynkomi
*d
= calloc2(1, sizeof(*d
));
33 d
->done
= generic_done
;
37 fprintf(stderr
, "uct: Dynkomi method none accepts no arguments\n");
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
];
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
;
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
;
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 if (extra_komi
< 0 && DEBUGL(3))
92 fprintf(stderr
, "XXX: extra_komi %.3f < 0 (color %s tree ek %.3f)\n", extra_komi
, stone2str(color
), tree
->extra_komi
);
93 // assert(extra_komi >= 0);
94 floating_t orig_komi
= extra_komi
;
96 if (my_value
< 0.5 && l
->komi_ratchet
> 0 && l
->komi_ratchet
!= INFINITY
) {
98 fprintf(stderr
, "losing %f extra komi %.1f ratchet %.1f -> 0\n",
99 my_value
, extra_komi
, l
->komi_ratchet
);
100 /* Disable dynkomi completely, too dangerous in this game. */
101 extra_komi
= l
->komi_ratchet
= 0;
103 } else if (my_value
< l
->orange_zone
&& extra_komi
> 0) {
104 extra_komi
= l
->komi_ratchet
= fmax(extra_komi
- l
->drop_step
, 0.0);
105 if (extra_komi
!= orig_komi
&& DEBUGL(3))
106 fprintf(stderr
, "dropping to %f, extra komi %.1f -> ratchet %.1f\n",
107 my_value
, orig_komi
, extra_komi
);
109 } else if (my_value
> l
->green_zone
&& extra_komi
+ 1 <= l
->komi_ratchet
) {
111 if (extra_komi
!= orig_komi
&& DEBUGL(3))
112 fprintf(stderr
, "winning %f extra_komi %.1f -> %.1f, ratchet %.1f\n",
113 my_value
, orig_komi
, extra_komi
, l
->komi_ratchet
);
115 return komi_by_color(extra_komi
, color
);
119 linear_persim(struct uct_dynkomi
*d
, struct board
*b
, struct tree
*tree
, struct tree_node
*node
)
121 struct dynkomi_linear
*l
= d
->data
;
123 return tree
->extra_komi
;
124 /* We don't reuse computed value from tree->extra_komi,
125 * since we want to use value correct for this node depth.
126 * This also means the values will stay correct after
128 return linear_permove(d
, b
, tree
);
132 uct_dynkomi_init_linear(struct uct
*u
, char *arg
, struct board
*b
)
134 struct uct_dynkomi
*d
= calloc2(1, sizeof(*d
));
136 d
->permove
= linear_permove
;
137 d
->persim
= linear_persim
;
138 d
->done
= generic_done
;
140 struct dynkomi_linear
*l
= calloc2(1, sizeof(*l
));
143 /* Force white to feel behind and try harder, but not to the
144 * point of resigning immediately in high handicap games.
145 * By move 100 white should still be behind but should have
146 * caught up enough to avoid resigning. */
147 if (board_large(b
)) {
148 l
->moves
[S_BLACK
] = 100;
149 l
->moves
[S_WHITE
] = 50;
151 /* The real value of one stone is twice the komi so about 15 points.
