// experiments with 0, 10, ..., 100 differential heuristics
void RunExperiments1(ScenarioLoader *sl)
{
std::vector<graphState> aPath;
Map *m = new Map(sl->GetNthExperiment(0).GetMapName());
m->Scale(sl->GetNthExperiment(0).GetXScale(),
sl->GetNthExperiment(0).GetYScale());
Graph *g = GraphSearchConstants::GetGraph(m);
GraphDistanceHeuristic diffHeuristic(g);
diffHeuristic.SetPlacement(kAvoidPlacement);
GraphEnvironment gEnv(g, &diffHeuristic);
gEnv.SetDirected(true);
TemplateAStar<graphState, graphMove, GraphEnvironment> taNew;
for (int z = 0; z <= 10; z++)
{
for (int x = 0; x < sl->GetNumExperiments(); x++)
{
Experiment e = sl->GetNthExperiment(x);
graphState start, goal;
start = m->GetNodeNum(e.GetStartX(), e.GetStartY());
goal = m->GetNodeNum(e.GetGoalX(), e.GetGoalY());
Timer t;
t.StartTimer();
taNew.GetPath(&gEnv, start, goal, aPath);
t.EndTimer();
printf("%d\t%d\t%lld\t%f\n", e.GetBucket(), diffHeuristic.GetNumHeuristics(), taNew.GetNodesExpanded(), t.GetElapsedTime());
}
for (int x = 0; x < 10; x++)
diffHeuristic.AddHeuristic();
}
exit(0);
}
bool MySearchUnit::makeMove(MapProvider *mp, reservationProvider *rp, AbsMapSimulationInfo *simInfo, tDirection &res)
{
if (getCachedMove(res))
return true;
Map *map = mp->GetMap();
MapAbstraction *aMap = mp->GetMapAbstraction();
PublicUnitInfo<xyLoc,tDirection,AbsMapEnvironment> pui;
// if we have a cache to be used, use it!
if (spread_cache)
{
addPathToCache(spread_cache);
node *next_start = spread_cache->tail()->n;
int targx, targy;
simInfo->GetPublicUnitInfo( targetUnit, pui );
xyLoc l = pui.currentState;
targx = l.x;
targy = l.y;
// Get a path by path-planning
node *to = aMap->GetAbstractGraph(0)->GetNode(map->GetNodeNum(targx, targy));
s_algorithm->setTargets(mp->GetMapAbstraction(), next_start, to, rp);
delete spread_cache;
spread_cache = 0;
res = moves.back();
moves.pop_back();
return true;
}
// Check if we have a target defined
if (targetUnit < 0)
{
if (verbose)
printf("SU %s: No target, doing nothing\n", this->GetName());
return false;
}
// Get the position of the target
int targx, targy;
simInfo->GetPublicUnitInfo( targetUnit, pui );
xyLoc l = pui.currentState;
targx = l.x;
targy = l.y;
// Get a path by path-planning
Graph *g0 = aMap->GetAbstractGraph(0);
// Get the start and goal nodes
node *from = g0->GetNode(map->GetNodeNum(loc.x, loc.y));
node *to = g0->GetNode(map->GetNodeNum(targx, targy));
if (from == to)
{
if (!onTarget)
{
if (verbose)
{
printf("STAY ON TARGET!\n");
printf("%p target time %1.4f\n", (void*)this, targetTime);
}
if (simInfo)
targetTime = simInfo->GetSimulationTime();
}
onTarget = true;
// return kStay;
}
else
onTarget = false;
// if (verbose)
// printf("SU %p: Getting new path\n", this);
path *p;
p = algorithm->GetPath(aMap, from, to, rp);
nodesExpanded+=algorithm->GetNodesExpanded();
nodesTouched+=algorithm->GetNodesTouched();
// returning an empty path means there is no path between the start and goal
if (p == NULL)
{
if (verbose)
printf("SU %s: Path returned NIL\n", this->GetName());
return false;
}
if (!(p->n && p->next && p->next->n && (loc.x == p->n->GetLabelL(kFirstData))
&& (loc.y == p->n->GetLabelL(kFirstData+1))))
{
if (p->n)
std::cout << *p->n << std::endl;
if ((p->next) && (p->next->n))
std::cout << *p->next->n << std::endl;
std::cout << loc.x << ", " << loc.y << std::endl;
