Classics


Intelligence in "Artificial" Wireless

Classics

The background of the presentation is a perspective on the development of wireless technology from 2000 to 2010. The foreground of the presentation is a contrasted understanding of intelligence in "natural" wireless (human communication) versus "artificial" wireless (communication between devices). Invited talk, presented at The Twelfth Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-2000), Austin, TX, August, 2000.


Provably bounded optimal agents

Classics

First appeared asRussell, S. J., Subramanian, D., and Parr, R. , "Provably bounded optimal agents", IJCAI-93, pp. 338-€“345. Journal of Artificial Intelligence Research, 1 (1995), pp.1-36.


Machine Learning, Neural and Statistical Classification

Classics

This book (originally published in 1994 by Ellis Horwood) is now out of print. The copyright now resides with the editors who have decided to make the material freely available on the web.This book is based on the EC (ESPRIT) project StatLog which compare and evaluated a range of classification techniques, with an assessment of their merits, disadvantages and range of application. This integrated volume provides a concise introduction to each method, and reviews comparative trials in large-scale commercial and industrial problems. It makes accessible to a wide range of workers the complex issue of classification as approached through machine learning, statistics and neural networks, encouraging a cross-fertilization between these discplines.




Neural Network Perception for Mobile Robot Guidance

Classics

Kluwer. See also Springer (https://www.springer.com/gp/book/9780792393733). See also: A Reply to Towell's Book Review of Neural Network Perception for Mobile Robot Guidance. Machine Learning, January 1995, Volume 18, Issue 1, pp 121–122 (https://link.springer.com/article/10.1007%2FBF00993825).


Statistical Language Learning

Classics

New, exacting empirical methods are needed to break the deadlock in such areas of artificial intelligence as robotics, knowledge representation, machine learning, machine translation, and natural language processing (NLP). It is time, Charniak observes, to switch paradigms. This text introduces statistical language processing techniques -- word tagging, parsing with probabilistic context free grammars, grammar induction, syntactic disambiguation, semantic word classes, word-sense disambiguation -- along with the underlying mathematics and chapter exercises. Charniak points out that as a method of attacking NLP problems, the statistical approach has several advantages. It is grounded in real text and therefore promises to produce usable results, and it offers an obvious way to approach learning: "one simply gathers statistics."