152 * But use a lower value to avoid being too pessimistic as black
153 * or too optimistic as white. */
154 l
->handicap_value
[S_BLACK
] = 8;
155 l
->handicap_value
[S_WHITE
] = 1;
157 l
->komi_ratchet
= INFINITY
;
158 l
->green_zone
= 0.85;
159 l
->orange_zone
= 0.8;
163 char *optspec
, *next
= arg
;
166 next
+= strcspn(next
, ":");
167 if (*next
) { *next
++ = 0; } else { *next
= 0; }
169 char *optname
= optspec
;
170 char *optval
= strchr(optspec
, '=');
171 if (optval
) *optval
++ = 0;
173 if (!strcasecmp(optname
, "moves") && optval
) {
174 /* Dynamic komi in handicap game; linearly
175 * decreases to basic settings until move
176 * #optval. moves=blackmoves%whitemoves */
177 for (int i
= S_BLACK
; *optval
&& i
<= S_WHITE
; i
++) {
178 l
->moves
[i
] = atoi(optval
);
179 optval
+= strcspn(optval
, "%");
180 if (*optval
) optval
++;
182 } else if (!strcasecmp(optname
, "handicap_value") && optval
) {
183 /* Point value of single handicap stone,
184 * for dynkomi computation. */
185 for (int i
= S_BLACK
; *optval
&& i
<= S_WHITE
; i
++) {
186 l
->handicap_value
[i
] = atoi(optval
);
187 optval
+= strcspn(optval
, "%");
188 if (*optval
) optval
++;
190 } else if (!strcasecmp(optname
, "rootbased")) {
191 /* If set, the extra komi applied will be
192 * the same for all simulations within a move,
193 * instead of being same for all simulations
194 * within the tree node. */
195 l
->rootbased
= !optval
|| atoi(optval
);
196 } else if (!strcasecmp(optname
, "green_zone") && optval
) {
197 /* Increase komi when win ratio is above green_zone */
198 l
->green_zone
= atof(optval
);
199 } else if (!strcasecmp(optname
, "orange_zone") && optval
) {
200 /* Decrease komi when > 0 and win ratio is below orange_zone */
201 l
->orange_zone
= atof(optval
);
202 } else if (!strcasecmp(optname
, "drop_step") && optval
) {
203 /* Decrease komi by drop_step points */
204 l
->drop_step
= atof(optval
);
206 fprintf(stderr
, "uct: Invalid dynkomi argument %s or missing value\n", optname
);
216 /* ADAPTIVE dynkomi strategy - Adaptive Situational Compensation */
217 /* We adapt the komi based on current situation:
218 * (i) score-based: We maintain the average score outcome of our
219 * games and adjust the komi by a fractional step towards the expected
221 * (ii) value-based: While winrate is above given threshold, adjust
222 * the komi by a fixed step in the appropriate direction.
223 * These adjustments can be
224 * (a) Move-stepped, new extra komi value is always set only at the
225 * beginning of the tree search for next move;
226 * (b) Continuous, new extra komi value is periodically re-determined
227 * and adjusted throughout a single tree search. */
229 struct dynkomi_adaptive
{
230 /* Do not take measured average score into regard for
231 * first @lead_moves - the variance is just too much.
232 * (Instead, we consider the handicap-based komi provided
233 * by linear dynkomi.) */
235 /* Maximum komi to pretend the opponent to give. */
236 floating_t max_losing_komi
;
237 /* Game portion at which losing komi is not allowed anymore. */
238 floating_t losing_komi_stop
;
239 /* Alternative game portion determination. */
241 floating_t (*indicator
)(struct uct_dynkomi
*d
, struct board
*b
, struct tree
*tree
, enum stone color
);
243 /* Value-based adaptation. */
244 floating_t zone_red
, zone_green
;
246 floating_t score_step_byavg
; // use portion of average score as increment
247 bool use_komi_ratchet
;
248 bool losing_komi_ratchet
; // ratchet even losing komi
249 int komi_ratchet_maxage
