---
title: "Towards Scalable MDP Algorithms"
authors:
  - "Andrey Kolobov"
  - "Mausam"
  - "Daniel S. Weld"
doi: "10.5591/978-1-57735-516-8/IJCAI11-481"
url: "https://ijcai.org/proceedings/2011/481"
pdf: "https://ijcai.org/proceedings/2011/0481.pdf"
venue: "Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence"
year: 2011
pages: "2818-2818"
track: ""
keywords:
---

# Towards Scalable MDP Algorithms

Andrey Kolobov, Mausam, Daniel S. Weld

*Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence*, pages 2818-2818. DOI: [10.5591/978-1-57735-516-8/IJCAI11-481](https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-481)

## Abstract

The scalability of algorithms for solving Markov Decision Processes (MDPs) has been a limiting factor for MDPs as a modeling tool. This dissertation develops theoretical and empirical techniques for solving larger MDPs than was possible before, and aims to demonstrate the achieved progress by applying these new algorithms to a real-world problem.