Cybernetics, Cognition and Machine Learning Applications
Written by Vinit Kumar Gunjan,Amit Kumar,P. N. Suganthan,Jan Haase
237 pages, about 5 hours of reading
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Themes, characters and key ideas in Cybernetics, Cognition and Machine Learning Applications, written by Chaptra AI.
- about 25 hours
- advanced
- Informative
- Academic
- Technical
This book compiles a selection of original, peer-reviewed research articles presented at the 3rd International Conference on Cybernetics, Cognition and Machine Learning Applications (ICCCMLA 2021). Held in Goa, India, in August 2021, the collection serves as a timely snapshot of contemporary advancements across critical technological and scientific domains. It comprehensively covers current research trends and developments in data science, artificial intelligence, neural networks, cognitive science, machine learning applications, cyber-physical systems, and cybernetics. The volume offers insights into the cutting-edge methodologies and findings shaping these interconnected fields, providing a valuable resource for academics, researchers, and industry professionals.
“"Exploring the intricate nexus of cybernetics and cognition to advance machine intelligence."”
Key themes
- Machine Learning Applications and Algorithms
- This is a core theme, encompassing the design, development, and application of algorithms that allow systems to learn from data without explicit programming. It covers various machine learning paradigms (supervised, unsupervised, reinforcement learning) and their practical implementations across diverse problem domains, including optimization, pattern recognition, and prediction.
- Cybernetics and Control Systems
- This theme explores the principles of control and communication in complex systems, both artificial and natural. Papers under this umbrella likely delve into feedback loops, self-regulation, adaptive systems, and the design of intelligent agents that interact with their environment. It forms a foundational layer for understanding how autonomous systems function and adapt.
- Cognitive Science and Artificial Intelligence
- This theme investigates the intersection of human cognition and artificial intelligence. It includes research on how human-like intelligence, learning, perception, and decision-making can be modeled, simulated, or replicated in machines. It encompasses areas like computational neuroscience, knowledge representation, and AI systems inspired by biological brains.
Worth discussing
What are the most significant emerging trends identified across the diverse papers in this collection?
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