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 
Artificial Intelligence Foundations of Computational Agents
This book contains below topics, What is artificial intelligence, Agent architectures and search, Reasoning with constraints, Propositions and inference, Planning, Supervised machine learning, Neural networks and deep learning, Reasoning and planning under uncertainty, Multiagent systems, Reinforcement learning.
Author(s): David L. Poole and Alan K. Mackworth, University of British Columbia
904 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
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 FirstOrder Logic, knowledge engineering, resolution, classical planning, and planning with state space search.it also handles with topics like acting in nondeterministic domains and multiagent 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
