2021
DOI: 10.1007/978-3-030-85172-9_11
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DSMC Evaluation Stages: Fostering Robust and Safe Behavior in Deep Reinforcement Learning

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Cited by 8 publications
(14 citation statements)
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“…Apart from that, we plan to build upon MoGym to develop DSMC techniques further. With DSMC Evaluation Stages [21] it has already been shown that DSMC can be applied during deep RL to determine state space regions with weak performance to concentrate on them during the learning process. With the help of MoGym this technique can now be done much more integrated and there is room for further implementations into this direction in our tool chain.…”
Section: Discussionmentioning
confidence: 99%
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“…Apart from that, we plan to build upon MoGym to develop DSMC techniques further. With DSMC Evaluation Stages [21] it has already been shown that DSMC can be applied during deep RL to determine state space regions with weak performance to concentrate on them during the learning process. With the help of MoGym this technique can now be done much more integrated and there is room for further implementations into this direction in our tool chain.…”
Section: Discussionmentioning
confidence: 99%
“…As such, the environment provides a stable and fully controllable training and checking context to assert the safety risk induced by an agent during and after training. More concrete, MoGym leverages deep statistical model checking (DSMC) [20,21]. As shown in these works on DSMC, the quality assessment of an agent during training is not trivial and can especially not always be derived from the observed training returns.…”
Section: Introductionmentioning
confidence: 99%
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