Learning the Scope of Applicability for Task Planning Knowledge in Experience-Based Planning Domains

Vahid Mokhtari, Roman Manevich, Luis Seabra Lopes, Armando J. Pinho

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

1 Scopus citations

Abstract

Experience-based planning domains (EBPDs) have been proposed to improve problem solving by learning from experience. They rely on acquiring and using task knowledge, i.e., activity schemata, for generating solutions to problem instances in a class of tasks. Using Three-Valued Logic Analysis (TVLA), we extend our previous work to generate a set of conditions that determine the scope of applicability of an activity schema. The inferred scope is an abstract representation of a potentially unbounded set of problems, in the form of a 3-valued logical structure, which is used to test the applicability of the respective activity schema for solving different task problems. We validate this work on two classical planning domains and a simulated PR2 in Gazebo.

Original languageEnglish
Title of host publication2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3973-3979
Number of pages7
ISBN (Electronic)9781728140049
DOIs
StatePublished - 1 Nov 2019
Externally publishedYes
Event2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2019 - Macau, China
Duration: 3 Nov 20198 Nov 2019

Publication series

NameIEEE International Conference on Intelligent Robots and Systems
ISSN (Print)2153-0858
ISSN (Electronic)2153-0866

Conference

Conference2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2019
Country/TerritoryChina
CityMacau
Period3/11/198/11/19

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

Fingerprint

Dive into the research topics of 'Learning the Scope of Applicability for Task Planning Knowledge in Experience-Based Planning Domains'. Together they form a unique fingerprint.

Cite this