uct/dynkomi.c

   1 #define DEBUG
   2 #include <assert.h>
   3 #include <math.h>
   4 #include <stdio.h>
   5 #include <stdlib.h>
   6 #include <string.h>
   7
   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"
  14
  15
  16 static void
  17 generic_done(struct uct_dynkomi *d)
  18 {
  19         if (d->data) free(d->data);
  20         free(d);
  21 }
  22
  23
  24 /* NONE dynkomi strategy - never fiddle with komi values. */
  25
  26 struct uct_dynkomi *
  27 uct_dynkomi_init_none(struct uct *u, char *arg, struct board *b)
  28 {
  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;
  35
  36         if (arg) {
  37                 fprintf(stderr, "uct: Dynkomi method none accepts no arguments\n");
  38                 exit(1);
  39         }
  40
  41         return d;
  42 }
  43
  44
  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. */
  51
  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;
  67 };
  68
  69 static floating_t
  70 linear_permove(struct uct_dynkomi *d, struct board *b, struct tree *tree)
  71 {
  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;
  76
  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);
  83         }
  84
  85         /* Do not take decisions on unstable value. */
  86         if (tree->root->u.playouts < GJ_MINGAMES) return extra_komi;
  87
  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
  93         if (my_value < 0.5 && l->komi_ratchet > 0 && l->komi_ratchet != INFINITY) {
  94                 if (DEBUGL(0))
  95                         fprintf(stderr, "losing %f extra %.1f ratchet %.1f -> 0\n",
  96                                 my_value, extra_komi, l->komi_ratchet);
  97                 /* Disable dynkomi completely, too dangerous in this game. */
  98                 extra_komi = l->komi_ratchet = 0;
  99
 100         } else if (my_value < l->orange_zone && extra_komi > 0) {
 101                 extra_komi = l->komi_ratchet  = fmax(extra_komi - l->drop_step, 0.0);
 102                 if (DEBUGL(3))
 103                         fprintf(stderr, "dropping to %f ratchet -> %.1f\n",
 104                                 my_value, extra_komi);
 105
 106         } else if (my_value > l->green_zone && extra_komi +1 <= l->komi_ratchet) {
 107                 extra_komi += 1;
 108                 if (DEBUGL(3))
 109                         fprintf(stderr, "winning %f extra_komi -> %.1f, ratchet %.1f\n",
 110                                 my_value, extra_komi, l->komi_ratchet);
 111         }
 112         return komi_by_color(extra_komi, color);
 113 }
 114
 115 static floating_t
 116 linear_persim(struct uct_dynkomi *d, struct board *b, struct tree *tree, struct tree_node *node)
 117 {
 118         struct dynkomi_linear *l = d->data;
 119         if (l->rootbased)
 120                 return tree->extra_komi;
 121         /* We don't reuse computed value from tree->extra_komi,
 122          * since we want to use value correct for this node depth.
 123          * This also means the values will stay correct after
 124          * node promotion. */
 125         return linear_permove(d, b, tree);
 126 }
 127
 128 struct uct_dynkomi *
 129 uct_dynkomi_init_linear(struct uct *u, char *arg, struct board *b)
 130 {
 131         struct uct_dynkomi *d = calloc2(1, sizeof(*d));
 132         d->uct = u;
 133         d->permove = linear_permove;
 134         d->persim = linear_persim;
 135         d->done = generic_done;
 136
 137         struct dynkomi_linear *l = calloc2(1, sizeof(*l));
 138         d->data = l;
 139
 140         /* Force white to feel behind and try harder, but not to the
 141          * point of resigning immediately in high handicap games.
 142          * By move 100 white should still be behind but should have
 143          * caught up enough to avoid resigning. */
 144         if (board_large(b)) {
 145                 l->moves[S_BLACK] = 100;
 146                 l->moves[S_WHITE] = 50;
 147         }
 148         /* The real value of one stone is twice the komi so about 15 points.
