This note provides an introduction to artificial intelligence.
Topics covered include: representation and inference in first-order logic,
modern deterministic and decision-theoretic planning techniques, basic
supervised learning methods, and Bayesian network inference and learning.
Author(s): Prof. Tomas Lozano-Perez and Prof.
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. It provides a concise introduction to each method, and
reviews comparative trials in large-scale commercial and industrial problems.
Author(s): D. Michie, D.J. Spiegelhalter, C.C. Taylor
AI is the part of computer science concerned with designing intelligent
computer systems, that is, computer systems that exhibit the characteristics we
associate with intelligence in human behaviour - understanding language,
learning, reasoning and solving problems .A theme we will develop in this course
note is that most AI systems can broken into: Search, Knowledge Representation
and applications of the above.
This book covers the following
topics: Introduction to Type Theory, Statements and Definitions in Nuprl,
Proofs, Proof Tactics, System Description, The Rules, The Metalanguage, Building
Theories, Recursive definition.
and Information Science, Cornell University