}
// a valid path must have at least 2 nodes and start where the unit is located
assert(p->n && p->next && p->next->n && (loc.x == p->n->GetLabelL(kFirstData))
&& (loc.y == p->n->GetLabelL(kFirstData+1)));
addPathToCache(p);
if (s_algorithm)
{
node *next_start = p->tail()->n;
s_algorithm->setTargets(mp->GetMapAbstraction(), next_start, to, rp);
}
delete p;
assert(moves.size() > 0);
res = moves.back();
moves.pop_back();
// if (verbose)
// printf("SU %p: returning move 0x%X\n", this, (int)dir);
return true;
}
// Compare:
// * 1 random lookup of 10 with BPMX
// * 1 random lookup of 10 without BPMX
// * octile
// * max of 10 heuristics
// * 1 lookup in compressed heuristic
void RunExperiments4(ScenarioLoader *sl)
{
std::vector<graphState> aPath;
Map *m = new Map(sl->GetNthExperiment(0).GetMapName());
m->Scale(sl->GetNthExperiment(0).GetXScale(),
sl->GetNthExperiment(0).GetYScale());
Graph *g = GraphSearchConstants::GetGraph(m);
GraphMapInconsistentHeuristic diffHeuristic(m, g);
diffHeuristic.SetPlacement(kAvoidPlacement);
diffHeuristic.SetMode(kRandom);
GraphEnvironment gEnv(g, &diffHeuristic);
gEnv.SetDirected(true);
TemplateAStar<graphState, graphMove, GraphEnvironment> taNew;
Timer t;
for (int x = 0; x < 10; x++)
diffHeuristic.AddHeuristic();
//diffHeuristic.SetNumUsedHeuristics(diffHeuristic.GetNumHeuristics()/10);
for (int x = 0; x < sl->GetNumExperiments(); x++)
{
Experiment e = sl->GetNthExperiment(x);
graphState start, goal;
start = m->GetNodeNum(e.GetStartX(), e.GetStartY());
goal = m->GetNodeNum(e.GetGoalX(), e.GetGoalY());
printf("%d\t", e.GetBucket());
// N memory -- 1 heuristic
diffHeuristic.SetNumUsedHeuristics(1);
diffHeuristic.SetMode(kMax);
taNew.SetUseBPMX(0);
t.StartTimer();
taNew.GetPath(&gEnv, start, goal, aPath);
t.EndTimer();
printf("%df\t%lld\t%f\t%f\t", diffHeuristic.GetNumHeuristics(),
taNew.GetNodesExpanded(), t.GetElapsedTime(), gEnv.GetPathLength(aPath));
// N memory -- 10 compressed heuristics no BPMX
diffHeuristic.SetNumUsedHeuristics(10);
diffHeuristic.SetMode(kCompressed);
taNew.SetUseBPMX(0);
t.StartTimer();
taNew.GetPath(&gEnv, start, goal, aPath);
t.EndTimer();
printf("%dc\t%lld\t%f\t%f\t", diffHeuristic.GetNumHeuristics(),
taNew.GetNodesExpanded(), t.GetElapsedTime(), gEnv.GetPathLength(aPath));
// N memory -- 10 compressed heuristics BPMX 1
diffHeuristic.SetNumUsedHeuristics(10);
diffHeuristic.SetMode(kCompressed);
taNew.SetUseBPMX(1);
t.StartTimer();
taNew.GetPath(&gEnv, start, goal, aPath);
t.EndTimer();
printf("%dcb1\t%lld\t%f\t%f\t", diffHeuristic.GetNumHeuristics(),
taNew.GetNodesExpanded(), t.GetElapsedTime(), gEnv.GetPathLength(aPath));
// N memory -- 10 compressed heuristics BPMX(°)
diffHeuristic.SetNumUsedHeuristics(10);
diffHeuristic.SetMode(kCompressed);
taNew.SetUseBPMX(1000);
t.StartTimer();
taNew.GetPath(&gEnv, start, goal, aPath);
t.EndTimer();
printf("%dcbi\t%lld\t%f\t%f\n", diffHeuristic.GetNumHeuristics(),
taNew.GetNodesExpanded(), t.GetElapsedTime(), gEnv.GetPathLength(aPath));
}
exit(0);
}
// Compare:
// * 10 N memory
// * 1...10 regular lookups
// * 1...9 random lookups with and without BPMX
// Only compare on longest problems
void RunExperiments5(ScenarioLoader *sl)
{
std::vector<graphState> aPath;
Map *m = new Map(sl->GetNthExperiment(0).GetMapName());
