- Inbunden (Hardback)
- Antal sidor
- Clarendon Press
- Michie, D. / Muggleton, S.
- Machine Intelligence and Inductive Learning
- 229 x 152 x 32 mm
- Antal komponenter
- 890 g
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Machine Intelligence 13
Machine Intelligence and Inductive Learningav K Furukawa2519
BL Leaders in the discipline discuss the latest developments in a fast moving field
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This book is the latest volume in a successful series - the result of a fruitful collaboration between the Turing Institute and the Japan Society for Artificial Intelligence.
This volume stems from a workshop held in 1992, which not only witnessed the series enter its second quarter century but also a new phase in its development. The pages of this book show that machine learning has emerged to declare itself as a seed bed of new theory, as a practical took in engineering disciplines, and as a material for new mental models in human sciences.
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Fler böcker av K Furukawa
This 14th volume of the classic series on machine intelligence contains papers on complex decision taking, inductive logic programming, applied machine learning, dynamic control, and computational learning theory.
E Goto, K Furukawa, R Nakajima, I Nakata, A Yonezawa
Partial computation of programs.- Treatment of big values in an applicative language HFP.- Toward the design and implementation of object oriented architecture.- DURAL: an extended Prolog language.- An algorithm for intelligent backtracking.- A pa...
Recensioner i media
Endeavour the current volume maintains the high standards set by its predecessors... authored by distinguished researchers...
1. Logic, Computers, Turing, and von Neumann; 2. Logic and Learning: Turing's Legacy; 3. A Generalization of the Least Generalization; 4. The Justification of Logical Theories based on Data Compression; 5. Utilizing Structure Information in Concept Formation; 6. The Discovery of Propositions in Noisy Data; 7. Learning Non-deterministic Finite Automata from Queries and Counterexamples; 8. Machine Learning and Biomolecular Modelling; 9. More than Meets the eye: Animal Learning and Knowledge Induction; 10. Regulation of Human Cognition and its growth; 11. Large Heterogeneous Knowledge Basis; 12. Learning Optimal Chess Strategies; 13. A Comparative Study of Classification Algorithms; 14. Recent Progress with BOXES; 15. Building Symbolic Representations of Intuitive 0.00-time Skills from Performance Data; 16. Learning Perceptually Chunked Macro Operators; 17. Inductively Speeding up Logic Programs