Theories of comparative analysis

"Theories of Comparative Analysis" provides a detailed examination of comparative analysis, the problem of predicting how a system will react to perturbations in its parameters, and why. It clearly formalizes the problem and presents two novel techniques - differential qualitative (DQ) analysis and exaggeration - that solve many comparative analysis problems, providing explanations suitable for use by design systems, automated diagnosis, intelligent tutoring systems, and explanation-based generalization.Weld first places comparative analysis within the context of qualitative physics and artificial intelligence. He then explains the theoretical basis for each technique and describes how they are implemented. He shows that they are essentially complementary: DQ analysis is sound, while exaggeration is a heuristic method: exaggeration, however, solves a wider variety of problems. Weld summarizes their similarities and differences and introduces a hybrid architecture that takes advantage of the strengths of each technique.Daniel S. Weld is Assistant Professor of Computer Science and Engineering at the University of Washington. "Theories of Comparative Analysis" is included in the Artificial Intelligence Series, edited by Michael Brady, Daniel Bobrow, and Randall Davis.

[1]  Smadar T. Kedar-Cabelli,et al.  Explanation-Based Generalization as Resolution Theorem Proving , 1987 .

[2]  Jon Doyle,et al.  AMORD explicit control of reasoning , 1977, SIGART Newsl..

[3]  Daniel S. Weld,et al.  Explaining Complex Engineered Devices. , 1983 .

[4]  Elisha Sacks,et al.  Piecewise Linear Reasoning , 1987, AAAI Conference on Artificial Intelligence.

[5]  Brian C. Williams,et al.  Qualitative Analysis of MOS Circuits , 1984, Artif. Intell..

[6]  James R. Munkres,et al.  Topology; a first course , 1974 .

[7]  Kenneth D. Forbus.  Qualitative Process Theory , 1984, Artif. Intell..

[8]  Brian C. Williams,et al.  Back to Backtracking: Controlling the ATMS , 1986, AAAI.

[9]  Daniel S. Weld.  Comparative Analysis , 1987, IJCAI.

[10]  Johan de Kleer,et al.  How Circuits Work , 1984, Artif. Intell..

[11]  Elisha Sacks.  Automatic Qualitative Analysis of Ordinary Differential Equations Using Piecewise Linear Approximations , 1988 .

[12]  Benjamin J. Kaipers,et al.  Qualitative Simulation , 1989, Artif. Intell..

[13]  Elisha Sacks,et al.  Qualitative Mathematical Reasoning , 1985, IJCAI.

[14]  Randall Davis,et al.  Diagnostic Reasoning Based on Structure and Behavior , 1984, Artif. Intell..

[15]  Olivier Raiman,et al.  Assembling a device , 1988, Artif. Intell. Eng..

[16]  Reid G. Simmons,et al.  Commonsense Arithmetic Reasoning , 1986, AAAI.

[17]  Antony Galton,et al.  The logic of occurrence , 1987 .

[18]  Peter Struss,et al.  Mathematical aspects of qualitative reasoning , 1988, Artif. Intell. Eng..

[19]  Brian C. Williams,et al.  Diagnosing Multiple Faults , 1987, Artif. Intell..

[20]  Olivier Raiman.  Order of magnitude reasoning , 1986, AAAI 1986.

[21]  Johan de Kleer,et al.  Causal and Teleological Reasoning In Circuit Recognition , 1979 .

[22]  Patrick J. Hayes,et al.  Naive physics I: ontology for liquids , 1989 .

[23]  Johan de Kleer,et al.  A Qualitative Physics Based on Confluences , 1984, Artif. Intell..

[24]  Benjamin Kuipers,et al.  Abstraction by Time-Scale in Qualitative Simulation , 1987, AAAI.

[25]  Brian C. Williams,et al.  MINIMA: A Symbolic Approach to Qualitative Algebraic Reasoning , 1988, AAAI.

[26]  A. Robinson.  Non-standard analysis , 1966 .

[27]  Herbert B. Enderton,et al.  A mathematical introduction to logic , 1972 .

[28]  Brian C. Williams,et al.  Doing Time: Putting Qualitative Reasoning on Firmer Ground , 1986, AAAI.

[29]  Benjamin Kuipers,et al.  The Limits of Qualitative Simulation , 1985, IJCAI.

[30]  Ramesh S. Patil,et al.  Causal representation of patient illness for electrolyte and acid-base diagnosis , 1981 .