Introduction to Machine Learning (N. Nilsson)

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

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 and Games

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

359 Pages

Introduction to Artificial Intelligence by Cristina Conati

This note provides an introduction to the field of artificial intelligence. Major topics covered includes: reasoning and representation, search, constraint satisfaction problems, planning, logic, reasoning under uncertainty, and planning under uncertainty.

Author(s): Cristina Conati

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

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 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

Building Expert Systems In Prolog (Amzi)

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

Author(s):

Pages