Conferences in DBLP
Thomas R. Gruber , Catherine Baudin , John H. Boose , Jay Webber Design Rationale Capture as Knowledge Acquisition. [Citation Graph (0, 0)][DBLP ] Conf ] Yolanda Gil A Domain-Independent Framework for Effective Experimentation in Planning. [Citation Graph (0, 0)][DBLP ] Conf ] Eric K. Jones Knowledge Refinement Using a High Level, Non-Technical Vocabulary. [Citation Graph (0, 0)][DBLP ] Conf ] Yong Ma , David C. Wilkins Improving the Performance of Inconsistent Knowledge Bases via Combined Optimization Method. [Citation Graph (0, 0)][DBLP ] Conf ] Susan Craw , Derek H. Sleeman The Flexibility of Speculative Refinement. [Citation Graph (0, 0)][DBLP ] Conf ] Michael A. Weintraub , Tom Bylander Generating Error Candidates for Assigning Blame in a Knowledge Base. [Citation Graph (0, 0)][DBLP ] Conf ] Michael de la Maza A Prototype Based Symbolic Concept Learning System. [Citation Graph (0, 0)][DBLP ] Conf ] Douglas H. Fisher , Jungsoon P. Yoo Combining Evidence of Deep and Surface Similarity. [Citation Graph (0, 0)][DBLP ] Conf ] Mary Gick , Stan Matwin The Importance of Causal Structure and Facts in Evaluating Explanations. [Citation Graph (0, 0)][DBLP ] Conf ] Peter M. Hastings , Steven L. Lytinen , Robert K. Lindsay Learning Words From Context. [Citation Graph (0, 0)][DBLP ] Conf ] Wayne Iba Modeling the Acquisition and Improvement of Motor Skkills. [Citation Graph (0, 0)][DBLP ] Conf ] Randolph M. Jones , Kurt VanLehn A Computational Model of Acquisition for Children's Addtion Strategies. [Citation Graph (0, 0)][DBLP ] Conf ] Michael I. Jordan , David E. Rumelhart Internal World Models and Supervised Learning. [Citation Graph (0, 0)][DBLP ] Conf ] Rick Kazman Babel: A Psychologically Plausible Cross-Linguistic Model of Lexical and Syntactic Acquisition. [Citation Graph (0, 0)][DBLP ] Conf ] Pat Langley , John A. Allen The Acquisition of Human Planning Expertise. [Citation Graph (0, 0)][DBLP ] Conf ] Robert Levinson , Richard Snyder Adaptive Pattern-Oriented Chess. [Citation Graph (0, 0)][DBLP ] Conf ] Joel D. Martin , Dorrit O. Billman Variability Bias and Category Learning. [Citation Graph (0, 0)][DBLP ] Conf ] Craig S. Miller , John E. Laird A Constraint-Motivated Model of Lexical Acquisition. [Citation Graph (0, 0)][DBLP ] Conf ] Sheldon Nicholl , David C. Wilkins Computer Modelling of Acquisition Orders in Child Language. [Citation Graph (0, 0)][DBLP ] Conf ] Thomas R. Shultz Simulating Stages of Human Cognitive Development With Connectionist Models. [Citation Graph (0, 0)][DBLP ] Conf ] Kurt VanLehn , Randolph M. Jones Learning Physics Via Explanation-Based Learning of Correctness and Analogical Search Control. [Citation Graph (0, 0)][DBLP ] Conf ] David W. Aha Incremental Constructive Induction: An Instance-Based Approach. [Citation Graph (0, 0)][DBLP ] Conf ] James P. Callan , Paul E. Utgoff A Transformational Approach to Constructive Induction. [Citation Graph (0, 0)][DBLP ] Conf ] David S. Day Learning Variable Descriptors for Applying Heuristics Across CSP Problems. [Citation Graph (0, 0)][DBLP ] Conf ] George Drastal Informed Pruning in Constructive Induction. [Citation Graph (0, 0)][DBLP ] Conf ] Tom Fawcett , Paul E. Utgoff A Hybrid Method for Feature