Changeset 13657 for trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/MctsSymbolicRegression/MctsSymbolicRegressionStatic.cs
 Timestamp:
 03/07/16 12:50:15 (8 years ago)
 File:

 1 edited
Legend:
 Unmodified
 Added
 Removed

trunk/sources/HeuristicLab.Algorithms.DataAnalysis/3.4/MctsSymbolicRegression/MctsSymbolicRegressionStatic.cs
r13652 r13657 262 262 alglib.minlmstate state; 263 263 alglib.minlmreport rep = null; 264 alglib.minlmcreatevj(y.Length, optConsts, out state); 264 alglib.minlmcreatevj(y.Length, optConsts, out state); 265 265 alglib.minlmsetcond(state, 0.0, epsF, 0.0, nIters); 266 266 //alglib.minlmsetgradientcheck(state, 0.000001); … … 333 333 double c = mctsState.c; 334 334 double q = 0; 335 double deltaQ = 0; 336 double deltaSqrQ = 0; 337 int deltaVisits = 0; 335 338 bool success = false; 336 339 do { 337 340 automaton.Reset(); 338 success = TryTreeSearchRec(rand, tree, c, automaton, eval, bestChildrenBuf, out q );341 success = TryTreeSearchRec(rand, tree, c, automaton, eval, bestChildrenBuf, out q, out deltaQ, out deltaSqrQ, out deltaVisits); 339 342 mctsState.totalRollouts++; 340 343 } while (!success && !tree.done); … … 347 350 // see ConstraintHandler.cs for more info 348 351 private static bool TryTreeSearchRec(IRandom rand, Tree tree, double c, Automaton automaton, Func<byte[], int, double> eval, List<Tree> bestChildrenBuf, 349 out double q) { 352 out double q, // quality of the expression 353 out double deltaQ, out double deltaSqrQ, out int deltaVisits // the updates for total quality and number of visits (can be negative if branches have been fully explored) 354 ) { 350 355 Tree selectedChild = null; 351 356 Contract.Assert(tree.state == automaton.CurrentState); … … 360 365 automaton.GetCode(out code, out nParams); 361 366 q = eval(code, nParams); 362 tree.visits ++;367 tree.visits += 1; 363 368 tree.sumQuality += q; 369 tree.sumSqrQuality += q * q; 370 deltaQ = q; 371 deltaVisits = 1; 372 deltaSqrQ = q * q; 364 373 return true; // we reached a final state 365 374 } else { … … 371 380 // stuck in a dead end (no final state and no allowed follow states) 372 381 q = 0; 382 deltaQ = 0; 383 deltaSqrQ = 0.0; 384 deltaVisits = 0; 373 385 tree.done = true; 374 386 tree.children = null; … … 380 392 tree.children[i] = new Tree() { children = null, done = false, state = possibleFollowStates[i], visits = 0 }; 381 393 382 selectedChild = SelectFinalOrRandom(automaton, tree, rand);394 selectedChild = nFs > 1 ? SelectFinalOrRandom(automaton, tree, rand) : tree.children[0]; 383 395 } 384 396 } else { 385 397 // tree.children != null 386 398 // UCT selection within tree 387 selectedChild = SelectUct(tree, rand, c, bestChildrenBuf);399 selectedChild = tree.children.Length > 1 ? SelectUctTuned(tree, rand, c, bestChildrenBuf) : tree.children[0]; 388 400 } 389 401 // make selected step and recurse 390 402 automaton.Goto(selectedChild.state); 391 var success = TryTreeSearchRec(rand, selectedChild, c, automaton, eval, bestChildrenBuf, out q); 403 var success = TryTreeSearchRec(rand, selectedChild, c, automaton, eval, bestChildrenBuf, 404 out q, out deltaQ, out deltaSqrQ, out deltaVisits); 392 405 if (success) { 393 406 // only update if successful 394 tree.sumQuality += q; 395 tree.visits++; 396 } 397 398 // tree.done = tree.children.All(ch => ch.done); 399 tree.done = true; for (int i = 0; i < tree.children.Length && tree.done; i++) tree.done = tree.children[i].done; 400 if (tree.done) { 407 tree.sumQuality += deltaQ; 408 tree.sumSqrQuality += deltaSqrQ; 409 tree.visits += deltaVisits; 410 } 411 412 if (tree.children.All(ch => ch.done)) { 413 tree.done = true; 414 // update parent nodes to remove information from this branch 415 if (tree.children.Length > 1) { 416 deltaQ = (tree.sumQuality  deltaQ); 417 deltaSqrQ = (tree.sumSqrQuality  deltaSqrQ); 418 deltaVisits = (tree.visits  deltaVisits); 419 } 401 420 tree.children = null; // cut off the subbranch if it has been fully explored 402 // TODO: update all qualities and visits to remove the information gained from this whole branch403 421 } 404 422 return success; … … 437 455 } 438 456 457 private static Tree SelectUctTuned(Tree tree, IRandom rand, double c, List<Tree> bestChildrenBuf) { 458 // determine total tries of still active children 459 int totalTries = 0; 460 bestChildrenBuf.Clear(); 461 for (int i = 0; i < tree.children.Length; i++) { 462 var ch = tree.children[i]; 463 if (ch.done) continue; 464 if (ch.visits == 0) bestChildrenBuf.Add(ch); 465 else totalTries += tree.children[i].visits; 466 } 467 // if there are unvisited children select a random child 468 if (bestChildrenBuf.Any()) { 469 return bestChildrenBuf[rand.Next(bestChildrenBuf.Count)]; 470 } 471 Contract.Assert(totalTries > 0); // the tree is not done yet so there is at least on child that is not done 472 double logTotalTries = Math.Log(totalTries); 473 var bestQ = double.NegativeInfinity; 474 for (int i = 0; i < tree.children.Length; i++) { 475 var ch = tree.children[i]; 476 if (ch.done) continue; 477 var varianceBound = ch.QualityVariance + Math.Sqrt(2.0 * logTotalTries / ch.visits); 478 if (varianceBound > 0.25) varianceBound = 0.25; 479 var childQ = ch.AverageQuality + c * Math.Sqrt(logTotalTries / ch.visits * varianceBound); 480 if (childQ > bestQ) { 481 bestChildrenBuf.Clear(); 482 bestChildrenBuf.Add(ch); 483 bestQ = childQ; 484 } else if (childQ >= bestQ) { 485 bestChildrenBuf.Add(ch); 486 } 487 } 488 return bestChildrenBuf[rand.Next(bestChildrenBuf.Count)]; 489 } 490 439 491 private static Tree SelectFinalOrRandom(Automaton automaton, Tree tree, IRandom rand) { 440 492 // if one of the new children leads to a final state then go there
Note: See TracChangeset
for help on using the changeset viewer.