The University of Southampton
University of Southampton Institutional Repository

Beyond Plan Length: heuristic search planning for maximum reward problems

Beyond Plan Length: heuristic search planning for maximum reward problems
Beyond Plan Length: heuristic search planning for maximum reward problems
Recently automatic extraction of heuristic estimates has been shown to be extremely fruitful when applied to classical planning domains. We present a simple extension to the heuristic extraction process from the well-known HSP system that allows us to apply it to reward maximisation problems. This extension involves computing an estimate of the maximal reward obtainable from a given state by ignoring delete lists. We also describe how to improve the accuracy of this estimate using any available mutual exclusion information. In this way we seek to apply recent advances in classical planning to a broader range of problems, ultimately to include both both probabilistic and decision theoretic problems.
Farquhar, Jason
deda815f-f964-4626-aedf-9d15a4e45376
Harris, Chris
c4fd3763-7b3f-4db1-9ca3-5501080f797a
Farquhar, Jason
deda815f-f964-4626-aedf-9d15a4e45376
Harris, Chris
c4fd3763-7b3f-4db1-9ca3-5501080f797a

Farquhar, Jason and Harris, Chris (2001) Beyond Plan Length: heuristic search planning for maximum reward problems.

Record type: Conference or Workshop Item (Other)

Abstract

Recently automatic extraction of heuristic estimates has been shown to be extremely fruitful when applied to classical planning domains. We present a simple extension to the heuristic extraction process from the well-known HSP system that allows us to apply it to reward maximisation problems. This extension involves computing an estimate of the maximal reward obtainable from a given state by ignoring delete lists. We also describe how to improve the accuracy of this estimate using any available mutual exclusion information. In this way we seek to apply recent advances in classical planning to a broader range of problems, ultimately to include both both probabilistic and decision theoretic problems.

Full text not available from this repository.

More information

Published date: May 2001
Additional Information: Submitted to: European Conference on Planning 2001 (ECP-01) May 20001.
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 255889
URI: http://eprints.soton.ac.uk/id/eprint/255889
PURE UUID: 3ed8422a-01c5-4b74-8e68-d49c36bac734

Catalogue record

Date deposited: 18 May 2001
Last modified: 29 Jan 2020 15:22

Export record

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×