BOOKS - Learning Automata and Their Applications to Intelligent Systems
Learning Automata and Their Applications to Intelligent Systems - JunQi Zhang, MengChu Zhou 2024 PDF | EPUB Wiley-IEEE Press BOOKS
ECO~14 kg CO²

1 TON

Views
78562

Telegram
 
Learning Automata and Their Applications to Intelligent Systems
Author: JunQi Zhang, MengChu Zhou
Year: 2024
Pages: 275
Format: PDF | EPUB
File size: 21.6 MB
Language: ENG



Pay with Telegram STARS
Learning Automata and Their Applications to Intelligent Systems The book "Learning Automata and Their Applications to Intelligent Systems" is a comprehensive guide to understanding the concept of automata and their role in shaping the future of intelligent systems. The author, a renowned expert in the field, provides a thorough analysis of the current state of the art in automata research and its applications in various domains, including computer science, artificial intelligence, and machine learning. The book offers a unique perspective on the evolution of technology and its impact on human society, highlighting the importance of developing a personal paradigm for perceiving the technological process of developing modern knowledge. The book begins by introducing the fundamental concepts of automata, including finite automata, pushdown automata, and Turing machines. It then delves into the more advanced topics of linear bounded automata, non-deterministic automata, and probabilistic automata, providing readers with a solid foundation in the subject matter. The author also explores the various applications of automata in intelligent systems, such as speech recognition, natural language processing, and robotics. One of the key themes of the book is the need to study and understand the process of technology evolution. The author argues that this is crucial for the survival of humanity, as it allows us to anticipate and prepare for the challenges and opportunities that arise from technological advancements. By examining the historical development of automata and their applications, the book provides a framework for understanding the trajectory of technological progress and how it has shaped our world today. The author emphasizes the importance of developing a personal paradigm for perceiving the technological process of developing modern knowledge.
''

You may also be interested in:

Handbook of Research on Machine Learning Foundations and Applications
Fundamentals of Optimization Theory With Applications to Machine Learning
Deep Learning Techniques for Automation and Industrial Applications
Machine Learning Refined Foundations, Algorithms, and Applications
Emergence and Innovation in Digital Learning Foundations and Applications
Machine Learning Applications in Non-conventional Machining Processes
An Introduction to Approaches and Modern Applications With Ensemble Learning
Machine Learning and Data Science Fundamentals and Applications
Handbook on Federated Learning Advances, Applications and Opportunities
Machine Learning Applications: From Computer Vision to Robotics
Machine Learning Hybridization and Optimization for Intelligent Applications
Programming The Ultimate Guide on Learning Technology and applications
Machine Learning for Asset Management New Developments and Financial Applications
System Design Using the Internet of Things with Deep Learning Applications
Artificial Intelligence and Machine Learning Applications for Sustainable Development
Cybernetics, Human Cognition, and Machine Learning in Communicative Applications
System Design Using the Internet of Things with Deep Learning Applications
Learning Airtable: Building Database-Driven Applications with No-Code
Fundamentals of Supervised Machine Learning With Applications in Python, R, and Stata
Applications of Deep Machine Learning in Future Energy Systems
Python for Machine Learning From Fundamentals to Real-World Applications
Artificial Intelligence Using Federated Learning Fundamentals, Challenges, and Applications
Python for Machine Learning: From Fundamentals to Real-World Applications
Data Science and Machine Learning Applications in Subsurface Engineering
Python for Machine Learning From Fundamentals to Real-World Applications
Applications of Optimization and Machine Learning in Image Processing and IoT
Applications of Deep Machine Learning in Future Energy Systems
An Introduction to Optimization With Applications to Machine Learning, 5th Edition
Real-Time Cloud Computing and Machine Learning Applications
Multimodal Scene Understanding Algorithms, Applications and Deep Learning
Applications of Optimization and Machine Learning in Image Processing and IoT
Handbook of Deep Learning in Biomedical Engineering Techniques and Applications
Advanced Deep Learning Applications in Big Data Analytics
Artificial Intelligence Using Federated Learning Fundamentals, Challenges, and Applications
Deep Learning and Medical Applications (Mathematics in Industry Book 40)
Hands-On Matrix Algebra Using R Active and Motivated Learning with Applications
Cognitive Analytics and Reinforcement Learning Theories, Techniques and Applications
Machine Learning and Analytics in Healthcare Systems Principles and Applications
Hands On Machine Learning with Python Concepts and Applications for Beginners
Blockchain, Big Data and Machine Learning Trends and Applications