We study both the value function and Q-function formulation of the linear programming
approach to approximate dynamic programming. The approach is model based and …

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 …

The deployment of Autonomous Vehicles (AVs) poses considerable challenges and unique
opportunities for the design and management of future urban road infrastructure. In light of …

In this paper we study value function approximation techniques that are based on the Linear
Programming formulation of Approximate Dynamic Programming. We propose a point-wise …

In this paper we study both the value function and Q-function formulation of the Linear
Programming (LP) approach to ADP. The approach selects from a restricted function space …

While Approximate Dynamic Programming has successfully been used in many applications
involving discrete states and inputs such as playing the games of Tetris or chess, it has not …

In this paper, we propose a novel formulation for encoding state constraints into the Linear
Programming approach to Approximate Dynamic Programming via the use of penalty …