;
250 // runtime, not configuration:
251 int komi_ratchet_age
;
252 floating_t komi_ratchet
;
254 /* Score-based adaptation. */
255 floating_t (*adapter
)(struct uct_dynkomi
*d
, struct board
*b
);
256 floating_t adapt_base
; // [0,1)
257 /* Sigmoid adaptation rate parameter; see below for details. */
258 floating_t adapt_phase
; // [0,1]
259 floating_t adapt_rate
; // [1,infty)
260 /* Linear adaptation rate parameter. */
262 floating_t adapt_dir
; // [-1,1]
264 #define TRUSTWORTHY_KOMI_PLAYOUTS 200
267 board_game_portion(struct dynkomi_adaptive
*a
, struct board
*b
)
269 if (!a
->adapt_aport
) {
270 int total_moves
= b
->moves
+ 2 * board_estimated_moves_left(b
);
271 return (floating_t
) b
->moves
/ total_moves
;
273 int brsize
= board_size(b
) - 2;
274 return 1.0 - (floating_t
) b
->flen
/ (brsize
* brsize
);
279 adapter_sigmoid(struct uct_dynkomi
*d
, struct board
*b
)
281 struct dynkomi_adaptive
*a
= d
->data
;
282 /* Figure out how much to adjust the komi based on the game
283 * stage. The adaptation rate is 0 at the beginning,
284 * at game stage a->adapt_phase crosses though 0.5 and
285 * approaches 1 at the game end; the slope is controlled
286 * by a->adapt_rate. */
287 floating_t game_portion
= board_game_portion(a
, b
);
288 floating_t l
= game_portion
- a
->adapt_phase
;
289 return 1.0 / (1.0 + exp(-a
->adapt_rate
* l
));
293 adapter_linear(struct uct_dynkomi
*d
, struct board
*b
)
295 struct dynkomi_adaptive
*a
= d
->data
;
296 /* Figure out how much to adjust the komi based on the game
297 * stage. We just linearly increase/decrease the adaptation
298 * rate for first N moves. */
299 if (b
->moves
> a
->adapt_moves
)
301 if (a
->adapt_dir
< 0)
302 return 1 - (- a
->adapt_dir
) * b
->moves
/ a
->adapt_moves
;
304 return a
->adapt_dir
* b
->moves
/ a
->adapt_moves
;
308 komi_by_score(struct uct_dynkomi
*d
, struct board
*b
, struct tree
*tree
, enum stone color
)
310 struct dynkomi_adaptive
*a
= d
->data
;
311 if (d
->score
.playouts
< TRUSTWORTHY_KOMI_PLAYOUTS
)
312 return tree
->extra_komi
;
314 struct move_stats score
= d
->score
;
315 /* Almost-reset tree->score to gather fresh stats. */
316 d
->score
.playouts
= 1;
318 /* Look at average score and push extra_komi in that direction. */
319 floating_t p
= a
->adapter(d
, b
);
320 p
= a
->adapt_base
+ p
* (1 - a
->adapt_base
);
321 if (p
> 0.9) p
= 0.9; // don't get too eager!
322 floating_t extra_komi
= tree
->extra_komi
+ p
* score
.value
;
324 fprintf(stderr
, "mC += %f * %f\n", p
, score
.value
);
329 komi_by_value(struct uct_dynkomi
*d
, struct board
*b
, struct tree
*tree
, enum stone color
)
331 struct dynkomi_adaptive
*a
= d
->data
;
332 if (d
->value
.playouts
< TRUSTWORTHY_KOMI_PLAYOUTS
)
333 return tree
->extra_komi
;
335 struct move_stats value
= d
->value
;
336 /* Almost-reset tree->value to gather fresh stats. */
337 d
->value
.playouts
= 1;
338 /* Correct color POV. */
339 if (color
== S_WHITE
)
340 value
.value
= 1 - value
.value
;
342 /* We have three "value zones":
343 * red zone | yellow zone | green zone
345 * red zone: reduce komi
346 * yellow zone: do not touch komi
347 * green zone: enlage komi.
349 * Also, at some point komi will be tuned in such way
350 * that it will be in green zone but increasing it will
351 * be unfeasible. Thus, we have a _ratchet_ - we will
352 * remember the last komi that has put us into the
353 * red zone, and not use it or go over it. We use the
354 * ratchet only when giving extra komi, we always want
355 * to try to reduce extra komi we take.
