Artificial Intelligence
Structured induction in expert systems
Structured induction in expert systems
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Computational Feasibility of Structured Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations
Structured matching: a task-specific technique for making decisions
Knowledge Acquisition
Knowledge-based artificial neural networks
Artificial Intelligence
Steps toward artificial intelligence
Computers & thought
Introspective multistrategy learning: on the construction of learning strategies
Artificial Intelligence
Evaluating PSMs in evolutionary design: the Autognostic experiments
International Journal of Human-Computer Studies
Machine Learning
Guest Editor's Introduction: Creating Robust Software through Self-Adaptation
IEEE Intelligent Systems
Systems That Know What They're Doing
IEEE Intelligent Systems
Knowledge Acquisition Via Incremental Conceptual Clustering
Machine Learning
ECML '95 Proceedings of the 8th European Conference on Machine Learning
Explanation-Based Neural Network Learning for Robot Control
Advances in Neural Information Processing Systems 5, [NIPS Conference]
Learning about Constraints by Reflection
AI '01 Proceedings of the 14th Biennial Conference of the Canadian Society on Computational Studies of Intelligence: Advances in Artificial Intelligence
Hierarchical Mixtures of Experts and the EM Algorithm
Hierarchical Mixtures of Experts and the EM Algorithm
Evolving Soccer Keepaway Players Through Task Decomposition
Machine Learning
Metacognition in computation: a selected research review
Artificial Intelligence
Meta-case-based reasoning: self-improvement through self-understanding
Journal of Experimental & Theoretical Artificial Intelligence
Using introspective reasoning to refine indexing
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Some studies in machine learning using the game of checkers
IBM Journal of Research and Development
Teleological Software Adaptation
SASO '09 Proceedings of the 2009 Third IEEE International Conference on Self-Adaptive and Self-Organizing Systems
Complexity in classificatory reasoning
AAAI'87 Proceedings of the sixth National conference on Artificial intelligence - Volume 2
Model-based diagnosis of planning failures
AAAI'90 Proceedings of the eighth National conference on Artificial intelligence - Volume 1
Knowledge-Based Systems
Empirically-based self-diagnosis and repair of domain knowledge
Empirically-based self-diagnosis and repair of domain knowledge
Metareasoning: Thinking about Thinking
Metareasoning: Thinking about Thinking
Model based diagnosis and contexts in self adaptive software
Self-star Properties in Complex Information Systems
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We view incremental experiential learning in intelligent software agents as progressive agent self-adaptation. When an agent produces an incorrect behavior, then it may reflect on, and thus diagnose and repair, the reasoning and knowledge that produced the incorrect behavior. In particular, we focus on the self-diagnosis and self-repair of an agent's domain knowledge. The core issue that this article addresses is: what kind of metaknowledge may enable the agent to diagnose faults in its domain knowledge? To address this question, we propose a representation that explicitly encodes metaknowledge in the form of Empirical Verification Procedures (EVPs). In the proposed knowledge representation, an EVP may be associated with each concept within the agent's domain knowledge. Each EVP explicitly semantically grounds the associated concept in the agent's perception, and can thus be used as a test to determine the validity of knowledge of that concept during diagnosis. We present the empirical evaluation of a system, Augur, that makes use of EVP metaknowledge to adapt its own domain knowledge in the context of a particular subclass of classification problem called Compositional Classification.