size_t DfpnSolver::MID(const DfpnBounds& maxBounds, DfpnHistory& history)
{
maxBounds.CheckConsistency();
SG_ASSERT(maxBounds.phi > 1);
SG_ASSERT(maxBounds.delta > 1);
++m_numMIDcalls;
size_t prevWork = 0;
SgEmptyBlackWhite colorToMove = GetColorToMove();
DfpnData data;
if (TTRead(data))
{
prevWork = data.m_work;
if (! maxBounds.GreaterThan(data.m_bounds))
// Estimated bounds are larger than we had
// anticipated. The calling state must have computed
// the max bounds with out of date information, so just
// return here without doing anything: the caller will
// now update to this new info and carry on.
return 0;
}
else
{
SgEmptyBlackWhite winner = SG_EMPTY;
if (TerminalState(colorToMove, winner))
{
++m_numTerminal;
DfpnBounds terminal;
if (colorToMove == winner)
DfpnBounds::SetToWinning(terminal);
else
{
SG_ASSERT(SgOppBW(colorToMove) == winner);
DfpnBounds::SetToLosing(terminal);
}
TTWrite(DfpnData(terminal, SG_NULLMOVE, 1));
return 1;
}
}
++m_generateMoves;
DfpnChildren children;
GenerateChildren(children.Children());
// Not thread safe: perhaps move into while loop below later...
std::vector<DfpnData> childrenData(children.Size());
for (size_t i = 0; i < children.Size(); ++i)
LookupData(childrenData[i], children, i);
// Index used for progressive widening
size_t maxChildIndex = ComputeMaxChildIndex(childrenData);
SgHashCode currentHash = Hash();
SgMove bestMove = SG_NULLMOVE;
DfpnBounds currentBounds;
size_t localWork = 1;
do
{
UpdateBounds(currentBounds, childrenData, maxChildIndex);
if (! maxBounds.GreaterThan(currentBounds))
break;
// Select most proving child
std::size_t bestIndex = 999999;
DfpnBoundType delta2 = DfpnBounds::INFTY;
SelectChild(bestIndex, delta2, childrenData, maxChildIndex);
bestMove = children.MoveAt(bestIndex);
// Compute maximum bound for child
const DfpnBounds childBounds(childrenData[bestIndex].m_bounds);
DfpnBounds childMaxBounds;
childMaxBounds.phi = maxBounds.delta
- (currentBounds.delta - childBounds.phi);
childMaxBounds.delta = delta2 == DfpnBounds::INFTY ? maxBounds.phi :
std::min(maxBounds.phi,
std::max(delta2 + 1, DfpnBoundType(delta2 * (1.0 + m_epsilon))));
SG_ASSERT(childMaxBounds.GreaterThan(childBounds));
if (delta2 != DfpnBounds::INFTY)
m_deltaIncrease.Add(float(childMaxBounds.delta-childBounds.delta));
// Recurse on best child
PlayMove(bestMove);
history.Push(bestMove, currentHash);
localWork += MID(childMaxBounds, history);
history.Pop();
UndoMove();
// Update bounds for best child
LookupData(childrenData[bestIndex], children, bestIndex);
// Compute some stats when find winning move
if (childrenData[bestIndex].m_bounds.IsLosing())
{
m_moveOrderingIndex.Add(float(bestIndex));
m_moveOrderingPercent.Add(float(bestIndex)
/ (float)childrenData.size());
m_totalWastedWork += prevWork + localWork
- childrenData[bestIndex].m_work;
}
else if (childrenData[bestIndex].m_bounds.IsWinning())
maxChildIndex = ComputeMaxChildIndex(childrenData);
} while (! CheckAbort());
// Find the most delaying move for losing states, and the smallest
// winning move for winning states.
if (currentBounds.IsSolved())
{
if (currentBounds.IsLosing())
{
std::size_t maxWork = 0;
for (std::size_t i = 0; i < children.Size(); ++i)
{
if (childrenData[i].m_work > maxWork)
{
maxWork = childrenData[i].m_work;
bestMove = children.MoveAt(i);
}
}
}
else
{
std::size_t minWork = DfpnBounds::INFTY;
for (std::size_t i = 0; i < children.Size(); ++i)
{
if (childrenData[i].m_bounds.IsLosing()
&& childrenData[i].m_work < minWork)
{
minWork = childrenData[i].m_work;
bestMove = children.MoveAt(i);
}
}
}
}
// Store search results
TTWrite(DfpnData(currentBounds, bestMove, localWork + prevWork));
return localWork;
}
void DfpnSolver::LookupData(DfpnData& data, const DfpnChildren& children,
std::size_t childIndex) const
{
const SgMove move = children.MoveAt(childIndex);
LookupChildData(move, data);
}
