Compact Representations of Extended Causal Models

Abstract

Judea Pearl (2000) was the first to propose a definition of actual causation using causal models. A number of authors have suggested that an adequate account of actual causation must appeal not only to causal structure, but also to considerations of normality. In (Halpern & Hitchcock, 2011) we offer a definition of actual causation using extended causal models, which include information about both causal structure and normality. Extended causal models are potentially very complex. In this paper, we show how it is possible to achieve a compact representation of extended causal models.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2012
Accession Number
ADA582556

Entities

People

  • Christopher Hitchcock
  • Joseph Halpern

Organizations

  • Cornell University

Tags

Communities of Interest

  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Bayesian Networks
  • Causal Reasoning
  • Cognitive Science
  • Computer Science
  • Data Science
  • Forest Fires
  • Information Science
  • Language
  • Normality
  • Probability
  • Probability Distributions
  • Psychology
  • Random Variables
  • Reasoning
  • Standards
  • Statistics

Fields of Study

  • Computer science

Readers

  • Military History
  • Neural Network Machine Learning.
  • Regression Analysis.