Machine Learning, Neural and Statistical Classification

Digital Notes on Artificial Intelligence by Sri Indu College of Engineering and Technology

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

140 Pages

Digital notes on Artificial Intelligence

This lecture note covers topics starting with an introduction to AI and progressing through various search strategies and A* search. The text delves into challenges such as searching with partial observations and constraint satisfaction problems, introducing techniques like Alpha Beta Pruning. It explores reasoning methods like forward and backward chaining, syntax and semantics of First-Order Logic, knowledge engineering, resolution, classical planning, and planning with state space search.it also handles with topics like acting in nondeterministic domains and multi-agent planning, Bayes Rule, Bayesian Networks and Dempster Shafer Theory.It includes learning decision trees and the role of knowledge in learning.

Author(s): Department of Information Technology , Malla Reddy College Of Engineering and Technology

143 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 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 by Professor Yun Peng

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.

Author(s): Professor Yun Peng

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 Lectures slides and readings

This note covers the following topics: Search, Backtracking Search, Game Tree Search, Reasoning Under Uncertainty, Planning, Decision Making under Uncertainty.

Author(s): Fahiem Bacchus

NA Pages

Building Expert Systems In Prolog (Amzi)

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

Author(s):

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