學習論
Learning and Memory 豆瓣
作者: Mark A. Gluck / Eduardo Mercado Worth Publishers 2013 - 1
Rigorously updated, with a new modular format, the second edition of Learning and Memory brings a modern perspective to the study of this key topic. Reflecting the growing importance of neuroscience in the field, it compares brain studies and behavioural approaches in human and other animal species, and is available in full-color throughout.
The Art of Doing Science and Engineering: Learning to Learn 豆瓣
作者: Richard R. Hamming CRC 1997
Highly effective thinking is an art that engineers and scientists can be taught to develop. By presenting actual experiences and analyzing them as they are described, the author conveys the developmental thought processes employed and shows a style of thinking that leads to successful results is something that can be learned. Along with spectacular successes, the author also conveys how failures contributed to shaping the thought processes.
Provides the reader with a style of thinking that will enhance a person's ability to function as a problem-solver of complex technical issues. Consists of a collection of stories about the author's participation in significant discoveries, relating how those discoveries came about and, most importantly, provides analysis about the thought processes and reasoning that took place as the author and his associates progressed through engineering problems.
Probably Approximately Correct 豆瓣 Goodreads
作者: Leslie Valiant Basic Books 2013 - 6
How does life prosper in a complex and erratic world? While we know that nature follows patterns - such as the law of gravity - our everyday lives are beyond what known science can predict. We nevertheless muddle through even in the absence of theories of how to act. But how do we do it? In Probably Approximately Correct, computer scientist Leslie Valiant presents a masterful synthesis of learning and evolution to show how both individually and collectively we not only survive, but prosper in a world as complex as our own. The key is "probably approximately correct" algorithms, a concept Valiant developed to explain how effective behavior can be learned. The model shows that pragmatically coping with a problem can provide a satisfactory solution in the absence of any theory of the problem. After all, finding a mate does not require a theory of mating. Valiant's theory reveals the shared computational nature of evolution and learning, and sheds light on perennial questions such as nature versus nurture and the limits of artificial intelligence.
Learning and Memory 豆瓣
作者: John R. Anderson Wiley 2000 - 1
From one of the leading researchers in the field of human memory comes the new edition of a truly integrative perspective on learning and memory! Rather than forge a simple synthesis, Anderson integrates learning research on animals and memory research on humans without distorting the character of either one. The result is a more complete picture of learning, including material on skill acquisition, inductive learning, and applications to education.