Home > Publications . Search All . Browse All . Country . Browse PSC Pubs . PSC Report Series

PSC In The News

RSS Feed icon

Frey and colleagues outline 10 trends showing scale of America's demographic transitions

Starr says surveys intended to predict recidivism assign higher risk to poor

Prescott and colleagues find incidence of noncompetes in U.S. labor force varies by job, state, worker education

Highlights

PAA 2015 Annual Meeting: Preliminary program and list of UM participants

ISR addition wins LEED Gold Certification

PSC Fall 2014 Newsletter now available

Martha Bailey and Nicolas Duquette win Cole Prize for article on War on Poverty

Next Brown Bag

Mon, March 9
Luigi Pistaferri, Consumption Inequality and Family Labor Supply

Efficient Reinforcement Learning with Multiple Reward Functions for Randomized Controlled Trial Analysis

Publication Abstract

Lizotte, Daniel, M. Bowling, and Susan A. Murphy. 2010. "Efficient Reinforcement Learning with Multiple Reward Functions for Randomized Controlled Trial Analysis." In Proceedings of the 27th International Conference on Machine Learning (ICML 2010) edited by Johannes Furnkranz and Thorsten Joachims. Madison, WI: International Machine Learning Society.

We introduce new, efficient algorithms for value iteration with multiple reward functions and continuous state. We also give an algorithm for finding the set of all non-dominated actions in the continuous state setting. This novel extension is appropriate for environments with continuous or finely discretized states where generalization is required, as is the case for data analysis of randomized controlled trials.

ISBN: 978-1-60558-907-7

Public Access Link

Browse | Search : All Pubs | Next