Generation. [Citation Graph (0, 0)][DBLP ] Conf ] Attilio Giordana , Lorenza Saitta , Davide Roverso Abstracting Concepts with Inverse Resolution. [Citation Graph (0, 0)][DBLP ] Conf ] Gregg H. Gunsch , Larry A. Rendell Opportunistic Constructive Induction. [Citation Graph (0, 0)][DBLP ] Conf ] Carl Myers Kadie Quantifying the Value of Constructive Induction, Knowledge, and Noise Filtering on Inductive Learning. [Citation Graph (0, 0)][DBLP ] Conf ] Adam Kowalczyk , Herman L. Ferrá , Ken Gardiner Discovering Production Rules with Higher Order Neural Networks. [Citation Graph (0, 0)][DBLP ] Conf ] Bing Leng , Bruce G. Buchanan Constructive Induction on Symbolic Features. [Citation Graph (0, 0)][DBLP ] Conf ] Xiaofeng Ling , Malur Aji Narayan Comparison of Methods Based on Inverse Resolution. [Citation Graph (0, 0)][DBLP ] Conf ] Christopher J. Matheus The Need for Constructive Induction. [Citation Graph (0, 0)][DBLP ] Conf ] Raymond J. Mooney , Dirk Ourston Constructive Induction in Theory Refinement. [Citation Graph (0, 0)][DBLP ] Conf ] Patrick M. Murphy , Michael J. Pazzani Constructive Induction of M-of-N Terms. [Citation Graph (0, 0)][DBLP ] Conf ] Harish Ragavan , Larry A. Rendell Relations, Knowledge and Empirical Learning. [Citation Graph (0, 0)][DBLP ] Conf ] Arlindo L. Oliveira , Alberto L. Sangiovanni-Vincentelli Learning Concepts by Synthesizing Minimal Threshold Gate Networks. [Citation Graph (0, 0)][DBLP ] Conf ] Sharad Saxena On the Effect of Instance Representation on Generalization. [Citation Graph (0, 0)][DBLP ] Conf ] Glenn Silverstein , Michael J. Pazzani Relational Clichés: Constraining Induction During Relational Learning. [Citation Graph (0, 0)][DBLP ] Conf ] Richard S. Sutton , Christopher J. Matheus Learning Polynomial Functions by Feature Construction. [Citation Graph (0, 0)][DBLP ] Conf ] Geoffrey G. Towell , Mark Craven , Jude W. Shavlik Constructive Induction in Knowledge-Based Neural Networks. [Citation Graph (1, 0)][DBLP ] Conf ] Larry Watanabe , Larry A. Rendell Feature Construction in Structural Decision Trees. [Citation Graph (0, 0)][DBLP ] Conf ] Der-Shung Yang , Larry A. Rendell , Gunnar Blix Fringe-Like Feature Construction: A Comparative Study and a Unifying Scheme. [Citation Graph (0, 0)][DBLP ] Conf ] Dit-Yan Yeung A Neural Network Approach to Constructive Induction. [Citation Graph (0, 0)][DBLP ] Conf ] David D. Lewis Learning in Intelligent Information Retrieval. [Citation Graph (0, 0)][DBLP ] Conf ] Jay N. Bhuyan , Vijay V. Raghavan A Probabilistic Retrieval Scheme for Cluster-based Adaptive Information Retrieval. [Citation Graph (0, 0)][DBLP ] Conf ] Stuart L. Crawford , Robert M. Fung , Lee A. Appelbaum , Richard M. Tong Classification Trees for Information Retrieval. [Citation Graph (0, 0)][DBLP ] Conf ] Sanjiv K. Bhatia , Jitender S. Deogun , Vijay V. Raghavan Query Formulation Through Knowledge Acquisition. [Citation Graph (0, 0)][DBLP ] Conf ] A. Goker , T. L. McCluskey Incremental Learning in a Probalistic Information Retrieval System. [Citation Graph (0, 0)][DBLP ] Conf ] K. L. Kwok Query Learning Using an ANN with Adaptive Architecture. [Citation Graph (0, 0)][DBLP ] Conf ] Ashwin Ram , Lawrence Hunter A Goal-Based Approach to Intelligent