Kamalapurkar, Rushikesh; Walters, Patrick; Rosenfeld, Joel; Dixon, Warren (2018). "Optimal Control and Lyapunov Stability". Reinforcement Learning for Optimal Feedback Control: A Lyapunov-Based Approach. Berlin: Springer. pp. 26–27. ISBN978-3-319-78383-3.
doi.org
Benveniste and Scheinkman established sufficient conditions for the differentiability of the value function, which in turn allows an application of the envelope theorem, see Benveniste, L. M.; Scheinkman, J. A. (1979). "On the Differentiability of the Value Function in Dynamic Models of Economics". Econometrica. 47 (3): 727–732. doi:10.2307/1910417. JSTOR1910417. Also see Seierstad, Atle (1982). "Differentiability Properties of the Optimal Value Function in Control Theory". Journal of Economic Dynamics and Control. 4: 303–310. doi:10.1016/0165-1889(82)90019-7.
Zhou, X. Y. (1990). "Maximum Principle, Dynamic Programming, and their Connection in Deterministic Control". Journal of Optimization Theory and Applications. 65 (2): 363–373. doi:10.1007/BF01102352. S2CID122333807.
jstor.org
Benveniste and Scheinkman established sufficient conditions for the differentiability of the value function, which in turn allows an application of the envelope theorem, see Benveniste, L. M.; Scheinkman, J. A. (1979). "On the Differentiability of the Value Function in Dynamic Models of Economics". Econometrica. 47 (3): 727–732. doi:10.2307/1910417. JSTOR1910417. Also see Seierstad, Atle (1982). "Differentiability Properties of the Optimal Value Function in Control Theory". Journal of Economic Dynamics and Control. 4: 303–310. doi:10.1016/0165-1889(82)90019-7.
Zhou, X. Y. (1990). "Maximum Principle, Dynamic Programming, and their Connection in Deterministic Control". Journal of Optimization Theory and Applications. 65 (2): 363–373. doi:10.1007/BF01102352. S2CID122333807.