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When training an agent using the Reinforcement Learning Toolbox, how can I use a custom stopping criterion?

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DHRUV LAAD
DHRUV LAAD on 2 Jan 2020
Answered: Rajani Mishra on 6 Jan 2020
The current options only allow for 5 predefined choices ("AverageSteps", "AverageReward", "EpisodeReward", "GlobalStepCount", "EpisodeCount"). I want to include a stopping criterion different from these. Is there any option to do the same?

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Rajani Mishra
Rajani Mishra on 6 Jan 2020
trainOpts = rlTrainingOptions(Name,Value) creates an option set for training using specified name-value pairs.
Arguments like - 'StopTrainingCriteria', 'StopTrainingValue', 'MaxEpisodes' should be specified for defining stopping criterion while training an agent.
  • StopTrainingCriteria: Specifies the termination condition. Takes one of the choices as you have mentioned
  • StopTrainingValue: Specifies the Critical value of training termination condition. Training terminates when the termination condition specified by the StopTrainingCriteria option equals or exceeds this value
  • MaxEpisodes: Specifies maximum number of episodes to train the agent, once the number of episodes reached training terminates
For more information please refer to
  1. https://www.mathworks.com/help/reinforcement-learning/ref/rltrainingoptions.html#mw_f2a4c660-a2a4-417d-9dbc-df113aa3b975
  2. https://www.mathworks.com/help/reinforcement-learning/training-and-validation.html?s_tid=CRUX_lftnav

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