Information Retrieval. [Citation Graph (0, 0)][DBLP ] Conf ] Paul Thompson Machine Learning in the Combination of Expert Opinion Approach to IR. [Citation Graph (0, 0)][DBLP ] Conf ] Steven Walczak Predicting Actions from Induction on Past Performance. [Citation Graph (0, 0)][DBLP ] Conf ] Matthew Brand Decision-Theoretic Learning in an Action System. [Citation Graph (0, 0)][DBLP ] Conf ] Steve A. Chien , Melinda T. Gervasio , Gerald DeJong On Becoming Decreasingly Reactive: Learning to Deliberate Minimally. [Citation Graph (0, 0)][DBLP ] Conf ] Helen G. Cobb , John J. Grefenstette Learning the Persistence of Actions in Reactive Control Rules. [Citation Graph (0, 0)][DBLP ] Conf ] José del R. Millán , Carme Torras Learning to Avoid Obstacles Through Reinforcement. [Citation Graph (0, 0)][DBLP ] Conf ] Goang-Tay Hsu , Reid G. Simmons Learning Football Evaluation for a Walking Robot. [Citation Graph (0, 0)][DBLP ] Conf ] Smadar Kedar , John L. Bresina , C. Lisa Dent The Blind Leading the Blind: Mutual Refinement of Approximate Theories. [Citation Graph (0, 0)][DBLP ] Conf ] Mieczyslaw M. Kokar , Spyros A. Reveliotis Learning to Select a Model in a Changing World. [Citation Graph (0, 0)][DBLP ] Conf ] Bruce Krulwich Learning from Deliberated Reactivity. [Citation Graph (0, 0)][DBLP ] Conf ] Long Ji Lin Self-improvement Based on Reinforcement Learning, Planning and Teaching. [Citation Graph (0, 0)][DBLP ] Conf ] Sridhar Mahadevan , Jonathan Connell Scaling Reinforcement Learning to Robotics by Exploiting the Subsumption Architecture. [Citation Graph (0, 0)][DBLP ] Conf ] Andrew W. Moore Variable Resolution Dynamic Programming. [Citation Graph (0, 0)][DBLP ] Conf ] David R. Pierce Learning a Set of Primitive Actions with an Uninterpreted Sensorimotor Apparatus. [Citation Graph (0, 0)][DBLP ] Conf ] Mark B. Ring Incremental Development of Complex Behaviors. [Citation Graph (0, 0)][DBLP ] Conf ] Satinder P. Singh Transfer of Learning Across Compositions of Sequentail Tasks. [Citation Graph (0, 0)][DBLP ] Conf ] Richard S. Sutton Planning by Incremental Dynamic Programming. [Citation Graph (0, 0)][DBLP ] Conf ] Ming Tan Learning a Cost-Sensitive Internal Representation for Reinforcement Learning. [Citation Graph (0, 0)][DBLP ] Conf ] Steven D. Whitehead Complexity and Cooperation in Q-Learning. [Citation Graph (0, 0)][DBLP ] Conf ] John A. Allen , Kevin Thompson Probabilistic Concept Formation in Relational Domains. [Citation Graph (0, 0)][DBLP ] Conf ] Michael Bain Experiments in Non-Monotonic Learning. [Citation Graph (0, 0)][DBLP ] Conf ] Ivan Bratko , Stephen Muggleton , Alen Varsek Learning Qualitative Models of Dynamic Systems. [Citation Graph (0, 0)][DBLP ] Conf ] Clifford Brunk , Michael J. Pazzani An Investigation of Noise-Tolerant Relational Concept Learning Algorithms. [Citation Graph (0, 0)][DBLP ] Conf ] Luc De Raedt , Maurice Bruynooghe , Bern Martens Integrity Constraints and Interactive Concept-Learning. [Citation Graph (0, 0)][DBLP ] Conf ] Saso Dzeroski , Nada Lavrac Learning Relations from Noisy Examples: An Empirical Comparison of LINUS and FOIL. [Citation Graph (1, 0)][DBLP ] Conf ] C. Feng Inducing Temporal Fault Diagnostic Rules from a Qualitative Model. [Citation Graph (0, 