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https://github.com/sockspls/badfish
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Retire outdated aspiration search code
Signed-off-by: Marco Costalba <mcostalba@gmail.com>
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1 changed files with 14 additions and 61 deletions
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@ -53,26 +53,6 @@ namespace {
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/// Types
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/// Types
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// IterationInfoType stores search results for each iteration
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//
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// Because we use relatively small (dynamic) aspiration window,
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// there happens many fail highs and fail lows in root. And
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// because we don't do researches in those cases, "value" stored
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// here is not necessarily exact. Instead in case of fail high/low
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// we guess what the right value might be and store our guess
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// as a "speculated value" and then move on. Speculated values are
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// used just to calculate aspiration window width, so also if are
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// not exact is not big a problem.
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struct IterationInfoType {
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IterationInfoType(Value v = Value(0), Value sv = Value(0))
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: value(v), speculatedValue(sv) {}
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Value value, speculatedValue;
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};
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// The BetaCounterType class is used to order moves at ply one.
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// The BetaCounterType class is used to order moves at ply one.
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// Apart for the first one that has its score, following moves
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// Apart for the first one that has its score, following moves
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// normally have score -VALUE_INFINITE, so are ordered according
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// normally have score -VALUE_INFINITE, so are ordered according
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@ -213,7 +193,7 @@ namespace {
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BetaCounterType BetaCounter;
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BetaCounterType BetaCounter;
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// Scores and number of times the best move changed for each iteration
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// Scores and number of times the best move changed for each iteration
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IterationInfoType IterationInfo[PLY_MAX_PLUS_2];
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Value ValueByIteration[PLY_MAX_PLUS_2];
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int BestMoveChangesByIteration[PLY_MAX_PLUS_2];
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int BestMoveChangesByIteration[PLY_MAX_PLUS_2];
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// Search window management
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// Search window management
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@ -716,7 +696,7 @@ namespace {
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TT.new_search();
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TT.new_search();
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H.clear();
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H.clear();
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init_ss_array(ss);
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init_ss_array(ss);
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IterationInfo[1] = IterationInfoType(rml.get_move_score(0), rml.get_move_score(0));
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ValueByIteration[1] = rml.get_move_score(0);
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Iteration = 1;
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Iteration = 1;
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// Is one move significantly better than others after initial scoring ?
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// Is one move significantly better than others after initial scoring ?
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@ -740,16 +720,16 @@ namespace {
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// Calculate dynamic search window based on previous iterations
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// Calculate dynamic search window based on previous iterations
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Value alpha, beta;
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Value alpha, beta;
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if (MultiPV == 1 && Iteration >= 6 && abs(IterationInfo[Iteration - 1].value) < VALUE_KNOWN_WIN)
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if (MultiPV == 1 && Iteration >= 6 && abs(ValueByIteration[Iteration - 1]) < VALUE_KNOWN_WIN)
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{
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{
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int prevDelta1 = IterationInfo[Iteration - 1].speculatedValue - IterationInfo[Iteration - 2].speculatedValue;
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int prevDelta1 = ValueByIteration[Iteration - 1] - ValueByIteration[Iteration - 2];
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int prevDelta2 = IterationInfo[Iteration - 2].speculatedValue - IterationInfo[Iteration - 3].speculatedValue;
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int prevDelta2 = ValueByIteration[Iteration - 2] - ValueByIteration[Iteration - 3];
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AspirationDelta = Max(abs(prevDelta1) + abs(prevDelta2) / 2, 16);
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AspirationDelta = Max(abs(prevDelta1) + abs(prevDelta2) / 2, 16);
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AspirationDelta = (AspirationDelta + 7) / 8 * 8; // Round to match grainSize
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AspirationDelta = (AspirationDelta + 7) / 8 * 8; // Round to match grainSize
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alpha = Max(IterationInfo[Iteration - 1].value - AspirationDelta, -VALUE_INFINITE);
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alpha = Max(ValueByIteration[Iteration - 1] - AspirationDelta, -VALUE_INFINITE);
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beta = Min(IterationInfo[Iteration - 1].value + AspirationDelta, VALUE_INFINITE);
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beta = Min(ValueByIteration[Iteration - 1] + AspirationDelta, VALUE_INFINITE);
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}
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}
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else
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else
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{
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{
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@ -768,32 +748,7 @@ namespace {
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break; // Value cannot be trusted. Break out immediately!
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break; // Value cannot be trusted. Break out immediately!
