Principles of Diagnosis: Current Trends and a Report on the First International Workshop

Automated diagnosis is an important AI problem not only for its potential practical applications but also because it exposes issues common to all automated reasoning efforts and presents real challenges to existing paradigms. Current research in this area addresses many problems, including managing and structuring probabilistic information, modeling physical systems, reasoning with defeasible assumptions, and interleaving deliberation and action. Furthermore, diagnosis programs must face these problems in contexts where scaling up to deal with cases of realistic size results in daunting combinatorics. This article presents these and other issues as discussed at the First International Workshop on Principles of Diagnosis.

[1]  Pietro Torasso,et al.  A Theory of Diagnosis for Incomplete Causal Models , 1989, IJCAI.

[2]  A. Hasman.  Kardio. A study in deep and qualitative knowledge for expert systems , 1991 .

[3]  Thomas D. Wu.  Domain Structure and the Complexity of Diagnostic Problem Solving , 1991, AAAI.

[4]  Hwee Tou Ng,et al.  Model-based, multiple fault diagnosis of time-varying, continuous physical devices , 1990, Sixth Conference on Artificial Intelligence for Applications.

[5]  James A. Reggia,et al.  A connectionist model for diagnostic problem solving , 1989, IEEE Trans. Syst. Man Cybern..

[6]  Peter Szolovits,et al.  Categorical and Probabilistic Reasoning in Medical Diagnosis , 1990, Artif. Intell..

[7]  Gregory F. Cooper,et al.  The Computational Complexity of Probabilistic Inference Using Bayesian Belief Networks , 1990, Artif. Intell..

[8]  Gerald Jay Sussman,et al.  CONSTRAINTS - A Language for Expressing Almost-Hierarchical Descriptions , 1980, Artif. Intell..

[9]  Johan de Kleer.  Focusing on Probable Diagnoses , 1991, AAAI.

[10]  Oskar Dressler.  Diagnoses as Coherent Assumption Sets , 1990, Expert Systems in Engineering.

[11]  W. Hamscher.  Model-based financial data interpretation , 1991, Proceedings First International Conference on Artificial Intelligence Applications on Wall Street.

[12]  Michael R. Genesereth,et al.  The Use of Design Descriptions in Automated Diagnosis , 1984, Artif. Intell..

[13]  Walter Charles Hamscher.  Model-based troubleshooting of digital systems , 1988 .

[14]  Pietro Torasso,et al.  Integrating Models of the Correct Behavior into Abductive Diagnosis , 1990, ECAI.

[15]  李幼升,et al.  Ph , 1989 .

[16]  Johan de Kleer,et al.  An Assumption-Based TMS , 1987, Artif. Intell..

[17]  Mark A. Kramer,et al.  Qualitative Analysis of Causal Feedback , 1991, AAAI.

[18]  Georg Gottlob,et al.  Hypothesis Classification, Abductive Diagnosis and Therapy , 1990, Expert Systems in Engineering.

[19]  Igor Mozetič,et al.  Reduction of Diagnostic Complexity through Model Abstractions , 1990 .

[20]  Eric Horvitz,et al.  Probabilistic Diagnosis Using a Reformulation of the INTERNIST-1/QMR Knowledge Base Part II , 2016 .

[21]  Philippe Dague,et al.  An Interval Propagation and Conflict Recognition Engine for Diagnosing Continuous Dynamic Systems , 1990, Expert Systems in Engineering.

[22]  Johan de Kleer,et al.  Readings in qualitative reasoning about physical systems , 1990 .

[23]  Benjamin Kuipers,et al.  Model-Based Monitoring of Dynamic Systems , 1989, IJCAI.

[24]  Peter Struss,et al.  "Physical Negation" Integrating Fault Models into the General Diagnostic Engine , 1989, IJCAI.

[25]  Randall Davis,et al.  Diagnosing Circuits With State: An Inherently Underconstrained Problem , 1984, AAAI.

[26]  Harry E. Pople,et al.  The Formation of Composite Hypotheses in Diagnostic Problem Solving: An Exercise in Synthetic Reasoning , 1977, IJCAI.

[27]  Johan de Kleer,et al.  Characterizing Non-Intermittent Faults , 1991, AAAI.

[28]  Dean Allemang,et al.  Some Results Concerning the Computational Complexity of Abduction , 1989, KR.

[29]  Max Henrion,et al.  Search-Based Methods to Bound Diagnostic Probabilities in Very Large Belief Nets , 1991, UAI.

[30]  Randall Davis,et al.  Representing Structure and Behavior of Digital Hardware , 1983, Computer.

[31]  田中 穂積.  E.H.Shortliffe 著, "Computer-Based Medical Consultations : MYCIN", American Elsevier, A4判, 264ぺージ, \10,080, 1976 , 1978 .

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

[33]  Walter Hamscher,et al.  Modeling Digital Circuits for Troubleshooting , 1991, Artif. Intell..

[34]  Randall Davis,et al.  Model-based reasoning: troubleshooting , 1988 .

[35]  J. M. Larrazabal,et al.  Reasoning about change , 1991 .

[36]  B. J. Glass,et al.  TEXSYS: a large scale demonstration of model-based real-time control of a space station subsystem , 1991, [1991] Proceedings. The Seventh IEEE Conference on Artificial Intelligence Application.

[37]  Raymond Reiter,et al.  Characterizing Diagnoses , 1990, AAAI.

[38]  Edward H. Shortliffe,et al.  A Method for Managing Evidential Reasoning in a Hierarchical Hypothesis Space , 1985, Artif. Intell..

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

[40]  Matthew L. Ginsberg,et al.  Readings in Nonmonotonic Reasoning , 1987, AAAI 1987.

[41]  Thomas D. Wu.  Efficient Diagnosis of Multiple Disorders Based on a Symptom Clustering Approach , 1990, AAAI.

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

[43]  James A. Reggia,et al.  Diagnostic Expert Systems Based on a Set Covering Model , 1983, Int. J. Man Mach. Stud..

[44]  Brian C. Williams,et al.  Diagnosis with Behavioral Modes , 1989, IJCAI.

[45]  Judea Pearl,et al.  Fusion, Propagation, and Structuring in Belief Networks , 1986, Artif. Intell..

[46]  Olivier Raiman,et al.  A Circumscribed Diagnosis Engine , 1990, Expert Systems in Engineering.

[47]  J. S. Brown,et al.  Pedagogical, natural language, and knowledge engineering techniques in SOPHIE-I, II and III , 1982 .

[48]  Peter Szolovits,et al.  Causal Understanding of Patient Illness in Medical Diagnosis , 1981, IJCAI.

[49]  Gisela Schäfer-Richter,et al.  SIDIA: Extending Prediction Based Diagnosis to Dynamic Models , 1990, Expert Systems in Engineering.

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

[51]  F. E. Finch,et al.  Qualitative modeling and fault diagnosis of dynamic processes by MIDAS , 1992 .

[52]  David Poole,et al.  Normality and Faults in Logic-Based Diagnosis , 1989, IJCAI.

[53]  Keith L. Clark,et al.  Negation as Failure , 1987, Logic and Data Bases.

[54]  Raymond Reiter,et al.  A Theory of Diagnosis from First Principles , 1986, Artif. Intell..