Planning for welfare to work

Yi Liangrong, Raphael Finkel, Judy Goldsmith

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

We are interested in building decision-support software for social welfare case managers. Our model in the form of a factored Markov decision process is so complex that a standard factored MDP solver was unable to solve it efficiently. We discuss factors contributing to the complexity of the model, then present a receding horizon planner that offers a rough policy quickly. Our planner computes locally, both in the sense of only offering one action suggestion at a time (rather than a complete policy) and because it starts from an initial state and considers only states reachable from there in its calculations.

Original languageEnglish
Title of host publicationProceedings of the 21th International Florida Artificial Intelligence Research Society Conference, FLAIRS-21
Pages696-701
Number of pages6
StatePublished - 2008
Event21th International Florida Artificial Intelligence Research Society Conference, FLAIRS-21 - Coconut Grove, FL, United States
Duration: May 15 2008May 17 2008

Publication series

NameProceedings of the 21th International Florida Artificial Intelligence Research Society Conference, FLAIRS-21

Conference

Conference21th International Florida Artificial Intelligence Research Society Conference, FLAIRS-21
Country/TerritoryUnited States
CityCoconut Grove, FL
Period5/15/085/17/08

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software

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