| Abstract: | Reviews the book, Connectionism: A Hands-On Approach by Michael R. W. Dawson (see record 2005-05691-000). This book is intended to be a practical introduction to connectionist models and neural networks. The book uses, as examples, simple connectionist models that have been studied over the years, with each chapter dedicated to a slightly more complex model or problem than the previous. The author also provides links to a web page where sample programs can be downloaded, allowing the reader to use these programs as they progress through the book. Although the book is well written, it falls short of its objective of being an introduction to connectionism. The book does not claim to be focused on connectionist theory, but its lack of a theoretical basis makes it difficult to follow. Throughout the book, there are references to another work by the author entitled Minds and Machines, which the reader can reference for the theoretical basis and background of connectionist models, and this may indicate the preferred use of the current book. This book falls short as a stand-alone text, but could make a decent workbook to supplement a theoretical text on connectionism. Those who are looking to expand into actually implementing these algorithms would be better served by packages such as PDP, SNNS, or even Matlab, but the book could still be useful to those who want to get a taste of how these algorithms work. The niche of this book seems to be for professors who want a "hands-on" supplement for their main text, but want to avoid too much depth on the math or implementation. (PsycINFO Database Record (c) 2010 APA, all rights reserved) |
