McGraw-Hill, 1991 - 621 páginas
The breadth of A. I. is explored and explained in this best selling text. Assuming no prior knowledge,it covers topics like neural networks and robotics. This text explores the range of problems which have been and remain to be solved using A. I. tools and techniques. The second half of this text is an excellent reference.
Resultados 1-3 de 75
17.2 Rote Learning 448 17.3 Learning by Taking Advice 450 17.4 Learning in
Problem Solving 452 17.5 Learning from Examples: Induction 457 17.6
Explanation-Based Learning 471 17.7 Discovery 475 17.8 Analogy 479 17.9
computer programs, e.g., database systems, can be said to "learn" in this sense,
although most people would not call such simple storage learning. However,
many AI programs are able to improve their performance substantially through ...
Like many other AI problems, learning has attracted the attention of
mathematicians and theoretical computer scientists. Inductive learning in
particular has received considerable attention. Valiant  describes a "theory
of the learnable" ...
Comentarios de la gente - Escribir un comentario
Calificaciones de los usuarios
very poor book for novice.Assumes u already know AI and the language is not at all user friendly.One has to read a sentence repeatedly to get a grasp and some times even then u don't understand.Go for other books much better than this
not soo good to go for novice
What Is Artificial Intelligence?
Problems Problem Spaces and Search
Heuristic Search Techniques
Derechos de autor
Otras 21 secciones no mostradas