use of ga.SimpleRMHC in project SimpleAsteroids by ljialin.
the class AgentEvaluator method evaluate.
@Override
public double evaluate(int[] solution) {
// at thias point,
System.out.println("Params are:");
System.out.println(searchSpace.report(solution));
// can also override parameters by setting them directly as follows:
BattleGameParameters.loss = 0.996;
BattleGameParameters.thrust = 3;
// BattleGameParameters.shipSize *= 2;
// BattleGameParameters.damageRadius *= 2;
SpaceBattleLinkStateTwoPlayer linkState = new SpaceBattleLinkStateTwoPlayer();
StateObservationMulti multi = linkState;
GameActionSpaceAdapterMulti.useHeuristic = false;
// DefaultMutator.totalRandomChaosMutation = false;
ElapsedCpuTimer timer = new ElapsedCpuTimer();
// AbstractMultiPlayer player2;
int idPlayer1 = 0;
int idPlayer2 = 1;
// player2 = new controllers.multiPlayer.discountOLMCTS.Agent(linkState, timer, idPlayer2);
// try the evolutionary players
int nResamples = 2;
EvoAlg evoAlg = new SimpleRMHC(nResamples);
double kExplore = searchSpace.getExplorationFactor(solution);
int nNeighbours = 100;
int nEvals = 100;
evoAlg = new NTupleBanditEA(kExplore, nNeighbours);
evoAlg = new SlidingMeanEDA().setHistoryLength(searchSpace.getHistoryLength(solution));
Agent evoAgent = new controllers.multiPlayer.ea.Agent(linkState, timer, evoAlg, idPlayer1, nEvals);
evoAgent.setDiscountFactor(searchSpace.getDiscountFactor(solution));
evoAgent.sequenceLength = searchSpace.getRolloutLength(solution);
// evoAgent.di
// EvoAlg evoAlg2 = new CompactSlidingModelGA().setHistoryLength(2);
EvoAlg evoAlg2 = new SlidingMeanEDA().setHistoryLength(2);
Agent player2 = new controllers.multiPlayer.ea.Agent(linkState, timer, evoAlg2, idPlayer2, nEvals);
player2.sequenceLength = 5;
// player2 = new controllers.multiPlayer.ea.Agent(linkState, timer, new SimpleRMHC(nResamples), idPlayer2, nEvals);
// player1 = new controllers.multiPlayer.smlrand.Agent();
// EvoAlg evoAlg2 = new SimpleRMHC(2);
// player1 = new controllers.multiPlayer.ea.Agent(linkState, timer, evoAlg2, idPlayer1, nEvals);
// in milliseconds
int thinkingTime = 10;
int delay = 10;
// player = new controllers.singlePlayer.sampleRandom.Agent(stateObs, timer);
// check that we can play the game
Random random = new Random();
int nSteps = 500;
ElapsedTimer t = new ElapsedTimer();
StatSummary sst1 = new StatSummary("Player 1 Elapsed Time");
StatSummary sst2 = new StatSummary("Player 2 Elapsed Time");
StatSummary ssTicks1 = new StatSummary("Player 1 nTicks");
StatSummary ssTicks2 = new StatSummary("Player 2 nTicks");
for (int i = 0; i < nSteps && !linkState.isGameOver(); i++) {
linkState.state = linkState.state.copyState();
timer = new ElapsedCpuTimer();
timer.setMaxTimeMillis(thinkingTime);
ElapsedTimer t1 = new ElapsedTimer();
// keep track of the number of game ticks used by each algorithm
int ticks;
ticks = SpaceBattleLinkStateTwoPlayer.nTicks;
Types.ACTIONS action1 = evoAgent.act(multi.copy(), timer);
sst1.add(t1.elapsed());
ticks = SpaceBattleLinkStateTwoPlayer.nTicks - ticks;
ssTicks1.add(ticks);
// System.out.println("Player 1 Ticks = " + ticks);
ElapsedTimer t2 = new ElapsedTimer();
ticks = SpaceBattleLinkStateTwoPlayer.nTicks;
Types.ACTIONS action2 = player2.act(multi.copy(), timer);
sst2.add(t2.elapsed());
ticks = SpaceBattleLinkStateTwoPlayer.nTicks - ticks;
ssTicks2.add(ticks);
// System.out.println("Player 2 Ticks = " + ticks);
multi.advance(new Types.ACTIONS[] { action1, action2 });
}
System.out.println(multi.getGameScore());
System.out.println(multi.isGameOver());
// System.out.println(SingleTreeNode.rollOutScores);
System.out.println(sst1);
System.out.println(sst2);
System.out.println(ssTicks1);
System.out.println(ssTicks2);
double score = multi.getGameScore(0);
System.out.println("Game score: " + score);
if (score > 0)
return 1;
if (score < 0)
return -1;
return 0;
}
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