Artificial Intelligence and Molecular Biology
by Lawrence Hunter
Publisher: AAAI Press 1993
Number of pages: 467
These original contributions provide a current sampling of AI approaches to problems of biological significance; they are the first to treat the computational needs of the biology community hand-in-hand with appropriate advances in artificial intelligence. Focusing on novel technologies and approaches, rather than on proven applications, they cover genetic sequence analysis, protein structure representation and prediction, automated data analysis aids, and simulation of biological systems. A brief introductory primer on molecular biology and Al gives computer scientists sufficient background to understand much of the biology discussed in the book.
Download or read it online for free here:
by William John Teahan - BookBoon
This book adopts a behaviour-based approach to the design of agent-oriented systems. The topics covered from a behaviour-based perspective include agent communication, searching, knowledge and reasoning, and intelligence.
by Neil C. Rowe - Prentice-Hall
Artificial intelligence is a hard subject to learn. The author have written a book to make it easier. He explains difficult concepts in a simple, concrete way. This book is intended for all first courses in artificial intelligence.
by Ahmed Rebai (ed.) - InTech
Bayesian networks are a general tool that can be used for a large number of problems involving uncertainty: reasoning, learning, planning and perception. This is a collection of contributions to the methodology and applications of Bayesian networks.
by Yoav Shoham, Kevin Leyton-Brown - Cambridge University Press
Multiagent systems consist of multiple autonomous entities having different information and diverging interests. This comprehensive introduction to the field offers a computer science perspective, but also draws on ideas from game theory.