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
904Pages
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
140Pages
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
173Pages
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 Na and iuml,ve Bayes, Unsupervised learning, Reinforcement learning, Probabilistic Reasoning, Bayesian networks and Markov models.
Author(s): Thomas P Trappenberg, Dalhousie University
208Pages
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
143Pages
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, AICompleteness, The Problem Domain of Superintelligent Machines.
Author(s): Prof. Roberto V. Zicari
178Pages
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
359Pages
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, GenerateandTest, Hill Climbing, Bestfirst Search, Problem Reduction, Constraint Satisfaction, Meansends, Symbolic Reasoning Under Uncertainty, Game Playing, Learning, Rote Learning.
Author(s): Dr. Prashanta Kumar Patra
128Pages
Hamed Farhadis online book Machine Learning, Advanced Techniques and Emerging Applications and quot, explores the latest developments in machine learning and their various applications It explores recent developments in machine learning techniques, and focuses on how these innovations are changing various industries. The book emphasizes the integration of these techniques into smart cities, where machine learning enhances urban management and infrastructure through datadriven solutions This includes the role of automation in, including how advanced algorithms simplify manufacturing, improve efficiency and enable customization In terms of providing details, the text explores the role of machine learning in emerging industries, and shows how startups and innovations can use these technologies to gain competitive advantage and drive innovation. Overall, the book provides a comprehensive overview of how advanced machine learning techniques are being used in various.
Author(s): Hamed Farhadi
NAPages