 149          * But use a lower value to avoid being too pessimistic as black
 150          * or too optimistic as white. */
 151         l->handicap_value[S_BLACK] = 8;
 152         l->handicap_value[S_WHITE] = 1;
 153
 154         l->komi_ratchet = INFINITY;
 155         l->green_zone = 0.85;
 156         l->orange_zone = 0.8;
 157         l->drop_step = 4.0;
 158
 159         if (arg) {
 160                 char *optspec, *next = arg;
 161                 while (*next) {
 162                         optspec = next;
 163                         next += strcspn(next, ":");
 164                         if (*next) { *next++ = 0; } else { *next = 0; }
 165
 166                         char *optname = optspec;
 167                         char *optval = strchr(optspec, '=');
 168                         if (optval) *optval++ = 0;
 169
 170                         if (!strcasecmp(optname, "moves") && optval) {
 171                                 /* Dynamic komi in handicap game; linearly
 172                                  * decreases to basic settings until move
 173                                  * #optval. moves=blackmoves%whitemoves */
 174                                 for (int i = S_BLACK; *optval && i <= S_WHITE; i++) {
 175                                         l->moves[i] = atoi(optval);
 176                                         optval += strcspn(optval, "%");
 177                                         if (*optval) optval++;
 178                                 }
 179                         } else if (!strcasecmp(optname, "handicap_value") && optval) {
 180                                 /* Point value of single handicap stone,
 181                                  * for dynkomi computation. */
 182                                 for (int i = S_BLACK; *optval && i <= S_WHITE; i++) {
 183                                         l->handicap_value[i] = atoi(optval);
 184                                         optval += strcspn(optval, "%");
 185                                         if (*optval) optval++;
 186                                 }
 187                         } else if (!strcasecmp(optname, "rootbased")) {
 188                                 /* If set, the extra komi applied will be
 189                                  * the same for all simulations within a move,
 190                                  * instead of being same for all simulations
 191                                  * within the tree node. */
 192                                 l->rootbased = !optval || atoi(optval);
 193                         } else if (!strcasecmp(optname, "green_zone") && optval) {
 194                                 /* Increase komi when win ratio is above green_zone */
 195                                 l->green_zone = atof(optval);
 196                         } else if (!strcasecmp(optname, "orange_zone") && optval) {
 197                                 /* Decrease komi when > 0 and win ratio is below orange_zone */
 198                                 l->orange_zone = atof(optval);
 199                         } else if (!strcasecmp(optname, "drop_step") && optval) {
 200                                 /* Decrease komi by drop_step points */
 201                                 l->drop_step = atof(optval);
 202                         } else {
 203                                 fprintf(stderr, "uct: Invalid dynkomi argument %s or missing value\n", optname);
 204                                 exit(1);
 205                         }
 206                 }
 207         }
 208
 209         return d;
 210 }
 211
 212
 213 /* ADAPTIVE dynkomi strategy - Adaptive Situational Compensation */
 214 /* We adapt the komi based on current situation:
 215  * (i) score-based: We maintain the average score outcome of our
 216  * games and adjust the komi by a fractional step towards the expected
 217  * score;
 218  * (ii) value-based: While winrate is above given threshold, adjust
 219  * the komi by a fixed step in the appropriate direction.
 220  * These adjustments can be
 221  * (a) Move-stepped, new extra komi value is always set only at the
 222  * beginning of the tree search for next move;
 223  * (b) Continuous, new extra komi value is periodically re-determined
 224  * and adjusted throughout a single tree search. */
 225
 226 struct dynkomi_adaptive {
 227         /* Do not take measured average score into regard for
 228          * first @lead_moves - the variance is just too much.
