On the Computational Consequences of Cost Function Design in Nonlinear Optimal Control

no code implementations • 5 Apr 2022 • Tyler Westenbroek, Anand Siththaranjan, Mohsin Sarwari, Claire J. Tomlin, Shankar S. Sastry

However, despite the extensive impacts of methods such as receding horizon control, dynamic programming and reinforcement learning, the design of cost functions for a particular system often remains a heuristic-driven process of trial and error.

reinforcement-learning Reinforcement Learning (RL)