Abstraction Super-Structuring Normal Forms: Towards a Theory of Structural Induction

[1]  J. Bennett,et al.  Enquiry Concerning Human Understanding , 2010 .

[2]  Nir Friedman,et al.  Learning Hidden Variable Networks: The Information Bottleneck Approach , 2005, J. Mach. Learn. Res..

[3]  Mark Burgin,et al.  Super-Recursive Algorithms , 2004, Monographs in Computer Science.

[4]  Marcus Hutter Simulation Algorithms for Computational Systems Biology , 2017, Texts in Theoretical Computer Science. An EATCS Series.

[5]  Tom Armstrong,et al.  On the Relationship between Lexical Semantics and Syntax for the Inference of Context-Free Grammars , 2004, AAAI.

[6]  Jürgen Schmidhuber,et al.  Shifting Inductive Bias with Success-Story Algorithm, Adaptive Levin Search, and Incremental Self-Improvement , 1997, Machine Learning.

[7]  Christopher R. Hitchcock Introduction: What is the Philosophy of Science , 2004 .

[8]  C. Habel,et al.  Language , 1931, NeuroImage.

[9]  David L. Dowe,et al.  Minimum Message Length and Kolmogorov Complexity , 1999, Comput. J..

[10]  Michael I. Jordan Graphical Models , 2003 .

[11]  Gary James Jason,et al.  The Logic of Scientific Discovery , 1988 .

[12]  Judea Pearl,et al.  Probabilistic reasoning in intelligent systems , 1988 .

[13]  Arto Salomaa,et al.  Computation and Automata , 1984 .

[14]  Walter J. Savitch,et al.  How to Make Arbitrary Grammars Look Like Context-Free Grammars , 1973, SIAM J. Comput..

[15]  S.-Y. Kuroda,et al.  Classes of Languages and Linear-Bounded Automata , 1964, Inf. Control..

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

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

[18]  A. Turing On Computable Numbers, with an Application to the Entscheidungsproblem. , 1937 .

[19]  A. J. Ayer,et al.  Language, Truth, and Logic , 1936 .

[20]  M. Kendall,et al.  The Logic of Scientific Discovery. , 1959 .