Efficient reasoning with ambient trees for space exploration

Emil Vassev, Mike Hinchey

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

Abstract

Modern reasoning is based on inference techniques such as induction, deduction, abduction, subsumption, classification and recognition. These inference techniques are very inefficient when applied to large amounts of knowledge such as ones employed by contemporary unmanned spacecraft. For efficient reasoning, we aim at knowledge representation based on special ambient trees determining special knowledge contexts to help such spacecraft retrieve context-relevant knowledge and perform deductive reasoning, which would not be otherwise highlighted. Contexts via their ambient trees provide a sort of a condensed and explicit symbolic representation of the world. This representation is cleaned from the overwhelming information that is non-relevant to the context and thus, it provides for efficient models of situations to reason about.

Original languageEnglish
Title of host publicationContext-Aware Systems and Applications - First International Conference, ICCASA 2012, Revised Selected Papers
Pages176-182
Number of pages7
DOIs
Publication statusPublished - 2013
Event1st International Conference on Context-Aware Systems and Applications, ICCASA 2012 - Ho Chi Minh City, Viet Nam
Duration: 26 Nov 201227 Nov 2012

Publication series

NameLecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering
Volume109 LNICST
ISSN (Print)1867-8211

Conference

Conference1st International Conference on Context-Aware Systems and Applications, ICCASA 2012
Country/TerritoryViet Nam
CityHo Chi Minh City
Period26/11/1227/11/12

Keywords

  • autonomous spacecraft
  • knowledge representation
  • reasoning
  • space exploration

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