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Briefly/rldemo_paper_code

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Copy_2_of_createPPONetworks.m 964 Bytes
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Briefly 提交于 2023-09-10 17:56 . 添加所有文件
criticNetwork = [
featureInputLayer(numObservations,'Normalization','none','Name','observations')
fullyConnectedLayer(128,'Name','fc1')
reluLayer('Name','relu1')
fullyConnectedLayer(200,'Name','fc2')
reluLayer('Name','relu2')
fullyConnectedLayer(1,'Name','fc4')];
criticOptions = rlRepresentationOptions('LearnRate',1e-3,'GradientThreshold',1);
critic = rlValueRepresentation(criticNetwork,observationInfo,...
'Observation',{'observations'},criticOptions);
actorNetwork = [
featureInputLayer(numObservations,'Normalization','none','Name','observations')
fullyConnectedLayer(200,'Name','fc1')
reluLayer('Name','relu1')
fullyConnectedLayer(numActions, 'Name', 'out')
softmaxLayer('Name','actionProb')];
actorOptions = rlRepresentationOptions('LearnRate',2e-4,'GradientThreshold',1);
actor = rlStochasticActorRepresentation(actorNetwork,observationInfo,actionInfo,...
'Observation',{'observations'},actorOptions);
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