A theory and methodology of inductive learning

The presented theory views inductive learning as a heuristic search through a space of symbolic descriptions, generated by an application of various inference rules to the initial observational statements. The inference rules include generalization rules, which perform generalizing transformations on descriptions, and conventional truth-preserving deductive rules. The application of the inference rules to descriptions is constrained by problem background knowledge, and guided by criteria evaluating the “quality” of generated inductive assertions.

[1]  M. Meyer.  Some points of difference concerning the theory of music. , .

[2]  B. Russell.  History of Western philosophy , 1949 .

[3]  J. Deese.  The psychology of learning , 1952 .

[4]  C I HOVLAND,et al.  A communication analysis of concept learning. , 1952, Psychological review.

[5]  John G. Kemeny,et al.  The Use of Simplicity in Induction , 1953 .

[6]  G. Pólya.  Mathematics and Plausible Reasoning , 1958 .

[7]  J. Bruell,et al.  Notes toward a motor theory of visual egocentric localization. , 1955, Psychological review.

[8]  William M. Smith,et al.  A Study of Thinking , 1956 .

[9]  Patrick Suppes,et al.  Introduction To Logic , 1958 .

[10]  H. R. Post.  SIMPLICITY IN SCIENTIFIC THEORIES* , 1960, The British Journal for the Philosophy of Science.

[11]  Ranan B. Banerji.  The description list of concepts , 1962, CACM.

[12]  H A SIMON,et al.  HUMAN ACQUISITION OF CONCEPTS FOR SEQUENTIAL PATTERNS. , 1963, Psychological review.

[13]  Ray J. Solomonoff,et al.  A Formal Theory of Inductive Inference. Part II , 1964, Inf. Control..

[14]  Philip J. Stone,et al.  Experiments in induction , 1966 .

[15]  Rudolf Carnap,et al.  The Aim of Inductive Logic , 1966 .

[16]  Patrick Henry Winston,et al.  Learning structural descriptions from examples , 1970 .

[17]  Donald A. Waterman,et al.  Generalization Learning Techniques for Automating the Learning of Heuristics , 1970, Artif. Intell..

[18]  Richard Fikes,et al.  Learning and Executing Generalized Robot Plans , 1993, Artif. Intell..

[19]  J. Feldman,et al.  A SURVEY OF RESULTS IN GRAMMATICAL INFERENCE , 1972 .

[20]  Ryszard S. Michalski,et al.  A Variable-Valued Logic System as Applied to Picture Description and Recognition , 1972 .

[21]  Richard C. T. Lee,et al.  Symbolic logic and mechanical theorem proving , 1973, Computer science classics.

[22]  Ryszard S. Michalski,et al.  AQVAL/1--Computer Implementation of a Variable-Valued Logic System VL1 and Examples of its Application to Pattern Recognition , 1973, IJCAI 1973.

[23]  H. Simon,et al.  Problem solving and rule induction: A unified view. , 1974 .

[24]  James C. Stoffel.  The Theory of Prime Events Data Analysis for Sample Vectors with Inherently Discrete Variables , 1974, IFIP Congress.

[25]  Marvin Minsky,et al.  A framework for representing knowledge , 1974 .

[26]  S. Vere.  Induction of concepts in the predicate calculus , 1975, IJCAI 1975.

[27]  Ryszard S. Michalski,et al.  Variable-Valued Logic and Its Applications to Pattern Recognition and Machine Learning , 1975 .

[28]  Marvin Minsky,et al.  A framework for representing knowledge" in the psychology of computer vision , 1975 .

[29]  Charles Locke Hedrick.  A computer program to learn production systems using a semantic net. , 1975 .

[30]  Charles G. Morgan,et al.  Automated Hypothesis Generation Using Extended Inductive Resolution , 1975, IJCAI.

[31]  David E. Shaw,et al.  Inferring LISP Programs From Examples , 1975, IJCAI.

[32]  Ryszard S. Michalski,et al.  Synthesis of Optimal and Quasi-Optimal Variable-Valued Logic Formulas , 1975 .

[33]  Douglas B. Lenat,et al.  AM, an artificial intelligence approach to discovery in mathematics as heuristic search , 1976 .

