Title page for ETD etd-05072003-102145
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Type of Document Dissertation
Author Dash, Denver
Author's Email Address ddash@sis.pitt.edu
URN etd-05072003-102145
Title Caveats for Causal Reasoning with Equilibrium Models
Degree Doctor of Philosophy
Program Intelligent Systems
School School of Arts and Sciences
Advisory Committee
Advisor Name Title
Marek Druzdzel Committee Chair
Greg Cooper Committee Member
Milos Hauskrecht Committee Member
Richard Scheines Committee Member
Vanathi Gopalakrishnan Committee Member
Keywords
  • causality
  • dynamics
  • Bayesian networks
  • structural equation models
  • feedback
  • Do operator
Date of Defense 2003-03-18
Availability unrestricted
Abstract
This thesis raises objections to the use of causal reasoning with equilibrium models. I consider two operators that are used to transform models: the {em Do} operator for modeling manipulation and the {em Equilibration} operator for modeling a system that has achieved equilibrium. I introduce a property of a causal model called the {em EMC Property} that is true iff the {em Do} operator commutes with the {em Equilibration} operator. I prove that not all models obey the EMC property, and I demonstrate empirically that when inferring a causal model from data, the learned model will not support causal reasoning if the EMC property is not obeyed. I find sufficient conditions for models to violate and not to violate the EMC property. In addition, I show that there exists a class of models that violate EMC and possess a set of variables whose manipulation will cause an instability in the system. All dynamic models in this class possess feedback, although I do not prove that feedback is a necessary or a sufficient condition for EMC violation. I define the {em Structural Stability Principle} which provides a necessary graphical criterion for stability in causal models. I will argue that the models in this class are quite common given typical assumptions about causal relations.
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