An inductive inference model to elicit noncompensatory judgment strategies

Jing Yin, Ling Rothrock

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

Abstract

The proposed research developed a noncompensatory policy capturing technique to infer judgment rules (represented in disjunctive normal form) from available human data. The rule induction algorithm employs multiobjective Genetic Algorithm (GA) as its central search mechanism to enhance the induction and classification process. The quality of the induced rule set is measured by two criteria, fidelity (the degree to which the rule set reflects the judgment data they have been extracted from) and compactness (the simplicity of the rule set). An experimental study is conducted to demonstrate the effectiveness of the algorithm on a number of benchmark datasets.

Original languageEnglish (US)
Title of host publicationHuman-Computer Interaction
Subtitle of host publicationDesign and Development Approaches - 14th International Conference, HCI International 2011, Proceedings
Pages414-422
Number of pages9
EditionPART 1
DOIs
StatePublished - Jul 19 2011
Event14th International Conference on Human-Computer Interaction, HCI International 2011 - Orlando, FL, United States
Duration: Jul 9 2011Jul 14 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume6761 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other14th International Conference on Human-Computer Interaction, HCI International 2011
CountryUnited States
CityOrlando, FL
Period7/9/117/14/11

Fingerprint

Inductive Inference
Genetic algorithms
Rule Induction
Multi-objective Genetic Algorithm
Model
Fidelity
Normal Form
Compactness
Experimental Study
Simplicity
Proof by induction
Benchmark
Strategy
Judgment
Demonstrate

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Yin, J., & Rothrock, L. (2011). An inductive inference model to elicit noncompensatory judgment strategies. In Human-Computer Interaction: Design and Development Approaches - 14th International Conference, HCI International 2011, Proceedings (PART 1 ed., pp. 414-422). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6761 LNCS, No. PART 1). https://doi.org/10.1007/978-3-642-21602-2_45
Yin, Jing ; Rothrock, Ling. / An inductive inference model to elicit noncompensatory judgment strategies. Human-Computer Interaction: Design and Development Approaches - 14th International Conference, HCI International 2011, Proceedings. PART 1. ed. 2011. pp. 414-422 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).
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Yin, J & Rothrock, L 2011, An inductive inference model to elicit noncompensatory judgment strategies. in Human-Computer Interaction: Design and Development Approaches - 14th International Conference, HCI International 2011, Proceedings. PART 1 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 6761 LNCS, pp. 414-422, 14th International Conference on Human-Computer Interaction, HCI International 2011, Orlando, FL, United States, 7/9/11. https://doi.org/10.1007/978-3-642-21602-2_45

An inductive inference model to elicit noncompensatory judgment strategies. / Yin, Jing; Rothrock, Ling.

Human-Computer Interaction: Design and Development Approaches - 14th International Conference, HCI International 2011, Proceedings. PART 1. ed. 2011. p. 414-422 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6761 LNCS, No. PART 1).

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

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Yin J, Rothrock L. An inductive inference model to elicit noncompensatory judgment strategies. In Human-Computer Interaction: Design and Development Approaches - 14th International Conference, HCI International 2011, Proceedings. PART 1 ed. 2011. p. 414-422. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1). https://doi.org/10.1007/978-3-642-21602-2_45