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The desire to use reinforcement learning in safety-critical settings has inspired a recent interest in formal methods for learning algorithms.
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Fulton, N., Mitsch, S., Quesel, J.D., Völp, M., Platzer, A.: KeYmaera X: An axiomatic tactical theorem prover for hybrid systems. In: Felty, A.P., Middeldorp, A. (eds.) CADE. LNCS, vol. 9195, pp. 527–538. Springer (2015)
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Bohrer, B., Tan, Y.K., Mitsch, S., Myreen, M.O., Platzer, A.: VeriPhy: Verified controller executables from verified cyber-physical system models. In: Grossman, D. (ed.) Proceedings of the 39th ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI 2018). pp. 617–630. ACM (2018)
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Fulton, N., Platzer, A.: Safe reinforcement learning via formal methods: Toward safe control through proof and learning. In: McIlraith, S., Weinberger, K. (eds.) Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence (AAAI 2018). pp. 6485–6492. AAAI Press (2018)
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