K. Furukawa / D. Michie / S. Muggleton (eds.)

Machine Intelligence 14

Applied Machine Intelligence
Herausgeber: Furukawa, K.; Muggleton, S.; Michie, D.

• Gebundenes Buch

Produktbeschreibung

Machine Intelligence 14 contains material presented at the Anglo-Janpanese workshop of Novemver 1993 held at the Hitachi Research Laboratory. It marks the 70th birthday of Donald Michie, the founder of the series. The contents is divided into the following subjects: complex decision taking, inductive logic programming, applied machine learning, dynamic control, and computational learning theory. Applications include controlling a steel mill, discovery of protein structural constraints, and qualitative control for dynamic systems.

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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.

Produktdetails

• Verlag: Oxford University Press, USA
• Seitenzahl: 470
• Erscheinungstermin: 8. August 1996
• Englisch
• Abmessung: 241mm x 159mm x 34mm
• Gewicht: 880g
• ISBN-13: 9780198538608
• ISBN-10: 019853860X
• Artikelnr.: 21028401

Inhaltsangabe

* 1: Game mastery and intelligence
* 2: Reacting, planning, and learning in an autonomous agent
* 3: Multi-entity models
* 4: Putting knowledge rich plan represetnations to use
* 5: On dealing with dynamic utility of learned knowledge
* 6: Inverting entailment and progol
* 7: Learning logic programs and regularities from examples by
inductive inference
* 8: Variations and local exceptions in inductive logic programming
* 9: Inductive logic programming with large-scale unstructured data
* 10: Discovery of protein structural constraints in a deductive
database using inductive logic programming
* 11: Controlling a steel mill with BOXES
* 12: A reasoning system for legal analogy
* 13: Concept learning algorithm with adaptive search
* 14: Deriving qualitative control for dynamic systems
* 15: Behavioural clones and cognitive skill models
* 16: A classification of abduction: abduction for logic programming
* 17: Efficient algorithms for inductive learning - an application of
multi-linear functions to inductive learning