Competitive Learning: Fundamentals and Applications for Reinforcement Learning through Competition

In artificial neural networks, competitive learning is a type of unsupervised learning in which nodes fight for the right to respond to a subset of the input data. This type of learning is known as "competitive learning." Competitive learning is a form of learning that is similar to Hebbian learning. It operates by raising the level of specialization at each node in the network. It works quite well for discovering clusters hidden within data.

How You Will Benefit

(I) Insights, and validations about the following topics:

Chapter 1: Competitive Learning

Chapter 2: Self-organizing map

Chapter 3: Perceptron

Chapter 4: Unsupervised Learning

Chapter 5: Hebbian Theory

Chapter 6: Backpropagation

Chapter 7: Multilayer Perceptron

Chapter 8: Learning Rule

Chapter 9: Feature Learning

Chapter 10: Types of artificial neural networks

(II) Answering the public top questions about competitive learning.

(III) Real world examples for the usage of competitive learning in many fields.

Who This Book Is For

Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of competitive learning.

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The artificial intelligence book series provides comprehensive coverage in over 200 topics. Each ebook covers a specific Artificial Intelligence topic in depth, written by experts in the field. The series aims to give readers a thorough understanding of the concepts, techniques, history and applications of artificial intelligence. Topics covered include machine learning, deep learning, neural networks, computer vision, natural language processing, robotics, ethics and more. The ebooks are written for professionals, students, and anyone interested in learning about the latest developments in this rapidly advancing field.
The artificial intelligence book series provides an in-depth yet accessible exploration, from the fundamental concepts to the state-of-the-art research. With over 200 volumes, readers gain a thorough grounding in all aspects of Artificial Intelligence. The ebooks are designed to build knowledge systematically, with later volumes building on the foundations laid by earlier ones. This comprehensive series is an indispensable resource for anyone seeking to develop expertise in artificial intelligence.