Neural-Symbolic Learning Systems

[1]  Raymond J. Mooney,et al.  Symbolic and neural learning algorithms: An experimental comparison , 1991, Machine Learning.

[2]  Raymond Reiter,et al.  A Logic for Default Reasoning , 1987, Artif. Intell..

[3]  Jude W. Shavlik,et al.  Training Knowledge-Based Neural Networks to Recognize Genes , 1990, NIPS.

[4]  John McCarthy,et al.  Epistemological challenges for connectionism , 1988, Behavioral and Brain Sciences.

[5]  David Makinson,et al.  Five faces of minimality , 1993, Stud Logica.

[6]  John L. Pollock,et al.  Defeasible Reasoning , 2020, Synthese Library.

[7]  Geoffrey G. Towell,et al.  Symbolic knowledge and neural networks: insertion, refinement and extraction , 1992 .

[8]  G. Stormo Consensus patterns in DNA. , 1990, Methods in enzymology.

[9]  Saso Dzeroski,et al.  Inductive Logic Programming: Techniques and Applications , 1993 .

[10]  Sebastian Thrun,et al.  Extracting Provably Correct Rules from Artificial Neural Networks , 1993 .

[11]  Robert C. Moore Semantical Considerations on Nonmonotonic Logic , 1985, IJCAI.

[12]  David W. Opitz,et al.  An anytime approach to connectionist theory refinement - refining the topologies of knowledge-based neural networks , 1996, Technical Report / University of Wisconsin, Madison / Computer Sciences Department.

[13]  Nada Lavrac,et al.  The Multi-Purpose Incremental Learning System AQ15 and Its Testing Application to Three Medical Domains , 1986, AAAI.

[14]  Michael C. Mozer,et al.  Rule Induction through Integrated Symbolic and Subsymbolic Processing , 1991, NIPS.

[15]  Victor W. Marek,et al.  Nonmonotonic logic - context-dependent reasoning , 1997, Artificial intelligence.

[16]  Sebastian Thrun,et al.  The MONK''s Problems-A Performance Comparison of Different Learning Algorithms, CMU-CS-91-197, Sch , 1991 .

[17]  Mary Shaw,et al.  Comparing Architectural Design Styles , 1995, IEEE Softw..

[18]  Raymond J. Mooney,et al.  Theory Refinement Combining Analytical and Empirical Methods , 1994, Artif. Intell..

[19]  Raymond J. Mooney,et al.  Integrating ILP and EBL , 1994, SGAR.

[20]  Jude Shavlik,et al.  THE EXTRACTION OF REFINED RULES FROM KNOWLEDGE BASED NEURAL NETWORKS , 1993 .

[21]  Luc De Raedt,et al.  Inductive Logic Programming: Theory and Methods , 1994, J. Log. Program..

[22]  David W. Opitz,et al.  Heuristically Expanding Knowledge-Based Neural Networks , 1993, IJCAI.

[23]  Rudy Setiono,et al.  A Penalty-Function Approach for Pruning Feedforward Neural Networks , 1997, Neural Computation.

[24]  Tim Menzies,et al.  Applications of abduction: knowledge-level modelling , 1996, Int. J. Hum. Comput. Stud..

[25]  Robert A. Kowalski,et al.  The Semantics of Predicate Logic as a Programming Language , 1976, JACM.

[26]  Ryszard S. Michalski,et al.  Learning Strategies and Automated Knowledge Acquisition , 1987 .

[27]  L. Shastri,et al.  From Simple Associations to Systemic Reasoning: A Connectionist Representation of Rules, Variables and Dynamic Bindings , 1990 .

[28]  Jude W. Shavlik,et al.  Using Symbolic Learning to Improve Knowledge-Based Neural Networks , 1992, AAAI.

[29]  Randy Goebel,et al.  Computational intelligence - a logical approach , 1998 .