357 * TODO: Make the ratchet expire after a while. */
359 /* We use komi_by_color() first to normalize komi
360 * additions/subtractions, then apply it again on
361 * return value to restore original komi parity. */
362 /* Positive extra_komi means that we are _giving_
363 * komi (winning), negative extra_komi is _taking_
365 floating_t extra_komi
= komi_by_color(tree
->extra_komi
, color
);
366 int score_step_red
= -a
->score_step
;
367 int score_step_green
= a
->score_step
;
369 if (a
->score_step_byavg
!= 0) {
370 struct move_stats score
= d
->score
;
371 /* Almost-reset tree->score to gather fresh stats. */
372 d
->score
.playouts
= 1;
373 /* Correct color POV. */
374 if (color
== S_WHITE
)
375 score
.value
= - score
.value
;
377 score_step_green
= round(score
.value
* a
->score_step_byavg
);
379 score_step_red
= round(-score
.value
* a
->score_step_byavg
);
380 if (score_step_green
< 0 || score_step_red
> 0) {
381 /* The steps are in bad direction - keep still. */
382 return komi_by_color(extra_komi
, color
);
386 /* Wear out the ratchet. */
387 if (a
->use_komi_ratchet
&& a
->komi_ratchet_maxage
> 0) {
388 a
->komi_ratchet_age
+= value
.playouts
;
389 if (a
->komi_ratchet_age
> a
->komi_ratchet_maxage
) {
390 a
->komi_ratchet
= 1000;
391 a
->komi_ratchet_age
= 0;
395 if (value
.value
< a
->zone_red
) {
396 /* Red zone. Take extra komi. */
398 fprintf(stderr
, "[red] %f, step %d | komi ratchet %f age %d/%d -> %f\n",
399 value
.value
, score_step_red
, a
->komi_ratchet
, a
->komi_ratchet_age
, a
->komi_ratchet_maxage
, extra_komi
);
400 if (a
->losing_komi_ratchet
|| extra_komi
> 0) {
401 a
->komi_ratchet
= extra_komi
;
402 a
->komi_ratchet_age
= 0;
404 extra_komi
+= score_step_red
;
405 return komi_by_color(extra_komi
, color
);
407 } else if (value
.value
< a
->zone_green
) {
408 /* Yellow zone, do nothing. */
409 return komi_by_color(extra_komi
, color
);
412 /* Green zone. Give extra komi. */
414 fprintf(stderr
, "[green] %f, step %d | komi ratchet %f age %d/%d\n",
415 value
.value
, score_step_green
, a
->komi_ratchet
, a
->komi_ratchet_age
, a
->komi_ratchet_maxage
);
416 extra_komi
+= score_step_green
;
417 if (a
->use_komi_ratchet
&& extra_komi
>= a
->komi_ratchet
)
418 extra_komi
= a
->komi_ratchet
- 1;
419 return komi_by_color(extra_komi
, color
);
424 bounded_komi(struct dynkomi_adaptive
*a
, struct board
*b
,
425 enum stone color
, floating_t komi
, floating_t max_losing_komi
)
427 /* At the end of game, disallow losing komi. */
428 if (komi_by_color(komi
, color
) < 0
429 && board_game_portion(a
, b
) > a
->losing_komi_stop
)
432 /* Get lower bound on komi we take so that we don't underperform
434 floating_t min_komi
= komi_by_color(- max_losing_komi
, color
);
436 if (komi_by_color(komi
- min_komi
, color
) > 0)
443 adaptive_permove(struct uct_dynkomi
*d
, struct board
*b
, struct tree
*tree
)
445 /* We do not use extra komi at the game end - we are not
446 * to fool ourselves at this point. */
447 if (board_estimated_moves_left(b
) <= MIN_MOVES_LEFT
) {
448 tree
->use_extra_komi
= false;
451 struct dynkomi_adaptive
*a
= d
->data
;
452 enum stone color
= stone_other(tree
->root_color
);
454 fprintf(stderr
, "m %d/%d ekomi %f permove %f/%d\n",
455 b
->moves
, a
->lead_moves
, tree
->extra_komi
,
456 d
->score
.value
, d
->score
.playouts
);
458 if (b
->moves
<= a
->lead_moves
)
459 return bounded_komi(a
, b
, color
,
460 board_effective_handicap(b
, 7 /* XXX */),
463 floating_t komi
= a
->indicator(d
, b
, tree
, color
);
465 fprintf(stderr
, "dynkomi: %f -> %f\n", tree
->extra_komi
, komi
);
466 return bounded_komi(a
, b
, color
, komi
, a
->max_losing_komi
);
470 adaptive_persim(struct uct_dynkomi
*d
, struct board
*b
, struct tree
*tree
, struct tree_node
*node
)
472 return tree