 229          * (Instead, we consider the handicap-based komi provided
 230          * by linear dynkomi.) */
 231         int lead_moves;
 232         /* Maximum komi to pretend the opponent to give. */
 233         floating_t max_losing_komi;
 234         /* Game portion at which losing komi is not allowed anymore. */
 235         floating_t losing_komi_stop;
 236         /* Alternative game portion determination. */
 237         bool adapt_aport;
 238         floating_t (*indicator)(struct uct_dynkomi *d, struct board *b, struct tree *tree, enum stone color);
 239
 240         /* Value-based adaptation. */
 241         floating_t zone_red, zone_green;
 242         int score_step;
 243         floating_t score_step_byavg; // use portion of average score as increment
 244         bool use_komi_ratchet;
 245         bool losing_komi_ratchet; // ratchet even losing komi
 246         int komi_ratchet_maxage;
 247         // runtime, not configuration:
 248         int komi_ratchet_age;
 249         floating_t komi_ratchet;
 250
 251         /* Score-based adaptation. */
 252         floating_t (*adapter)(struct uct_dynkomi *d, struct board *b);
 253         floating_t adapt_base; // [0,1)
 254         /* Sigmoid adaptation rate parameter; see below for details. */
 255         floating_t adapt_phase; // [0,1]
 256         floating_t adapt_rate; // [1,infty)
 257         /* Linear adaptation rate parameter. */
 258         int adapt_moves;
 259         floating_t adapt_dir; // [-1,1]
 260 };
 261 #define TRUSTWORTHY_KOMI_PLAYOUTS 200
 262
 263 static floating_t
 264 board_game_portion(struct dynkomi_adaptive *a, struct board *b)
 265 {
 266         if (!a->adapt_aport) {
 267                 int total_moves = b->moves + 2 * board_estimated_moves_left(b);
 268                 return (floating_t) b->moves / total_moves;
 269         } else {
 270                 int brsize = board_size(b) - 2;
 271                 return 1.0 - (floating_t) b->flen / (brsize * brsize);
 272         }
 273 }
 274
 275 static floating_t
 276 adapter_sigmoid(struct uct_dynkomi *d, struct board *b)
 277 {
 278         struct dynkomi_adaptive *a = d->data;
 279         /* Figure out how much to adjust the komi based on the game
 280          * stage. The adaptation rate is 0 at the beginning,
 281          * at game stage a->adapt_phase crosses though 0.5 and
 282          * approaches 1 at the game end; the slope is controlled
 283          * by a->adapt_rate. */
 284         floating_t game_portion = board_game_portion(a, b);
 285         floating_t l = game_portion - a->adapt_phase;
 286         return 1.0 / (1.0 + exp(-a->adapt_rate * l));
 287 }
 288
 289 static floating_t
 290 adapter_linear(struct uct_dynkomi *d, struct board *b)
 291 {
 292         struct dynkomi_adaptive *a = d->data;
 293         /* Figure out how much to adjust the komi based on the game
 294          * stage. We just linearly increase/decrease the adaptation
 295          * rate for first N moves. */
 296         if (b->moves > a->adapt_moves)
 297                 return 0;
 298         if (a->adapt_dir < 0)
 299                 return 1 - (- a->adapt_dir) * b->moves / a->adapt_moves;
 300         else
 301                 return a->adapt_dir * b->moves / a->adapt_moves;
 302 }
 303
 304 static floating_t
 305 komi_by_score(struct uct_dynkomi *d, struct board *b, struct tree *tree, enum stone color)
 306 {
 307         struct dynkomi_adaptive *a = d->data;
 308         if (d->score.playouts < TRUSTWORTHY_KOMI_PLAYOUTS)
 309                 return tree->extra_komi;
 310
 311         struct move_stats score = d->score;
 312         /* Almost-reset tree->score to gather fresh stats. */
 313         d->score.playouts = 1;
 314
 315         /* Look at average score and push extra_komi in that direction. */
 316         floating_t p = a->adapter(d, b);
 317         p = a->adapt_base + p * (1 - a->adapt_base);
 318         if (p > 0.9) p = 0.9; // don't get too eager!
