Artificial Intelligence Techniques and Optimization

G. Kumaresan

ISBN 10: 9355287925 / ISBN 13: 9789355287922

Editore: MJP Publisher, 2024

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nach der Bestellung gedruckt Neuware - Printed after ordering - The document you uploaded appears to be a textbook on Artificial Intelligence techniques and optimization processes, written by Dr. G. Kumaresan. The book covers various topics in AI, including state-space search, adversarial search, propositional and predicate logic, and optimization algorithms. It also delves into different learning methods such as supervised, unsupervised, and reinforcement learning, as well as neural networks and ensemble learning techniques. If you are asking for a specific description related to a particular section of the document, please clarify which topic or area you want a detailed description of, and I can assist you accordingly. If you are referring to the overall description of the book, I can summarize the contents as follows:Focus: The book is aimed at exploring artificial intelligence techniques and their optimization processes. It provides insights into how AI systems solve complex problems, enhance decision-making, and optimize performance in various applications.Target Audience: This is intended for beginners and those looking to understand the fundamental principles of AI. It also seems suitable for advanced readers looking for practical implementations of AI algorithms. Content Breakdown: The book explains search algorithms, learning methods (including neural networks and reinforcement learning), and AI's role in solving real-world problems like optimization. Let me know how you'd like to proceed or if you have a specific section in mind!

Codice articolo 9789355287922

Dati bibliografici

• Titolo: Artificial Intelligence Techniques and Optimization
• Editore: MJP Publisher
• Data di pubblicazione: 2024
• Lingua: Inglese
• ISBN 10: 9355287925
• ISBN 13: 9789355287922
• Rilegatura: Taschenbuch
• Condizione: Neu
• Dimensioni: 216 L x 140 A x 20 P (millimetri) 216 millimetri di larghezza per 140 millimetri di altezza per 20 millimetri di profondità
• Peso: 480 grammi

Descrizione articolo

Riassunto

Artificial Intelligence: Techniques and Optimization by Dr. G. Kumaresan is an essential resource for students, professionals, and AI enthusiasts looking to understand and master the complex concepts of artificial intelligence. This well-structured textbook covers a wide range of AI topics, focusing on optimization techniques that enhance the efficiency and effectiveness of AI systems. Key features of the book include:

• Comprehensive Introduction to AI: The book starts by providing a solid foundation in the basics of artificial intelligence, discussing its history, development, and potential applications in today’s world.

• Diverse AI Environments: It explains the various types of AI environments, such as fully observable and partially observable environments, and provides insights into how intelligent agents operate in each type.

• Search Algorithms: A detailed explanation of uninformed and informed search algorithms, including Breadth-First Search (BFS), Depth-First Search (DFS), A* Search, and more. These algorithms are vital for solving complex problems in AI.

• Adversarial Search: The book explores adversarial search methods, including game theory approaches like Minimax and Alpha-Beta Pruning, which are essential for AI applications in competitive environments such as gaming.

• Learning Techniques: It covers different learning methods, including supervised, unsupervised, semi-supervised, and reinforcement learning, along with ensemble learning techniques for building more accurate and reliable AI models.

• Neural Networks: A section is dedicated to neural networks and how they are modeled after the human brain to process and learn from data.

• Optimization Algorithms: The book delves into optimization methods, discussing how AI systems can be fine-tuned using algorithms like Genetic Algorithms, Swarm Intelligence, and Evolutionary Computation.

• Practical Applications: Each chapter includes real-world examples and applications, making it easy for readers to understand how these AI techniques are applied in various industries.

This textbook is an ideal companion for anyone interested in learning AI from the ground up and those who wish to explore more advanced topics like optimization and machine learning algorithms.