Machine Learning - EWSL-91. European Working Session on Learning, Porto, Portugal, March 6-8, 1991. Proceedings. Lecture notes in computer science ; 482.

Kodratoff, Yves,

ISBN 10: 354053816X / ISBN 13: 9783540538165

Editore: Springer Berlin, 1991

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541 pages Ex-Library book in good condition. 9783540538165 Sprache: Englisch Gewicht in Gramm: 1020. Codice articolo 1166171

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Titolo: Machine Learning - EWSL-91. European Working...

Casa editrice: Springer Berlin

Data di pubblicazione: 1991

Legatura: Brossura

Descrizione articolo

Riassunto:

This book contains the proceedings of the 5th European Working Session on Learning (EWSL-91), which describes the most recent advances in the field, especially those originating from European research groups. The topics have been divided into groups covering new trends in machine learning (ML), such as in multi-strategy learning, inversion of resolution and multi-agents, as well as established topics such as discovery, numeric and statistical approaches, theorem proving and explanation-based learning, and case-based reasoning.

Contenuti:

Abstracting background knowledge for concept learning.- A multistrategy learning approach to domain modeling and knowledge acquisition.- Using plausible explanations to bias empirical generalization in weak theory domains.- The replication problem: A constructive induction approach.- Integrating an explanation-based learning mechanism into a general problem-solver.- Analytical negative generalization and empirical negative generalization are not cumulative: A case study.- Evaluating and changing representation in concept acquisition.- Application of empirical discovery in knowledge acquisition.- Using accuracy in scientific discovery.- KBG : A generator of knowledge bases.- On estimating probabilities in tree pruning.- Rule induction with CN2: Some recent improvements.- On changing continuous attributes into ordered discrete attributes.- A method for inductive cost optimization.- When does overfitting decrease prediction accuracy in induced decision trees and rule sets?.- Semi-naive bayesian classifier.- Description contrasting in incremental concept formation.- System FLORA: Learning from time-varying training sets.- Message-based bucket brigade: An algorithm for the apportionment of credit problem.- Acquiring object-knowledge for learning systems.- Learning nonrecursive definitions of relations with linus.- Extending explanation-based generalization by abstraction operators.- Static learning for an adaptative theorem prover.- Explanation-based generalization and constraint propagation with interval labels.- Learning by explanation of failures.- PANEL : Logic and learnability.- Panel on : Causality and learning.- Seed space and version space: Generalizing from approximations.- Integrating EBL with automatic text analysis.- Abduction for explanation-based learning.- Consistent term mappings, term partitions, and inverse resolution.- Learning by analogical replay in prodigy: First results.- Analogical reasoning for logic programming.- Case-based learning of strategic knowledge.- Learning in distributed systems and multi-agent environments.- Learning to relate terms in a multiple agent environment.- Extending learning to multiple agents: Issues and a model for multi-agent machine learning (MA-ML).- Applications of machine learning: Notes from the panel members.- Evaluation of learning systems : An artificial data-based approach.- Shift of bias in learning from drug compounds: The fleming project.- Learning features by experimentation in chess.- Representation and induction of musical structures for computer assisted composition.- IPSA: Inductive protein structure analysis.- Four stances on knowledge acquisition and machine learning.- Programme of EWSL-91.