Mohlo by se vám také líbit

Více informací o knize Optimization Methods for Logical Inference

• Parametry knihy
• Anotace
• Oblíbené z jiného soudku

Nákupem získáte 450 bodů

Anotace knihy

Merging logic and mathematics in deductive inference--an innovative, cutting--edge approach. Optimization methods for logical inference? Absolutely, say Vijay Chandru and John Hooker, two major contributors to this rapidly expanding field. And even though "solving logical inference problems with optimization methods may seem a bit like eating sauerkraut with chopsticks...it is the mathematical structure of a problem that determines whether an optimization model can help solve it, not the context in which the problem occurs." Presenting powerful, proven optimization techniques for logic inference problems, Chandru and Hooker show how optimization models can be used not only to solve problems in artificial intelligence and mathematical programming, but also have tremendous application in complex systems in general. They survey most of the recent research from the past decade in logic/optimization interfaces, incorporate some of their own results, and emphasize the types of logic most receptive to optimization methods--propositional logic, first order predicate logic, probabilistic and related logics, logics that combine evidence such as Dempster--Shafer theory, rule systems with confidence factors, and constraint logic programming systems. Requiring no background in logic and clearly explaining all topics from the ground up, Optimization Methods for Logical Inference is an invaluable guide for scientists and students in diverse fields, including operations research, computer science, artificial intelligence, decision support systems, and engineering.

Parametry knihy

Zařazení knihy Knihy v angličtině Mathematics & science Mathematics Mathematical foundations

• Plný název: Optimization Methods for Logical Inference
• Autor: Vijay Chandru, John Hooker
• Jazyk: Angličtina
• Vazba: Pevná
• Počet stran: 366
• EAN: 9780471570356
• ISBN: 0471570354
• ID: 04892211
• Nakladatelství: John Wiley & Sons Inc
• Hmotnost: 726 g
• Rozměry: 241 × 165 × 26 mm
• Datum vydání: 14. April 1999

Oblíbené z jiného soudku

---

---

---