0)][DBLP ] Conf ] Kazuo Hiraki , John H. Gennari , Yoshinobu Yamamoto , Yuichiro Anzai Learning Spatial Relations from Images. [Citation Graph (0, 0)][DBLP ] Conf ] David Humme , Claude Sammut Using Inverse Resolution to Learn Relations from Experiments. [Citation Graph (0, 0)][DBLP ] Conf ] Boonserm Kijsirikul , Masayuki Numao , Masamichi Shimura Efficient Learning of Logic Programs with Non-determinant, Non-discriminating Literals. [Citation Graph (0, 0)][DBLP ] Conf ] Christopher Leckie , Ingrid Zukerman Learning Search Control Rules for Planning: An Inductive Approach. [Citation Graph (0, 0)][DBLP ] Conf ] C. David Page Jr. , Alan M. Frisch Learning Constrained Atoms. [Citation Graph (0, 0)][DBLP ] Conf ] Michael J. Pazzani , Clifford Brunk , Glenn Silverstein A Knowledge-intensive Approach to Learning Relational Concepts. [Citation Graph (1, 0)][DBLP ] Conf ] Zhaogang Qian , Keki B. Irani The Consistent Concept Axiom. [Citation Graph (0, 0)][DBLP ] Conf ] J. Ross Quinlan Determinate Literals in Inductive Logic Programming. [Citation Graph (0, 0)][DBLP ] Conf ] Bradley L. Richards , Raymond J. Mooney First-Order Theory Revision. [Citation Graph (1, 0)][DBLP ] Conf ] Céline Rouveirol Completeness for Inductive Procedures. [Citation Graph (0, 0)][DBLP ] Conf ] Rüdiger Wirth , Paul O'Rorke Constraints on Predicate Invention. [Citation Graph (0, 0)][DBLP ] Conf ] James Wogulis Revising Relational Domain Theories. [Citation Graph (0, 0)][DBLP ] Conf ] Kenji Yamanishi , Akihiko Konagaya Learning Stochastic Motifs from Genetic Sequences. [Citation Graph (0, 0)][DBLP ] Conf ] Hamid R. Berenji Refinement of Approximate Reasoning-based Controllers by Reinforcement Learning. [Citation Graph (1, 0)][DBLP ] Conf ] Marco Botta , S. Ravotto , Lorenza Saitta , S. B. Sperotto Improving Learning Using Causality and Abduction. [Citation Graph (0, 0)][DBLP ] Conf ] Timothy Cain The DUCTOR: A Theory Revision System for Propositional Domains. [Citation Graph (0, 0)][DBLP ] Conf ] William W. Cohen The Generality of Overgenerality. [Citation Graph (0, 0)][DBLP ] Conf ] Marie desJardins Probabilistic Evaluating of Bias for Learning Systems. [Citation Graph (0, 0)][DBLP ] Conf ] Ronen Feldman , Alberto Maria Segre , Moshe Koppel Incremental Refinement of Approximate Domain Theories. [Citation Graph (0, 0)][DBLP ] Conf ] Diana F. Gordon An Enhancer for Reactive Plans. [Citation Graph (0, 0)][DBLP ] Conf ] Jonathan Gratch , Gerald DeJong A Hybrid Approach to Guaranteed Effective Control Strategies. [Citation Graph (0, 0)][DBLP ] Conf ] Rei Hamakawa Revision Cost for Theory Refinement. [Citation Graph (0, 0)][DBLP ] Conf ] Xiaofeng Ling , Marco Valtorta Revision of Reduced Theories. [Citation Graph (0, 0)][DBLP ] Conf ] Richard Maclin , Jude W. Shavlik Refining Domain Theories Expressed as Finite-State Automata. [Citation Graph (0, 0)][DBLP ] Conf ] Claire Nedellec A Smallest Generalization Step Strategy. [Citation Graph (0, 0)][DBLP ] Conf ] Dirk Ourston , Raymond J. Mooney Improving Shared Rules in Multiple Category Domain Theories. [Citation Graph (0, 0)][DBLP ] Conf ] Wei-Min Shen Discovering Regularities from Large Knowledge Bases. [Citation Graph (0, 0)][DBLP ] Conf ] Prasad Tadepalli Learning with Incrutable