[30]  Marvin Minsky,et al.  Logical vs. analogical or symbolic vs. connectionist or neat vs. scruffy , 1991 .

[31]  J. Ross Quinlan,et al.  Induction of Decision Trees , 1986, Machine Learning.

[32]  Kenneth A. Ross,et al.  The well-founded semantics for general logic programs , 1991, JACM.

[33]  Rudy Setiono,et al.  Extracting Rules from Neural Networks by Pruning and Hidden-Unit Splitting , 1997, Neural Computation.

[34]  Jude Shavlik An Overview of Research at Wisconsin on Knowledge-Based Neural Networks , 1996 .

[35]  Axel van Lamsweerde,et al.  Requirements engineering in the year 00: a research perspective , 2000, Proceedings of the 2000 International Conference on Software Engineering. ICSE 2000 the New Millennium.

[36]  Gadi Pinkas,et al.  Reasoning, Nonmonotonicity and Learning in Connectionist Networks that Capture Propositional Knowledge , 1995, Artif. Intell..

[37]  M. O'Neill Escherichia coli promoters. I. Consensus as it relates to spacing class, specificity, repeat substructure, and three-dimensional organization. , 1989, The Journal of biological chemistry.

[38]  John G. Taylor Promise of neural networks , 1993, Perspectives in neural computing.

[39]  Bashar Nuseibeh,et al.  An Abductive Approach for Handling Inconsistencies in SCR Specifications , 2000 .

[40]  J. Pearl Causality: Models, Reasoning and Inference , 2000 .

[41]  Hava T. Siegelmann,et al.  On the Computational Power of Neural Nets , 1995, J. Comput. Syst. Sci..

[42]  Huan Liu,et al.  NeuroLinear: From neural networks to oblique decision rules , 1997, Neurocomputing.

[43]  Frédéric Maire,et al.  Rule-extraction by backpropagation of polyhedra , 1999, Neural Networks.

[44]  James R. Williamson,et al.  A Constructive, Incremental-Learning Network for Mixture Modeling and Classification , 1997, Neural Computation.

[45]  Lokendra Shastri,et al.  Advances in SHRUTI—A Neurally Motivated Model of Relational Knowledge Representation and Rapid Inference Using Temporal Synchrony , 1999, Applied Intelligence.

[46]  Ah Chung Tsoi,et al.  Lessons in Neural Network Training: Overfitting May be Harder than Expected , 1997, AAAI/IAAI.

[47]  Ron Sun,et al.  Robust Reasoning: Integrating Rule-Based and Similarity-Based Reasoning , 1995, Artif. Intell..

[48]  Saso Dzeroski,et al.  Experiments In Learning Nonrecursive Definitions Of Relations With Linus , 1991 .

[49]  Sebastian Thrun,et al.  Explanation Based Learning: A Comparison of Symbolic and Neural Network Approaches , 1993, ICML.

[50]  Saso Dzeroski,et al.  Background Knowledge and Declarative Bias in Inductive Concept Learning , 1992, AII.

[51]  Radek Vingralek Connectionist Approach to Finding Stable Models and Other Structures in Nonmonotonic Reasoning , 1993, LPNMR.

[52]  Leslie G. Valiant,et al.  A theory of the learnable , 1984, CACM.

[53]  Andrea Zisman,et al.  Inconsistency Management in Software Engineering: Survey and Open Research Issues , 2000 .

[54]  Jacek M. Zurada,et al.  Extraction of linguistic rules from data via neural networks and fuzzy approximation , 2000 .

[55]  Lokendra Shastri A Connectionist Approach to Knowledge Representation and Limited Inference , 1988 .

[56]  Henry Prakken,et al.  Argument-Based Extended Logic Programming with Defeasible Priorities , 1997, J. Appl. Non Class. Logics.

[57]  Bashar Nuseibeh,et al.  An Abductive Approach for Analysing Event-Based Requirements Specifications , 2002, ICLP.