Introduction to Machine Learning (N. Nilsson)

Lecture Notes On Artificial Intelligence By Dr. Prashanta Kumar Patra

This book covers the following topics: AI Technique, Level of the Model,Problem Spaces, and Search: Defining the Problem as a State Space Search, Production Systems, Problem Characteristics, Production System Characteristics, Issues in the Design of Search Programs. Heuristic Search Techniques: Generate-andTest, Hill Climbing, Best-first Search, Problem Reduction, Constraint Satisfaction, Means-ends, Symbolic Reasoning Under Uncertainty, Game Playing, Learning: Rote Learning.

Author(s): Dr. Prashanta Kumar Patra

128 Pages

Introduction to Artificial Intelligence Lecture Notes

This book explains the following topics: Principles of knowledge-based search techniques, automatic deduction, knowledge representation using predicate logic, machine learning, probabilistic reasoning, Applications in tasks such as problem solving, data mining, game playing, natural language understanding, computer vision, speech recognition, and robotics.

Author(s): Chuck Dyer

NA Pages

Introduction to Artificial Intelligence

This note explains the following topics: Search, Game playing, Logic, Planning, Probabilistic reasoning, Decision theory, Markov decision processes, POMDPs, Game theory, Machine learning, Wrapping up.

Author(s): Vincent Conitzer

NA Pages

Artificial Intelligence Techniques Notes

This note provides a general introduction to artificial intelligence and its techniques. Topics covered includes: Biological Intelligence and Neural Networks, Building Intelligent Agents, Semantic Networks, Production Systems, Uninformed Search, Expert Systems, Machine Learning, Limitations and Misconceptions of AI.

Author(s): Dr John A. Bullinaria

NA Pages

Artificial Intelligence Lecture Notes Veer Surendra Sai University

This lecture note covers the following topics: Formalized symbolic logic, Probabilistic Reasoning Structured knowledge, graphs, frames and related structures, Matching Techniques, Knowledge organizations, Management, Natural Language processing, Pattern recognition, expert systems.

Author(s): Prof. Pradipta Kumar Das, Prof. D. Chandrasekhar Rao and Prof. Kishore Kumar Sahu

213 Pages

Artificial Intelligence Course Notes

This note explains artificial intelligence, including agent design, heuristic search, knowledge representation, planning, logic, natural language processing and machine learning.

Author(s): Ray Toal

NA Pages

Machine Learning, Neural and Statistical Classification (D. Michie, D. Spiegelhalter, C. Taylor)

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

NA Pages

Practical Artificial Intelligence Programming in Java

This book is for both professional programmers and home hobbyists who already know how to program in Java and who want to learn practical Artificial Intelligence (AI) programming and information processing techniques. Topics covered includes: Search, Reasoning, Semantic Web, Expert Systems, Genetic Algorithms, Neural Networks, Machine Learning with Weka, Statistical Natural Language Processing.

Author(s): Mark Watson

222 Pages

Introduction to Machine Learning

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Artificial Intelligence I (W. Jones)

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