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//Save info about search result
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//Save info about search result
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Value speculatedValue;
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ValueByIterationInfo[Iteration] = value;
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bool fHigh = false;
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bool fLow = false;
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Value delta = value - IterationInfo[Iteration - 1].value;
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if (value >= beta)
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{
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assert(delta > 0);
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fHigh = true;
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speculatedValue = value + delta;
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BestMoveChangesByIteration[Iteration] += 2; // Allocate more time
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}
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else if (value <= alpha)
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{
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assert(value == alpha);
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assert(delta < 0);
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fLow = true;
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speculatedValue = value + delta;
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BestMoveChangesByIteration[Iteration] += 3; // Allocate more time
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} else
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speculatedValue = value;
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speculatedValue = Min(Max(speculatedValue, -VALUE_INFINITE), VALUE_INFINITE);
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IterationInfo[Iteration] = IterationInfoType(value, speculatedValue);
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// Drop the easy move if it differs from the new best move
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// Drop the easy move if it differs from the new best move
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if (ss[0].pv[0] != EasyMove)
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if (ss[0].pv[0] != EasyMove)
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@ -813,15 +768,13 @@ namespace {
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// Stop search early when the last two iterations returned a mate score
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// Stop search early when the last two iterations returned a mate score
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if ( Iteration >= 6
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if ( Iteration >= 6
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&& abs(IterationInfo[Iteration].value) >= abs(VALUE_MATE) - 100
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&& abs(ValueByIteration[Iteration]) >= abs(VALUE_MATE) - 100
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&& abs(IterationInfo[Iteration-1].value) >= abs(VALUE_MATE) - 100)
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&& abs(ValueByIteration[Iteration-1]) >= abs(VALUE_MATE) - 100)
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stopSearch = true;
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stopSearch = true;
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// Stop search early if one move seems to be much better than the rest
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// Stop search early if one move seems to be much better than the rest
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int64_t nodes = nodes_searched();
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int64_t nodes = nodes_searched();
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if ( Iteration >= 8
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if ( Iteration >= 8
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&& !fLow
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&& !fHigh
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&& EasyMove == ss[0].pv[0]
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&& EasyMove == ss[0].pv[0]
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&& ( ( rml.get_move_cumulative_nodes(0) > (nodes * 85) / 100
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&& ( ( rml.get_move_cumulative_nodes(0) > (nodes * 85) / 100
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&& current_search_time() > MaxSearchTime / 16)
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&& current_search_time() > MaxSearchTime / 16)
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@ -983,7 +936,7 @@ namespace {
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// for time managment: When Problem is true, we try to complete the
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// for time managment: When Problem is true, we try to complete the
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// current iteration before playing a move.
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// current iteration before playing a move.
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Problem = ( Iteration >= 2
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Problem = ( Iteration >= 2
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&& value <= IterationInfo[Iteration - 1].value - ProblemMargin);
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&& value <= ValueByIteration[Iteration - 1] - ProblemMargin);
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if (Problem && StopOnPonderhit)
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if (Problem && StopOnPonderhit)
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StopOnPonderhit = false;
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StopOnPonderhit = false;
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@ -1132,7 +1085,7 @@ namespace {
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// Reset the global variable Problem to false if the value isn't too
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// Reset the global variable Problem to false if the value isn't too
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// far below the final value from the last iteration.
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// far below the final value from the last iteration.
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if (value > IterationInfo[Iteration - 1].value - NoProblemMargin)
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if (value > ValueByIteration[Iteration - 1] - NoProblemMargin)
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Problem = false;
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Problem = false;
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}
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}
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else // MultiPV > 1
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else // MultiPV > 1
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@ -1366,7 +1319,7 @@ namespace {
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// (from the computer's point of view) since the previous iteration.
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// (from the computer's point of view) since the previous iteration.
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if ( ply == 1
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if ( ply == 1
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&& Iteration >= 2
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&& Iteration >= 2
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&& -value <= IterationInfo[Iteration-1].value - ProblemMargin)
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&& -value <= ValueByIteration[Iteration-1] - ProblemMargin)
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Problem = true;
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Problem = true;
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}
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}
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@ -2224,7 +2177,7 @@ namespace {
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// (from the computer's point of view) since the previous iteration.
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// (from the computer's point of view) since the previous iteration.
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if ( sp->ply == 1
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if ( sp->ply == 1
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&& Iteration >= 2
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&& Iteration >= 2
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&& -value <= IterationInfo[Iteration-1].value - ProblemMargin)
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&& -value <= ValueByIteration[Iteration-1] - ProblemMargin)
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Problem = true;
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Problem = true;
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}
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}
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lock_release(&(sp->lock));
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lock_release(&(sp->lock));
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