m->Scale(sl->GetNthExperiment(0).GetXScale(),
sl->GetNthExperiment(0).GetYScale());
Graph *g = GraphSearchConstants::GetGraph(m);
GraphMapInconsistentHeuristic diffHeuristic(m, g);
diffHeuristic.SetPlacement(kAvoidPlacement);
diffHeuristic.SetMode(kRandom);
GraphEnvironment gEnv(g, &diffHeuristic);
gEnv.SetDirected(true);
TemplateAStar<graphState, graphMove, GraphEnvironment> taNew;
Timer t;
for (int x = 0; x < 10; x++)
diffHeuristic.AddHeuristic();
//diffHeuristic.SetNumUsedHeuristics(diffHeuristic.GetNumHeuristics()/10);
for (int x = 0; x < sl->GetNumExperiments(); x++)
{
Experiment e = sl->GetNthExperiment(x);
if (e.GetBucket() != 127)
continue;
graphState start, goal;
start = m->GetNodeNum(e.GetStartX(), e.GetStartY());
goal = m->GetNodeNum(e.GetGoalX(), e.GetGoalY());
printf("%d\t", e.GetBucket());
for (int y = 1; y <= 10; y++)
{
// N memory -- 1 heuristic
diffHeuristic.SetNumUsedHeuristics(y);
diffHeuristic.SetMode(kMax);
taNew.SetUseBPMX(0);
t.StartTimer();
taNew.GetPath(&gEnv, start, goal, aPath);
t.EndTimer();
printf("%dmx\t%lld\t%f\t%f\t", diffHeuristic.GetNumUsedHeuristics(),
taNew.GetNodesExpanded(), t.GetElapsedTime(), gEnv.GetPathLength(aPath));
}
for (int y = 1; y <= 9; y++)
{
for (int z = 0; z <= 1; z++)
{
// N memory -- 1 heuristic
diffHeuristic.SetNumUsedHeuristics(y);
diffHeuristic.SetMode(kRandom);
taNew.SetUseBPMX(z);
t.StartTimer();
taNew.GetPath(&gEnv, start, goal, aPath);
t.EndTimer();
if (z==0)
printf("%drnd\t%lld\t%f\t%f\t", diffHeuristic.GetNumUsedHeuristics(),
taNew.GetNodesExpanded(), t.GetElapsedTime(), gEnv.GetPathLength(aPath));
else
printf("%drdb\t%lld\t%f\t%f\t", diffHeuristic.GetNumUsedHeuristics(),
taNew.GetNodesExpanded(), t.GetElapsedTime(), gEnv.GetPathLength(aPath));
}
}
printf("\n");
}
exit(0);
}
// Compare:
// * 10 N memory
// * 100 compressed heuristics
void RunExperiments(ScenarioLoader *sl, int memory)
{
std::vector<graphState> aPath;
Map *m = new Map(sl->GetNthExperiment(0).GetMapName());
m->Scale(sl->GetNthExperiment(0).GetXScale(),
sl->GetNthExperiment(0).GetYScale());
Graph *g = GraphSearchConstants::GetGraph(m);
GraphMapInconsistentHeuristic diffHeuristic(m, g);
GraphMapInconsistentHeuristic diff1(m, g);
diffHeuristic.SetPlacement(kAvoidPlacement);
diffHeuristic.SetMode(kRandom);
diff1.SetPlacement(kAvoidPlacement);
diff1.SetMode(kMax);
GraphEnvironment gEnv(g, &diffHeuristic);
gEnv.SetDirected(true);
GraphEnvironment gEnv2(g, &diff1);
gEnv2.SetDirected(true);
TemplateAStar<graphState, graphMove, GraphEnvironment> taNew;
Timer t;
for (int x = 0; x < memory; x++)
diffHeuristic.AddHeuristic();
diffHeuristic.SetNumUsedHeuristics(memory);
diffHeuristic.Compress();
diff1.AddHeuristic();
diff1.SetNumUsedHeuristics(1);
for (int x = 0; x < sl->GetNumExperiments(); x++)
{
Experiment e = sl->GetNthExperiment(x);
// if (e.GetBucket() < 100)
// continue;
graphState start, goal;
start = m->GetNodeNum(e.GetStartX(), e.GetStartY());
goal = m->GetNodeNum(e.GetGoalX(), e.GetGoalY());
printf("%d\t", e.GetBucket());
// 10N memory -- 10 heuristics
// diffHeuristic.SetNumUsedHeuristics(1);
// diffHeuristic.SetMode(kMax);
// taNew.SetUseBPMX(0);
//
// t.StartTimer();
// taNew.GetPath(&gEnv, start, goal, aPath);
// t.EndTimer();
// printf("%dmx\t%lld\t%f\t%f\t", diffHeuristic.GetNumUsedHeuristics(),
// taNew.GetNodesExpanded(), t.GetElapsedTime(), gEnv.GetPathLength(aPath));