[34]  Edward H. Shortliffe,et al.  Computer-based medical consultations, MYCIN , 1976 .

[35]  Douglas B. Lenat,et al.  Designing a rule system that searches for scientific discoveries , 1977, SGAR.

[36]  James Burton Larson,et al.  Inductive inference in the variable valued predicate logic system vl21: methodology and computer implementation. , 1977 .

[37]  Edward M. Riseman,et al.  Levels of Pattern Description in Learning , 1977, IJCAI.

[38]  Ryszard S. Michalski,et al.  Inductive inference of VL decision rules , 1977, SGAR.

[39]  Ryszard S. Michalski,et al.  An Experiment on Inductive Learning in Chess End Games , 1977 .

[40]  Brian L. Cohen,et al.  A Powerful and Efficient Structural Pattern Recognition System , 1977, Artif. Intell..

[41]  John Darlington,et al.  A Transformation System for Developing Recursive Programs , 1977, J. ACM.

[42]  K S Fu,et al.  Syntactic Shape Recognition Using Attributed Grammars. , 1978 .

[43]  Bruce G. Buchanan,et al.  Dendral and Meta-Dendral: Their Applications Dimension , 1978, Artif. Intell..

[44]  D. L. Hintzman.  The psychology of learning and memory , 1978 .

[45]  Alan W. Biermann,et al.  The Inference of Regular LISP Programs from Examples , 1978, IEEE Transactions on Systems, Man, and Cybernetics.

[46]  Ryszard S. Michalski,et al.  Selection of Most Representative Training Examples and Incremental Generation of VL1 Hypotheses: The Underlying Methodology and the Description of Programs ESEL and AQ11 , 1978 .

[47]  Frederick Hayes-Roth,et al.  An interference matching technique for inducing abstractions , 1978, CACM.

[48]  T. Havránek,et al.  Mechanizing Hypothesis Formation: Mathematical Foundations for a General Theory , 1978 .

[49]  Daniel Kayser,et al.  Learning criterion and inductive behaviour , 1978, Pattern Recognit..

[50]  Tom Michael Mitchell.  Version spaces: an approach to concept learning. , 1979 .

[51]  Tom M. Mitchell,et al.  Models of Learning Systems. , 1979 .

[52]  Brian R. Gaines.  Maryanski's Grammatical Inferencer , 1979, IEEE Transactions on Computers.

[53]  Ronald J. Brachman,et al.  ON THE EPISTEMOLOGICAL STATUS OF SEMANTIC NETWORKS , 1979 .

[54]  John Gaschnig.  Development of uranium exploration models for the Prospector consultant system: final report covering the period September 22, 1978 to September 21, 1979 , 1980 .

[55]  Ryszard S. Michalski,et al.  Pattern Recognition as Rule-Guided Inductive Inference , 1980, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[56]  Keith Price,et al.  Review of "Artificial Intelligence: A Theoretical Approach by Ranan B. Banerji", North Holland, NY. , 1980, SGAR.

[57]  Douglas B. Lenat,et al.  Knowledge-based systems in artificial intelligence , 1981 .

[58]  Edwin Diday,et al.  A Recent Advance in Data Analysis: Clustering Objects into Classes Characterized by Conjunctive Concepts , 1981 .

[59]  Claude Sammut,et al.  Learning Concepts by Performing Experiments , 1981 .

[60]  Thomas G. Dietterich,et al.  Inductive Learning of Structural Descriptions: Evaluation Criteria and Comparative Review of Selected Methods , 1981, Artif. Intell..

[61]  Tom M. Mitchell,et al.  Generalization as Search , 2002 .

[62]  T. Niblett,et al.  AUTOMATIC INDUCTION OF CLASSIFICATION RULES FOR A CHESS ENDGAME , 1982 .

[63]  Ryszard S. Michalski,et al.  INDUCE.3: A Program for Learning Structural Descriptions from Examples , 1983 .

[64]  Ehud Shapiro,et al.  Inductive Inference of Theories from Facts , 1991, Computational Logic - Essays in Honor of Alan Robinson.