An Error in LSTM Network Training Using Reinforcement Learning Toolbox

I wrote tthe following code for using LSTM,
for idx = 1:type
actorNetWork = [
imageInputLayer(obsSize,Normalization="none")
convolution2dLayer(8,16, ...
Stride=1,Padding=1,WeightsInitializer="he")
reluLayer
convolution2dLayer(4,8, ...
Stride=1,Padding="same",WeightsInitializer="he")
reluLayer
fullyConnectedLayer(256,WeightsInitializer="he")
reluLayer
fullyConnectedLayer(128,WeightsInitializer="he")
reluLayer
fullyConnectedLayer(64,WeightsInitializer="he")
reluLayer
fullyConnectedLayer(numAct)
softmaxLayer
];
actorNetWork = dlnetwork(actorNetWork);
criticNetwork = [
sequenceInputLayer(obsSize)
sequenceFoldingLayer('Name','fold')
convolution2dLayer(8,16, ...
Stride=1,Padding=1,WeightsInitializer="he")
reluLayer
convolution2dLayer(4,8, ...
Stride=1,Padding="same",WeightsInitializer="he")
reluLayer
fullyConnectedLayer(368,WeightsInitializer="he")
reluLayer
fullyConnectedLayer(256,WeightsInitializer="he")
reluLayer
sequenceUnfoldingLayer('Name','unfold')
flattenLayer('Name','flatten')
lstmLayer(64)
fullyConnectedLayer(1)];
lgraph = layerGraph(criticNetwork);
lgraph = connectLayers(lgraph,'fold/miniBatchSize','unfold/miniBatchSize');
actor(idx) = rlDiscreteCategoricalActor(actorNetWork,oinfo,ainfo);
critic(idx) = rlValueFunction(lgraph,oinfo);
end
opt = rlPPOAgentOptions(...
'ActorOptimizerOptions',actorOpts,...
'CriticOptimizerOptions',criticOpts,...
'ExperienceHorizon',128,...
'ClipFactor',0.2,...
'EntropyLossWeight',0.1,...
'MiniBatchSize',128,...
'NumEpoch',3,...
'AdvantageEstimateMethod','gae',...
'GAEFactor',0.95,...
'SampleTime',Ts,...
'DiscountFactor',0.995);
agentA = rlPPOAgent(actor(1),critic(1),opt);
but I get the following error. I apprecaite your help.
Error using rl.agent.util.checkFcnRNNCompatibility
To train an agent that has states, all actor and critic representations for that agent must have states.
Error in rl.agent.AbstractOnPolicyPGAgent/setCritic (line 148)
rl.agent.util.checkFcnRNNCompatibility(critic,this.Actor_)
Error in rl.agent.rlPPOAgent (line 21)
this = setCritic(this,critic);
Error in rlPPOAgent (line 95)
Agent = rl.agent.rlPPOAgent(Actor, Critic, AgentOptions);

 Accepted Answer

I believe that both the actor and the critic need to be LSTM networks. In your case only the critic is

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R2022a

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