Artificial Intelligence by Seoul National University
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 note describes the following topics: introduction to AI and production systems,
Representation of Knowledge, Knowledge Representation using predicate logic,
Knowledge Inference, Planning and Machine Learning, Expert Systems and Meta
Knowledge.
Author(s): St Anne College of Engineering and
Technology
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 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.
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 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
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