Theories. [Citation Graph (0, 0)][DBLP ] Conf ] Gheorghe Tecuci , Ryszard S. Michalski A Method for Multistrategy Task-Adaptive Learning Based on Plausible Justifications. [Citation Graph (0, 0)][DBLP ] Conf ] Kevin Thompson , Pat Langley , Wayne Iba Using Background Knowledge in Concept Formation. [Citation Graph (0, 0)][DBLP ] Conf ] Bradley L. Whitehall , Stephen C. Y. Lu A Study of How Domain Knowledge Improves Knowledge-Based Learning Systems. [Citation Graph (0, 0)][DBLP ] Conf ] Edward J. Wisniewski , Douglas L. Medin Is it a Pocket or a Purse? Tighly Coupled Theory and Data Driven Learing. [Citation Graph (0, 0)][DBLP ] Conf ] Jungsoon P. Yoo , Douglas H. Fisher Identifying Cost Effective Boundaries of Operationality. [Citation Graph (0, 0)][DBLP ] Conf ] Steve A. Chien , Bradley L. Whitehall , Thomas G. Dietterich , Richard J. Doyle , Brian Falkenhainer , James Garrett , Stephen C. Y. Lu Machine Learning in Engineering Automation. [Citation Graph (0, 0)][DBLP ] Conf ] Leonid V. Belyaev , Loretta P. Falcone Noise-Resistant Classification. [Citation Graph (0, 0)][DBLP ] Conf ] Scott Bennett , Gerald DeJong Comparing Stochastic Planning to the Acquisition of Increasingly Permissive Plans. [Citation Graph (0, 0)][DBLP ] Conf ] Gautam Biswas , Jerry B. Weinberg , Qian Yang , Glenn R. Koller Conceptual Clustering and Exploratory Data Analysis. [Citation Graph (0, 0)][DBLP ] Conf ] Jason Catlett Megainduction: A Test Flight. [Citation Graph (0, 0)][DBLP ] Conf ] Giuseppe Cerbone , Thomas G. Dietterich Knowledge Compilation to Speed Up Numerical Optimization. [Citation Graph (0, 0)][DBLP ] Conf ] Ashok K. Goel Model Revision: A Theory of Incremental Model Learning. [Citation Graph (0, 0)][DBLP ] Conf ] Jürgen Herrmann Learning Analytical Knowledge About VLSI-Design from Observation. [Citation Graph (0, 0)][DBLP ] Conf ] Carl Myers Kadie Continous Conceptual Set Covering: Learning Robot Operators From Examples. [Citation Graph (0, 0)][DBLP ] Conf ] Paul O'Rorke , Steven Morris , Michael Amirfathi , William Bond , Daniel C. St. Clair Machine Learning for Nondestructive Evaluation. [Citation Graph (0, 0)][DBLP ] Conf ] Peter Pachowicz , Jerzy W. Bala Improving Recognition Effectiveness of Noisy Texture Concepts. [Citation Graph (0, 0)][DBLP ] Conf ] R. Bharat Rao , Stephen C. Y. Lu , Robert E. Stepp Knowledge-Based Equation Discovery in Engineering Domains. [Citation Graph (0, 0)][DBLP ] Conf ] Yoram Reich Design Integrated Learning Systems for Engineering Design. [Citation Graph (0, 0)][DBLP ] Conf ] Jeffrey C. Schlimmer Database Consistency via Inductive Learning. [Citation Graph (0, 0)][DBLP ] Conf ] David K. Tcheng , Bruce L. Lambert , Stephen C. Y. Lu , Larry A. Rendell AIMS: An Adaptive Interactive Modeling System for Supporting Engineering Decision Making. [Citation Graph (0, 0)][DBLP ] Conf ] Larry Watanabe , Sudhakar Yerramareddy Decision Tree Induction of 3-D Manufacturing Features. [Citation Graph (0, 0)][DBLP ] Conf ] Mario Martin , Ramon Sangüesa , Ulises Cortés Knowledge Acquisition Combining Analytical and Empirrcal Techniques. [Citation Graph (0, 0)][DBLP ] Conf ] Lambert E. Wixson Scaling Reinforcement Learning Techniques via Modularity. [Citation Graph (0, 0)][DBLP ] Conf ] 