41 citations · 160 across the 25 of their papers we have counts for
5 papers · 1 filter
Model Predictive Control and Reinforcement Learning: A Unified Framework Based on Dynamic Programming
Dimitri P. Bertsekas
In this paper we describe a new conceptual framework that connects approximate Dynamic Programming (DP), Model Predictive Control (MPC), and Reinforcement Learning (RL). This frame…
Incremental Aggregated Proximal and Augmented Lagrangian Algorithms
Dimitri P. Bertsekas
We consider minimization of the sum of a large number of convex functions, and we propose an incremental aggregated version of the proximal algorithm, which bears similarity to the…
Lambda-Policy Iteration: A Review and a New Implementation
Dimitri P. Bertsekas
In this paper we discuss -policy iteration, a method for exact and approximate dynamic programming. It is intermediate between the classical value iteration (VI) and policy iter…
Incremental Gradient, Subgradient, and Proximal Methods for Convex Optimization: A Survey
Dimitri P. Bertsekas
We survey incremental methods for minimizing a sum consisting of a large number of convex component functions . Our methods consist of iterations applied…
Value and Policy Iteration in Optimal Control and Adaptive Dynamic Programming
Dimitri P. Bertsekas
In this paper, we consider discrete-time infinite horizon problems of optimal control to a terminal set of states. These are the problems that are often taken as the starting point…