 319         floating_t extra_komi = tree->extra_komi + p * score.value;
 320         if (DEBUGL(3))
 321                 fprintf(stderr, "mC += %f * %f\n", p, score.value);
 322         return extra_komi;
 323 }
 324
 325 static floating_t
 326 komi_by_value(struct uct_dynkomi *d, struct board *b, struct tree *tree, enum stone color)
 327 {
 328         struct dynkomi_adaptive *a = d->data;
 329         if (d->value.playouts < TRUSTWORTHY_KOMI_PLAYOUTS)
 330                 return tree->extra_komi;
 331
 332         struct move_stats value = d->value;
 333         /* Almost-reset tree->value to gather fresh stats. */
 334         d->value.playouts = 1;
 335         /* Correct color POV. */
 336         if (color == S_WHITE)
 337                 value.value = 1 - value.value;
 338
 339         /* We have three "value zones":
 340          * red zone | yellow zone | green zone
 341          *        ~45%           ~60%
 342          * red zone: reduce komi
 343          * yellow zone: do not touch komi
 344          * green zone: enlage komi.
 345          *
 346          * Also, at some point komi will be tuned in such way
 347          * that it will be in green zone but increasing it will
 348          * be unfeasible. Thus, we have a _ratchet_ - we will
 349          * remember the last komi that has put us into the
 350          * red zone, and not use it or go over it. We use the
 351          * ratchet only when giving extra komi, we always want
 352          * to try to reduce extra komi we take.
 353          *
 354          * TODO: Make the ratchet expire after a while. */
 355
 356         /* We use komi_by_color() first to normalize komi
 357          * additions/subtractions, then apply it again on
 358          * return value to restore original komi parity. */
 359         /* Positive extra_komi means that we are _giving_
 360          * komi (winning), negative extra_komi is _taking_
 361          * komi (losing). */
 362         floating_t extra_komi = komi_by_color(tree->extra_komi, color);
 363         int score_step_red = -a->score_step;
 364         int score_step_green = a->score_step;
 365
 366         if (a->score_step_byavg != 0) {
 367                 struct move_stats score = d->score;
 368                 /* Almost-reset tree->score to gather fresh stats. */
 369                 d->score.playouts = 1;
 370                 /* Correct color POV. */
 371                 if (color == S_WHITE)
 372                         score.value = - score.value;
 373                 if (score.value > 0)
 374                         score_step_green = round(score.value * a->score_step_byavg);
 375                 else
 376                         score_step_red = round(-score.value * a->score_step_byavg);
 377                 if (score_step_green < 0 || score_step_red > 0) {
 378                         /* The steps are in bad direction - keep still. */
 379                         return komi_by_color(extra_komi, color);
 380                 }
 381         }
 382
 383         /* Wear out the ratchet. */
 384         if (a->use_komi_ratchet && a->komi_ratchet_maxage > 0) {
 385                 a->komi_ratchet_age += value.playouts;
 386                 if (a->komi_ratchet_age > a->komi_ratchet_maxage) {
 387                         a->komi_ratchet = 1000;
 388                         a->komi_ratchet_age = 0;
 389                 }
 390         }
 391
 392         if (value.value < a->zone_red) {
 393                 /* Red zone. Take extra komi. */
 394                 if (DEBUGL(3))
 395                         fprintf(stderr, "[red] %f, step %d | komi ratchet %f age %d/%d -> %f\n",
 396                                 value.value, score_step_red, a->komi_ratchet, a->komi_ratchet_age, a->komi_ratchet_maxage, extra_komi);
 397                 if (a->losing_komi_ratchet || extra_komi > 0) {
 398                         a->komi_ratchet = extra_komi;
 399                         a->komi_ratchet_age = 0;
 400                 }
 401                 extra_komi += score_step_red;
 402                 return komi_by_color(extra_komi, color);
 403
 404         } else if (value.value < a->zone_green) {
 405                 /* Yellow zone, do nothing. */
 406                 return komi_by_color(extra_komi, color);
 407
 408         } else {
 409                 /* Green zone. Give extra komi. */
 410                 if (DEBUGL(3))
 411                         fprintf(stderr, "[green] %f, step %d | komi ratchet %f age %d/%d\n",
 412                                 value.value, score_step_green, a->komi_ratchet, a->komi_ratchet_age, a->komi_ratchet_maxage);
