Data-Driven Control of Unknown Systems: A Linear Programming Approach

30 Mar 2020 Tanzanakis Alexandros Lygeros John

We consider the problem of discounted optimal state-feedback regulation for general unknown deterministic discrete-time systems. It is well known that open-loop instability of systems, non-quadratic cost functions and complex nonlinear dynamics, as well as the on-policy behavior of many reinforcement learning (RL) algorithms, make the design of model-free optimal adaptive controllers a challenging task... (read more)

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