Created
June 14, 2018 11:42
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Snippet for toyCarIRL, blog usage, not executable
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| def getRLAgentFE(self, W, i): #get the feature expectations of a new poliicy using RL agent | |
| IRL_helper(W, self.behavior, self.num_frames, i) # train the agent and save the model in a file used below | |
| saved_model = 'saved-models_'+self.behavior+str(i)+'/164-150-100-50000-'+str(self.num_frames)+'.h5' # use the saved model to get the FE | |
| model = neural_net(self.num_states, [164, 150], saved_model) | |
| return play(model, W)#return feature expectations by executing the learned policy |
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