 413                 extra_komi += score_step_green;
 414                 if (a->use_komi_ratchet && extra_komi >= a->komi_ratchet)
 415                         extra_komi = a->komi_ratchet - 1;
 416                 return komi_by_color(extra_komi, color);
 417         }
 418 }
 419
 420 static floating_t
 421 bounded_komi(struct dynkomi_adaptive *a, struct board *b,
 422              enum stone color, floating_t komi, floating_t max_losing_komi)
 423 {
 424         /* At the end of game, disallow losing komi. */
 425         if (komi_by_color(komi, color) < 0
 426             && board_game_portion(a, b) > a->losing_komi_stop)
 427                 return 0;
 428
 429         /* Get lower bound on komi we take so that we don't underperform
 430          * too much. */
 431         floating_t min_komi = komi_by_color(- max_losing_komi, color);
 432
 433         if (komi_by_color(komi - min_komi, color) > 0)
 434                 return komi;
 435         else
 436                 return min_komi;
 437 }
 438
 439 static floating_t
 440 adaptive_permove(struct uct_dynkomi *d, struct board *b, struct tree *tree)
 441 {
 442         /* We do not use extra komi at the game end - we are not
 443          * to fool ourselves at this point. */
 444         if (board_estimated_moves_left(b) <= MIN_MOVES_LEFT) {
 445                 tree->use_extra_komi = false;
 446                 return 0;
 447         }
 448         struct dynkomi_adaptive *a = d->data;
 449         enum stone color = stone_other(tree->root_color);
 450         if (DEBUGL(3))
 451                 fprintf(stderr, "m %d/%d ekomi %f permove %f/%d\n",
 452                         b->moves, a->lead_moves, tree->extra_komi,
 453                         d->score.value, d->score.playouts);
 454
 455         if (b->moves <= a->lead_moves)
 456                 return bounded_komi(a, b, color,
 457                                     board_effective_handicap(b, 7 /* XXX */),
 458                                     a->max_losing_komi);
 459
 460         floating_t komi = a->indicator(d, b, tree, color);
 461         if (DEBUGL(3))
 462                 fprintf(stderr, "dynkomi: %f -> %f\n", tree->extra_komi, komi);
 463         return bounded_komi(a, b, color, komi, a->max_losing_komi);
 464 }
 465
 466 static floating_t
 467 adaptive_persim(struct uct_dynkomi *d, struct board *b, struct tree *tree, struct tree_node *node)
 468 {
 469         return tree->extra_komi;
 470 }
 471
 472 struct uct_dynkomi *
 473 uct_dynkomi_init_adaptive(struct uct *u, char *arg, struct board *b)
 474 {
 475         struct uct_dynkomi *d = calloc2(1, sizeof(*d));
 476         d->uct = u;
 477         d->permove = adaptive_permove;
 478         d->persim = adaptive_persim;
 479         d->done = generic_done;
 480
 481         struct dynkomi_adaptive *a = calloc2(1, sizeof(*a));
 482         d->data = a;
 483
 484         a->lead_moves = board_large(b) ? 20 : 4; // XXX
 485         a->max_losing_komi = 30;
 486         a->losing_komi_stop = 1.0f;
 487         a->indicator = komi_by_value;
 488
 489         a->adapter = adapter_sigmoid;
 490         a->adapt_rate = -18;
 491         a->adapt_phase = 0.65;
 492         a->adapt_moves = 200;
 493         a->adapt_dir = -0.5;
 494
 495         a->zone_red = 0.45;
 496         a->zone_green = 0.50;
 497         a->score_step = 1;
 498         a->use_komi_ratchet = true;
 499         a->komi_ratchet_maxage = 0;
 500         a->komi_ratchet = 1000;
 501
 502         if (arg) {
 503                 char *optspec, *next = arg;
 504                 while (*next) {
 505                         optspec = next;
 506                         next += strcspn(next, ":");
 507                         if (*next) { *next++ = 0; } else { *next = 0; }
 508
 509                         char *optname = optspec;
 510                         char *optval = strchr(optspec, '=');
 511                         if (optval) *optval++ = 0;
 512
 513                         if (!strcasecmp(optname, "lead_moves") && optval) {
 514                                 /* Do not adjust komi adaptively for first
 515                                  * N moves. */
 516                                 a->lead_moves = atoi(optval);
 517                         } else if (!strcasecmp(optname, "max_losing_komi") && optval) {
 518                                 a->max_losing_komi = atof(optval);
 519                         } else if (!strcasecmp(optname, "losing_komi_stop") && optval) {
