次の通り変更すると学習しました．
12-13行目をコメントアウト
32行目のfalseをtrueに変更
%迷路の作成
GW = createGridWorld(8,8);
GW.CurrentState = '[2,1]';
GW.TerminalStates = '[8,8]';
GW.ObstacleStates = ["[3,3]";"[3,4]";"[3,5]";"[3,6]";"[3,7]";"[4,3]";"[7,3]";"[6,3]";"[5,3]"];
updateStateTranstionForObstacles(GW)
GW.T(state2idx(GW,"[2,4]"),:,:) = 0;
GW.T(state2idx(GW,"[2,4]"),state2idx(GW,"[4,4]"),:) = 1;
nS = numel(GW.States);
nA = numel(GW.Actions);
GW.R = -1*ones(nS,nS,nA);
%GW.R(state2idx(GW,"[4,2]"),state2idx(GW,"[5,2]"),:) = 5; %--- ?
%GW.R(state2idx(GW,"[8,3]"),state2idx(GW,"[8,4]"),:) = 5; %--- ?
GW.R(:,state2idx(GW,GW.TerminalStates),:) = 10;
%環境の読み込み
env = rlMDPEnv(GW)
env.ResetFcn = @() 2;
rng(0)
%Q学習
qTable = rlTable(getObservationInfo(env),getActionInfo(env));
qRepresentation = rlQValueRepresentation(qTable,getObservationInfo(env),getActionInfo(env));
qRepresentation.Options.LearnRate = 1;
agentOpts = rlQAgentOptions;
agentOpts.EpsilonGreedyExploration.Epsilon = .04;
qAgent = rlQAgent(qRepresentation,agentOpts);
trainOpts = rlTrainingOptions;
trainOpts.MaxStepsPerEpisode = 50;
trainOpts.MaxEpisodes= 200;
trainOpts.StopTrainingCriteria = "AverageReward";
trainOpts.StopTrainingValue = 101;
trainOpts.ScoreAveragingWindowLength = 30;
doTraining = true; %--- trueにしないと以下のif文に入らない
if doTraining
% Train the agent.
trainingStats = train(qAgent,env,trainOpts);
end
%結果の描画
plot(env)
env.Model.Viewer.ShowTrace = true;
env.Model.Viewer.clearTrace;
sim(qAgent,env)
