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Machine learning: a guide to current research
Recent progress on the mathematician's apprentice project
Machine learning: a guide to current research
Explanation-based manipulator learning
Machine learning: a guide to current research
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SOAR: an architecture for general intelligence
Artificial Intelligence
Principles of artificial intelligence
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The role of explicit contextual knowledge in learning concepts to improve performance
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Defining operationality for explanation-based learning
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Computer system architecture (3rd ed.)
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Program Transformation Systems
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Inductive Inference: Theory and Methods
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Dynamic Memory: A Theory of Reminding and Learning in Computers and People
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The Architecture of Cognition
A Computer Model of Skill Acquisition
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A Discipline of Programming
Chunking in Soar: The Anatomy of a General Learning Mechanism
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Explanation-Based Generalization: A Unifying View
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Editorial: The Terminology of Machine Learning
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Learning at the Knowledge Level
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On the Transformational Implementation approach to programming
ICSE '76 Proceedings of the 2nd international conference on Software engineering
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The chunking of goal hierarchies: a model of practice and stimulus-response compatibility
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ACM Transactions on Information Systems (TOIS)
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ACM Transactions on Graphics (TOG)
HyperActive: extending an open hypermedia architecture to support agency
ACM Transactions on Computer-Human Interaction (TOCHI)
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WSC '93 Proceedings of the 25th conference on Winter simulation
A feature-based learning method for theorem proving
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
SHAPES: A Novel Approach for Learning Search Heuristics in Under-Constrained Optimization Problems
IEEE Transactions on Knowledge and Data Engineering
An Application of Explanation-Based Learning to Protocol Conformance Testing
IEEE Expert: Intelligent Systems and Their Applications
Using Machine Learning Techniques in Real-World Mobile Robots
IEEE Expert: Intelligent Systems and Their Applications
Building and Exploiting Ad Hoc Concept Hierarchies for Web Log Analysis
DaWaK 2000 Proceedings of the 4th International Conference on Data Warehousing and Knowledge Discovery
Goal-directed concept acquisition in requirements elicitation
IWSSD '91 Proceedings of the 6th international workshop on Software specification and design
Functional reasoning theories: Problems and perspectives
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
Learning hierarchical task networks by observation
ICML '06 Proceedings of the 23rd international conference on Machine learning
Integrating data mining with case-based reasoning for chronic diseases prognosis and diagnosis
Expert Systems with Applications: An International Journal
Inferring graphical procedures: the compleat metarnouse
Human-Computer Interaction
Hierarchical Classifiers for Complex Spatio-temporal Concepts
Transactions on Rough Sets IX
An Inductive Logic Programming Approach to Statistical Relational Learning
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Second-order matching modulo evaluation: a technique for reusing proofs
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Intensional dynamic programming. A Rosetta stone for structured dynamic programming
Journal of Algorithms
Generating compiler optimizations from proofs
Proceedings of the 37th annual ACM SIGPLAN-SIGACT symposium on Principles of programming languages
On analytical and similarity-based classification
AAAI'90 Proceedings of the eighth National conference on Artificial intelligence - Volume 2
Assessing plausibility of explanation and meta-explanation in inter-human conflicts
Engineering Applications of Artificial Intelligence
Proceedings of the 20th ACM international conference on Information and knowledge management
Enhancing the Adaptation of BDI Agents Using Learning Techniques
International Journal of Agent Technologies and Systems
An evolutionary algorithm with a history mechanism for tuning a chess evaluation function
Applied Soft Computing
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Explanation-based learning (EBL) is a technique by which an intelligent system can learn by observing examples. EBL systems are characterized by the ability to create justified generalizations from single training instances. They are also distinguished by their reliance on background knowledge of the domain under study. Although EBL is usually viewed as a method for performing generalization, it can be viewed in other ways as well. In particular, EBL can be seen as a method that performs four different learning tasks: generalization, chunking, operationalization, and analogy.This paper provides a general introduction to the field of explanation-based learning. Considerable emphasis is placed on showing how EBL combines the four learning tasks mentioned above. The paper begins with a presentation of an intuitive example of the EBL technique. Subsequently EBL is placed in its historical context and the relation between EBL and other areas of machine learning is described. The major part of this paper is a survey of selected EBL programs, which have been chosen to show how EBL manifests each of the four learning tasks. Attempts to formalize the EBL technique are also briefly discussed. The paper concludes with a discussion of the limitations of EBL and the major open questions in the field.