Computation, Causation, and Discovery - Brossura

Brossura

ISBN 10: 0262571242 ISBN 13: 9780262571241

Casa editrice: Aaai Pr, 1999

Riassunto

In science, business, and policymaking -- anywhere data are used in prediction -- two sorts of problems requiring very different methods of analysis often arise. The first, problems of recognition and classification, concerns learning how to use some features of a system to accurately predict other features of that system. The second, problems of causal discovery, concerns learning how to predict those changes to some features of a system that will result if an intervention changes other features. This book is about the second -- much more difficult -- type of problem.

Typical problems of causal discovery are: How will a change in commission rates affect the total sales of a company? How will a reduction in cigarette smoking among older smokers affect their life expectancy? How will a change in the formula a college uses to award scholarships affect its dropout rate? These sorts of changes are interventions that directly alter some features of the system and perhaps -- and this is the question -- indirectly alter others.

The contributors discuss recent research and applications using Bayes nets or directed graphic representations, including representations of feedback or "recursive" systems. The book contains a thorough discussion of foundational issues, algorithms, proof techniques, and applications to economics, physics, biology, educational research, and other areas.

Dettagli dell?edizione

• Editore: Aaai Pr
• Data di pubblicazione: 1999
• Lingua: Inglese
• ISBN 10: 0262571242
• ISBN 13: 9780262571241
• Rilegatura: Copertina flessibile
• Numero di pagine: 552
• Redattore: Glymour Clark, Cooper Gregory F.
• Contatto del produttore: non disponibile
• Persona responsabile: non disponibile