Artificial Intelligence Course Notes

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

Lecture note on Artificial Intelligence

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

173 Pages

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

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

Lecture Notes On Artificial Intelligence By Dr. Prashanta Kumar Patra

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.

Author(s): Dr. Prashanta Kumar Patra

128 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 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.

Author(s):

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