International Symposium on Affective Science and Engineering
Online ISSN : 2433-5428
ISASE2018
セッションID: A4-4
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A4: Artificial Intelligence
A Computational Framework for Identity Based on Situation Theory
Janelle MASONKofi KYEIDarrion LONGHannah FOSTERWilliam NICKJames MAYESAlbert ESTERLINE
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This paper presents a computational framework for identity (initially about the culprit in a crime scene) based on Barwise’s situation theory. Situations support information and can carry information about other situations. An utterance situation carries information about a described situation thanks to the constraints imposed by natural language. We are concerned with utterance situations in which identity judgments are made about the culprit in a crime scene, which is the corresponding described situation. The id-situation and crime scene along with various resource situations make up a case in the legal sense. We have developed OWL ontologies to provide concepts and principled vocabularies for encoding our scenarios in RDF, and we present an example of a SPARQL query of one of our encodings that spans situations. To follow how evidence supports hypotheses on the identity of the culprit in a crime scene, we use Dempster-Shafer theory. We tightly integrate it with our ontologies by having the representation of a case per our ontologies present a network containing situations and stitched together by objects; evidence "flows" along this network, diminishing and combining. We review the modifications of Dempster-Shafer theory required when one goes from a closed-world assumption to an open-world assumption. We review our plans regarding equational reasoning based on identities established in our id-cases, and we review the related issues regarding the meanings of URIs.

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© 2018 Japan Society of Kansei Engineering
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