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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 
Explorations in Artificial Intelligence and Machine Learning
This PDF covers the following topics related to Artificial Intelligence and Machine Learning : Introduction to Machine Learning,The Bayesian Approach to Machine Learning, A Revealing Introduction to Hidden Markov Models, Introduction to Reinforcement Learning, Deep Learning for Feature Representation, Neural Networks and Deep Learning, AI-Completeness: The Problem Domain of Super-intelligent Machines.
Author(s): Prof. Roberto V. Zicari
178 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
Artificial Intelligence by Prof. Pallab Dasgupta and Prof. Partha Pratim Chakrabarti
This note covers the following topics: Problem Solving by Search, Informed State Space Search, Propositional Logic, Informed State Space Search, AND/OR Graphs and Game Trees, Method of Resolution Refutation, GraphPLAN and SATPlan, Reasoning under Uncertainty, Learning Decision Trees, Convolutional and Recurrent Neural Networks.
Author(s): Prof. Pallab Dasgupta and Prof. Partha Pratim Chakrabarti
NA Pages
Artificial Intelligence Lecture Materials
This note will provide an introduction to the field of Artificial Intelligence. It will cover a number of AI ideas and techniques, as well as give you a brief introduction to symbolic computing.
Author(s): Diane Cook
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
Artificial Intelligence Lecture Notes MIT
This course note introduces representations, techniques, and architectures used to build applied systems and to account for intelligence from a computational point of view.
Author(s): Prof. Leslie Kaelbling and Prof. Tomas Lozano-Perez
NA Pages
Artificial Intelligence Lecture Notes
This course note covers major topics of AI, including Search, Logic and Knowledge Representation, and Natural Language Processing, with brief coverage of the Brain and Machine Vision.
Author(s): Gordon S. Novak Jr
NA Pages
Building Expert Systems In Prolog (Amzi)
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Building Expert Systems In Prolog
Currently this section contains no detailed description for the page, will update this page soon.
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