Intelligence is a complex, natural phenomenon exhibited by humans and many other living things, without sharply defined boundaries between intelligent and unintelligent behaviour. Artificial inteliigence focuses on the phenomenon of intelligent behaviour, in humans or machines. Experimentation with computer programs allows us to manipulate their design and intervene in the environmental conditions in ways that are not possible with humans. Thus, experimentation can help us to understand what principles govern intelligent action and what mechanisms are sufficient for computers to replicate intelligent behaviours.Phil. Trans. R. Soc. Lond. A. 1994 349 1689
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.
The field of AI is directed at the fundamental problem of how the mind works; its approach, among other things, is to try to simulate its working -- in bits and pieces. History shows us that mankind has been trying to do this for certainly hundreds of years, but the blooming of current computer technology has sparked an explosion in the research we can now do. The center of AI is the wonderful capacity we call learning, which the field is paying increasing attention to. Learning is difficult and easy, complicated and simple, and most research doesn't look at many aspects of its complexity. However, we in the AI field are starting. Let us now celebrate the efforts of our forebears and rejoice in our own efforts, so that our successors can thrive in their research. This article is the substance, edited and adapted, of the keynote address given at the 1992 annual meeting of the Association for the Advancement of Artificial Intelligence on 14 July in San Jose, California. AI Magazine 14(2): 36-48
See also:Yoav Shoham. An Overview of Agent-Oriented Programming. In Software agents, Jeffrey M. Bradshaw (Ed.). MIT Press, Cambridge, MA, USA 271-290.Yoav Shoham. Agent oriented programming. The Seventh Annual Workshop on Space Operations Applications and Research (SOAR 1993), Volume 1; p 303.Yoav Shoham. Agent oriented programming: An overview of the framework and summary of recent research. In Knowledge Representation and Reasoning Under Uncertainty. Lecture Notes in Computer Science, Volume 808, 1994, pp 123-129. Yoav Shoham. Final Report on AFOSR grant AF F49620-94-1-0090: Communication and coordination in multi-agent systems: agent-oriented programming and computational social laws. Robotics Laboratory, Computer Science Department, Stanford University. 6 December, 1996.Artificial Intelligence, 60 (1), 51-92