Analogical abduction and prediction: Their impact on deception

Kenneth D Forbus*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

To deceive involves corrupting the predictions or explanations of others. A deeper understanding of how this works thus requires modeling how human abduction and prediction operate. This paper proposes that most human abduction and prediction are carried out via analogy, over experience and generalizations constructed from experience. I take experience to include cultural products, such as stories. How analogical reasoning and learning can be used to make predictions and explanations is outlined, along with both the advantages of this approach and the technical questions that it raises. Concrete examples involving deception and counter- deception are used to explore these ideas further.

Original languageEnglish (US)
Title of host publicationDeceptive and Counter-Deceptive Machines - Papers from the AAAI 2015 Fall Symposium, Technical Report
PublisherAI Access Foundation
Pages15-20
Number of pages6
VolumeFS-15-03
ISBN (Electronic)9781577357490
StatePublished - Jan 1 2015
EventAAAI 2015 Fall Symposium - Arlington, United States
Duration: Nov 12 2015Nov 14 2015

Other

OtherAAAI 2015 Fall Symposium
CountryUnited States
CityArlington
Period11/12/1511/14/15

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Forbus, K. D. (2015). Analogical abduction and prediction: Their impact on deception. In Deceptive and Counter-Deceptive Machines - Papers from the AAAI 2015 Fall Symposium, Technical Report (Vol. FS-15-03, pp. 15-20). AI Access Foundation.