Approximate Linear Programming for Average Cost MDPs

By Michael H. Veatch. 2013

15 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics, Electrical and Electronic Engineering

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Mengdi Wang
2. Yichen Chen
3. Alan Malek
4. Donghwan Lee
5. Lihong Li
6. Niao He
7. Bo Dai
8. Ofir Nachum

In Computational Theory and Mathematics

1. Yichen Chen
2. Alan Malek
3. Mengdi Wang
4. Joan Bas-Serrano
5. Gergely Neu

In Electrical and Electronic Engineering

1. Alan Malek
2. Mengdi Wang
3. Yichen Chen

Citations in the corpus

• Efficient Sequential Decision Making (2017, background): “Similar results are obtained more recently by Veatch [51].”
• An online primal-dual method for discounted Markov decision processes (2016, background): “Approximate linear programming has been studied for approximating large-scale MDP on a low-dimensional subspace, started with [11] and followed by [1], [23].”
• Linear Programming for Large-Scale Markov Decision Problems (2014, unknown): “Similar results are obtained more recently by Veatch (2013). An appropriate choice for vector ν is ν = μγ,w∗.”