 520                                 a->losing_komi_stop = atof(optval);
 521                         } else if (!strcasecmp(optname, "indicator")) {
 522                                 /* Adaptatation indicator - how to decide
 523                                  * the adaptation rate and direction. */
 524                                 if (!strcasecmp(optval, "value")) {
 525                                         /* Winrate w/ komi so far. */
 526                                         a->indicator = komi_by_value;
 527                                 } else if (!strcasecmp(optval, "score")) {
 528                                         /* Expected score w/ current komi. */
 529                                         a->indicator = komi_by_score;
 530                                 } else {
 531                                         fprintf(stderr, "UCT: Invalid indicator %s\n", optval);
 532                                         exit(1);
 533                                 }
 534
 535                                 /* value indicator settings */
 536                         } else if (!strcasecmp(optname, "zone_red") && optval) {
 537                                 a->zone_red = atof(optval);
 538                         } else if (!strcasecmp(optname, "zone_green") && optval) {
 539                                 a->zone_green = atof(optval);
 540                         } else if (!strcasecmp(optname, "score_step") && optval) {
 541                                 a->score_step = atoi(optval);
 542                         } else if (!strcasecmp(optname, "score_step_byavg") && optval) {
 543                                 a->score_step_byavg = atof(optval);
 544                         } else if (!strcasecmp(optname, "use_komi_ratchet")) {
 545                                 a->use_komi_ratchet = !optval || atoi(optval);
 546                         } else if (!strcasecmp(optname, "losing_komi_ratchet")) {
 547                                 a->losing_komi_ratchet = !optval || atoi(optval);
 548                         } else if (!strcasecmp(optname, "komi_ratchet_age") && optval) {
 549                                 a->komi_ratchet_maxage = atoi(optval);
 550
 551                                 /* score indicator settings */
 552                         } else if (!strcasecmp(optname, "adapter") && optval) {
 553                                 /* Adaptatation method. */
 554                                 if (!strcasecmp(optval, "sigmoid")) {
 555                                         a->adapter = adapter_sigmoid;
 556                                 } else if (!strcasecmp(optval, "linear")) {
 557                                         a->adapter = adapter_linear;
 558                                 } else {
 559                                         fprintf(stderr, "UCT: Invalid adapter %s\n", optval);
 560                                         exit(1);
 561                                 }
 562                         } else if (!strcasecmp(optname, "adapt_base") && optval) {
 563                                 /* Adaptation base rate; see above. */
 564                                 a->adapt_base = atof(optval);
 565                         } else if (!strcasecmp(optname, "adapt_rate") && optval) {
 566                                 /* Adaptation slope; see above. */
 567                                 a->adapt_rate = atof(optval);
 568                         } else if (!strcasecmp(optname, "adapt_phase") && optval) {
 569                                 /* Adaptation phase shift; see above. */
 570                                 a->adapt_phase = atof(optval);
 571                         } else if (!strcasecmp(optname, "adapt_moves") && optval) {
 572                                 /* Adaptation move amount; see above. */
 573                                 a->adapt_moves = atoi(optval);
 574                         } else if (!strcasecmp(optname, "adapt_aport")) {
 575                                 a->adapt_aport = !optval || atoi(optval);
 576                         } else if (!strcasecmp(optname, "adapt_dir") && optval) {
 577                                 /* Adaptation direction vector; see above. */
 578                                 a->adapt_dir = atof(optval);
 579
 580                         } else {
 581                                 fprintf(stderr, "uct: Invalid dynkomi argument %s or missing value\n", optname);
 582                                 exit(1);
 583                         }
 584                 }
 585         }
 586
 587         return d;
 588 }