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Dynamic programming and optimal control Dimitri P. Bertsekas
Publisher: Athena Scientific

1, Bertsekas, Athena Scientific. Provides a dynamic programming example solution, introduces the cost-to-go. Discrete problem by Bellman equation, Dynamic Programming. Optimal control for the analogous discrete time state equations. One good one is Dynamic Programming and Optimal Control, vol. So, you need to know intertemporal optimization (usually dynamic programming or optimal control formalism), some differential equations and dynamic systems, and linear estimation theory. We do teach dynamic programming and optimal control theory. In some sense that isn't really responsive. The dynamic programming technique is applied to find the optimal controller in the inner loop while the component parameters are optimized iteratively in the outer loop. Topics from deterministic and stochastic optimal control, reinforcement learning and dynamic programming, numerical optimization in the context of control, and robotics. But the Taylor Rule isn't really a solution to that kind of a problem; it's more of an ad-hoc rule of thumb. Finally, it surveys such advanced topics as uncertainty in two-period models, catastrophic risk, stochastic control problems, deterministic optimal control, and stochastic and deterministic dynamic programming approaches. LQR and Kalman filtering are covered in many books on linear systems, optimal control, and optimization.