// diffHeuristic.SetNumUsedHeuristics(memory);
// diffHeuristic.SetMode(kCompressed);
// taNew.SetUseBPMX(0);
// t.StartTimer();
// taNew.GetPath(&gEnv, start, goal, aPath);
// t.EndTimer();
// printf("%dcmp\t%lld\t%f\t%f\t", diffHeuristic.GetNumUsedHeuristics(),
// taNew.GetNodesExpanded(), t.GetElapsedTime(), gEnv.GetPathLength(aPath));
// diffHeuristic.SetNumUsedHeuristics(memory);
// diffHeuristic.SetMode(kCompressed);
taNew.SetUseBPMX(0);
t.StartTimer();
taNew.GetPath(&gEnv2, start, goal, aPath);
t.EndTimer();
printf("%dbx1\t%lld\t%f\t%f\t", diff1.GetNumUsedHeuristics(),
taNew.GetNodesExpanded(), t.GetElapsedTime(), gEnv.GetPathLength(aPath));
taNew.SetUseBPMX(0);
t.StartTimer();
taNew.GetPath(&gEnv, start, goal, aPath);
t.EndTimer();
printf("%dbx1\t%lld\t%f\t%f\t", diffHeuristic.GetNumUsedHeuristics(),
taNew.GetNodesExpanded(), t.GetElapsedTime(), gEnv.GetPathLength(aPath));
taNew.SetUseBPMX(1);
t.StartTimer();
taNew.GetPath(&gEnv, start, goal, aPath);
t.EndTimer();
printf("%dbx1\t%lld\t%f\t%f\t", diffHeuristic.GetNumUsedHeuristics(),
taNew.GetNodesExpanded(), t.GetElapsedTime(), gEnv.GetPathLength(aPath));
// diffHeuristic.SetNumUsedHeuristics(memory);
// diffHeuristic.SetMode(kCompressed);
// taNew.SetUseBPMX(1000);
//
// t.StartTimer();
// taNew.GetPath(&gEnv, start, goal, aPath);
// t.EndTimer();
// printf("%dbxi\t%lld\t%f\t%f\t", diffHeuristic.GetNumUsedHeuristics(),
// taNew.GetNodesExpanded(), t.GetElapsedTime(), gEnv.GetPathLength(aPath));
printf("\n");
fflush(stdout);
}
exit(0);
}
// experiments with 0, 10, ..., 100 differential heuristics
// 10% of them are used at each step with and without BPMX
void RunExperiments2(ScenarioLoader *sl)
{
std::vector<graphState> aPath;
Map *m = new Map(sl->GetNthExperiment(0).GetMapName());
m->Scale(sl->GetNthExperiment(0).GetXScale(),
sl->GetNthExperiment(0).GetYScale());
Graph *g = GraphSearchConstants::GetGraph(m);
GraphMapInconsistentHeuristic diffHeuristic(m, g);
diffHeuristic.SetPlacement(kAvoidPlacement);
diffHeuristic.SetMode(kRandom);
GraphEnvironment gEnv(g, &diffHeuristic);
gEnv.SetDirected(true);
TemplateAStar<graphState, graphMove, GraphEnvironment> taNew;
Timer t;
for (int z = 0; z < 1; z++)
{
for (int x = 0; x < 10; x++)
diffHeuristic.AddHeuristic();
diffHeuristic.SetNumUsedHeuristics(diffHeuristic.GetNumHeuristics()/10);
for (int x = 0; x < sl->GetNumExperiments(); x++)
{
Experiment e = sl->GetNthExperiment(x);
// if (e.GetBucket() != 127)
// { continue; }
graphState start, goal;
start = m->GetNodeNum(e.GetStartX(), e.GetStartY());
goal = m->GetNodeNum(e.GetGoalX(), e.GetGoalY());
// taNew.SetUseBPMX(false);
// Timer t;
// t.StartTimer();
// taNew.GetPath(&gEnv, start, goal, aPath);
// t.EndTimer();
//
// printf("%d\t%d.%d\t%d\t%f\t\t%f\n", e.GetBucket(), diffHeuristic.GetNumHeuristics(), diffHeuristic.GetNumHeuristics()/10,
// taNew.GetNodesExpanded(), t.GetElapsedTime(), gEnv.GetPathLength(aPath));
for (int y = 1; y < 6; y++)
{
if (y == 5)
taNew.SetUseBPMX(1000);
else
taNew.SetUseBPMX(y);
t.StartTimer();
taNew.GetPath(&gEnv, start, goal, aPath);
t.EndTimer();
printf("%d\t%d.%d\t%lld\t%f\tBPMX\t%f\n", e.GetBucket(), diffHeuristic.GetNumHeuristics(), y,
taNew.GetNodesExpanded(), t.GetElapsedTime(), gEnv.GetPathLength(aPath));
}
}
}
exit(0);
}
