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

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 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 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

Techniques in Artificial Intelligence

This note provides an introduction to artificial intelligence. Topics covered include: representation and inference in first-order logic, modern deterministic and decision-theoretic planning techniques, basic supervised learning methods, and Bayesian network inference and learning.

Author(s): Prof. Tomas Lozano-Perez and Prof. Leslie Kaelbling

NA Pages

Artificial Intelligence Lecture Notes

This course note covers major topics of AI, including Search, Logic and Knowledge Representation, and Natural Language Processing, with brief coverage of the Brain and Machine Vision.

Author(s): Gordon S. Novak Jr

NA Pages

Introduction to Machine Learning (N. Nilsson)

This note covers the following topics: Preliminaries, Boolean Functions, Using Version Spaces for Learning, Statistical Learning, Decision Trees, Inductive Logic Programming , Computational Learning Theory, Unsupervised Learning, Temporal-Difference Learning, Delayed-Reinforcement Learning.

Author(s): Nils J. Nilsson

NA Pages

Machine Learning, Neural and Statistical Classification

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Building Expert Systems In Prolog

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