Explorations in Artificial Intelligence and Machine Learning

Introduction to Artificial Intelligence by Thomas P Trappenberg

This note covers introduction and history, Search, Robotics and motion planning, Constraint satisfaction problem, Machine learning, Learning machines and the perceptron, Regression, classification and maximum likelihood, Support vector machines, Learning Theory, Generative models and Naïve Bayes, Unsupervised learning, Reinforcement learning, Probabilistic Reasoning, Bayesian networks and Markov models.

Author(s): Thomas P Trappenberg, Dalhousie University

208 Pages

Artificial Intelligence by Seoul National University

This book explains the following topics: History of AI, Machine Evolution, Evolutionary Computation, Components of EC, Genetic Algorithms, Genetic Programming, Uninformed Search, Search Space Graphs, Depth-First Search, Breadth-First Search, Iterative Deepening, Heuristic Search, The Propositional Calculus, Resolution in the Propositional Calculus, The Predicate Calculus, Resolution in the Predicate Calculus, Reasoning with Uncertain Information, Agent Architectures.

Author(s): Seoul National University

NA Pages

Introduction to Artificial Intelligence by Cristina Conati

This note provides an introduction to the field of artificial intelligence. Major topics covered includes: reasoning and representation, search, constraint satisfaction problems, planning, logic, reasoning under uncertainty, and planning under uncertainty.

Author(s): Cristina Conati

NA Pages

Artificial Intelligence by IIT Kharagpur

This lecture note covers the following topics: Introduction to Agent, Problem Solving using Search, State Space Search, Pegs and Disks problem, Uninformed Search , Single agent search, Informed Search Strategies, Two agent, Constraint satisfaction problems, Knowledge Representation and Logic, First Order Logic, Rule based Systems, Other representation formalisms, Planning, Reasoning with Uncertainty - Probabilistic reasoning, Reasoning with uncertainty-Fuzzy Reasoning.

Author(s): IIT Kharagpur

NA 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

Building Expert Systems In Prolog (Amzi)

Currently this section contains no detailed description for the page, will update this page soon.

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Introduction to Machine Learning (N. Nilsson)

This note covers the following topics: Preliminaries, Boolean Functions, Using Version Spaces for Learning, Statistical Learning, Decision Trees, Inductive Logic Programming , Computational Learning Theory, Unsupervised Learning, Temporal-Difference Learning, Delayed-Reinforcement Learning.

Author(s): Nils J. Nilsson

NA Pages

Artificial Intelligence II (David Marshall)

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.

Author(s): David Marshall

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

Artificial Intelligence I (W. Jones)

Currently this section contains no detailed description for the page, will update this page soon.

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