Artificial Intelligence by Seoul National University
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Artificial Intelligence by Seoul National University
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.
This note explains the following topics:
Problem Solving by Search , Knowledge and Reasoning, Planning Classical
Planning, Uncertain knowledge and Learning.
Author(s): Department of CSE, Sri
Indu College of Engineering and Technology
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.
This PDF covers the following topics related to
Artificial Intelligence and Games : AI Methods, Ways of Using AI
in Games, Playing Games, Generating Content, Modeling Players, Game AI Panorama,
Frontiers of Game AI Research.
Author(s): Georgios
N. Yannakakis, Julian Togelius
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.
This note explains the following topics: State Space
Search, Decision Trees, Evaluating Hypotheses, Evaluation of hypothesis, Neural
Networks, Computational Learning Theory, DMF Clustering, Data Mining, Text
Mining, Graph Mining, Text Mining.
This note is
designed as a broad rather than in-depth introduction to the principles of
artificial intelligence, its characteristics, major techniques, and important
sub-fields and applications.
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.