->extra_komi
;
476 uct_dynkomi_init_adaptive(struct uct
*u
, char *arg
, struct board
*b
)
478 struct uct_dynkomi
*d
= calloc2(1, sizeof(*d
));
480 d
->permove
= adaptive_permove
;
481 d
->persim
= adaptive_persim
;
482 d
->done
= generic_done
;
484 struct dynkomi_adaptive
*a
= calloc2(1, sizeof(*a
));
487 a
->lead_moves
= board_large(b
) ? 20 : 4; // XXX
488 a
->max_losing_komi
= 30;
489 a
->losing_komi_stop
= 1.0f
;
490 a
->indicator
= komi_by_value
;
492 a
->adapter
= adapter_sigmoid
;
494 a
->adapt_phase
= 0.65;
495 a
->adapt_moves
= 200;
499 a
->zone_green
= 0.50;
501 a
->use_komi_ratchet
= true;
502 a
->komi_ratchet_maxage
= 0;
503 a
->komi_ratchet
= 1000;
506 char *optspec
, *next
= arg
;
509 next
+= strcspn(next
, ":");
510 if (*next
) { *next
++ = 0; } else { *next
= 0; }
512 char *optname
= optspec
;
513 char *optval
= strchr(optspec
, '=');
514 if (optval
) *optval
++ = 0;
516 if (!strcasecmp(optname
, "lead_moves") && optval
) {
517 /* Do not adjust komi adaptively for first
519 a
->lead_moves
= atoi(optval
);
520 } else if (!strcasecmp(optname
, "max_losing_komi") && optval
) {
521 a
->max_losing_komi
= atof(optval
);
522 } else if (!strcasecmp(optname
, "losing_komi_stop") && optval
) {
523 a
->losing_komi_stop
= atof(optval
);
524 } else if (!strcasecmp(optname
, "indicator")) {
525 /* Adaptatation indicator - how to decide
526 * the adaptation rate and direction. */
527 if (!strcasecmp(optval
, "value")) {
528 /* Winrate w/ komi so far. */
529 a
->indicator
= komi_by_value
;
530 } else if (!strcasecmp(optval
, "score")) {
531 /* Expected score w/ current komi. */
532 a
->indicator
= komi_by_score
;
534 fprintf(stderr
, "UCT: Invalid indicator %s\n", optval
);
538 /* value indicator settings */
539 } else if (!strcasecmp(optname
, "zone_red") && optval
) {
540 a
->zone_red
= atof(optval
);
541 } else if (!strcasecmp(optname
, "zone_green") && optval
) {
542 a
->zone_green
= atof(optval
);
543 } else if (!strcasecmp(optname
, "score_step") && optval
) {
544 a
->score_step
= atoi(optval
);
545 } else if (!strcasecmp(optname
, "score_step_byavg") && optval
) {
546 a
->score_step_byavg
= atof(optval
);
547 } else if (!strcasecmp(optname
, "use_komi_ratchet")) {
548 a
->use_komi_ratchet
= !optval
|| atoi(optval
);
549 } else if (!strcasecmp(optname
, "losing_komi_ratchet")) {
550 a
->losing_komi_ratchet
= !optval
|| atoi(optval
);
551 } else if (!strcasecmp(optname
, "komi_ratchet_age") && optval
) {
552 a
->komi_ratchet_maxage
= atoi(optval
);
554 /* score indicator settings */
555 } else if (!strcasecmp(optname
, "adapter") && optval
) {
556 /* Adaptatation method. */
557 if (!strcasecmp(optval
, "sigmoid")) {
558 a
->adapter
= adapter_sigmoid
;
559 } else if (!strcasecmp(optval
, "linear")) {
560 a
->adapter
= adapter_linear
;
562 fprintf(stderr
, "UCT: Invalid adapter %s\n", optval
);
565 } else if (!strcasecmp(optname
, "adapt_base") && optval
) {
566 /* Adaptation base rate; see above. */
567 a
->adapt_base
= atof(optval
);
568 } else if (!strcasecmp(optname
, "adapt_rate") && optval
) {
569 /* Adaptation slope; see above. */
570 a
->adapt_rate
= atof(optval
);
571 } else if (!strcasecmp(optname
, "adapt_phase") && optval
) {
572 /* Adaptation phase shift; see above. */
573 a
->adapt_phase
= atof(optval
);
574 } else if (!strcasecmp(optname
, "adapt_moves") && optval
) {
575 /* Adaptation move amount; see above. */
576 a
->adapt_moves
= atoi(optval
);
577 } else if (!strcasecmp(optname
, "adapt_aport")) {
578 a
->adapt_aport
= !optval
|| atoi(optval
);
579 } else if (!strcasecmp(optname
, "adapt_dir") && optval
) {
580 /* Adaptation direction vector; see above. */
581 a
->adapt_dir
= atof(optval
);
584 fprintf(stderr
, "uct: Invalid dynkomi argument %s or missing value\n", optname
);