Mammalian Cognitive Architecture for Robotics: Modeling Advanced Neural Systems for Sophisticated Autonomous Agents

Thomas, Gareth

ISBN 13: 9798266926073

Editore: Independently published, 2025

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• Titolo: Mammalian Cognitive Architecture for Robotics: Modeling Advanced Neural Systems for Sophisticated Autonomous Agents
• Editore: Independently published
• Data di pubblicazione: 2025
• Lingua: Inglese
• ISBN 13: 9798266926073
• Rilegatura: Brossura
• Condizione: New

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💡 Note: This book is written for serious engineers and researchers who want rigorous, high-level technical insight. It’s dense, detailed, and assumes prior familiarity with advanced concepts.
If you value precision, depth, and professional-grade explanations—you’ll find this book indispensable.

What if the secret to building truly intelligent robots has been right in front of us all along—hidden in the brains of mammals?

For decades, robotics has stumbled on the same problem: machines that can perform tasks, but fail when the world shifts, bends, or surprises them. The solution isn’t another narrow algorithm. It’s a complete rethinking of cognition—modeled on the very systems that evolution has refined for survival, learning, and adaptability.

Mammalian Cognitive Architecture for Robotics rips open the blueprint of mammalian intelligence and shows how to harness it for advanced autonomous agents. From the layered neocortex to the dynamic rewiring of plastic synapses, from attention and emotion to decision-making and social coordination, this book lays out the raw materials for a new era of robotics.

Inside, you’ll discover:

• How mammalian brains balance speed, accuracy, and flexibility—and how to engineer the same trade-offs into robotic systems.

• Why cognition is not just data processing but a seamless integration of memory, attention, perception, and motivation.

• How neuroplasticity and lifelong learning can be transformed into algorithms that evolve with experience.

• The principles behind mammalian vision, haptics, olfaction, and navigation—and how to implement them in sensors and AI models.

• The path toward surpassing mammalian limits by combining biological inspiration with symbolic reasoning, meta-cognition, and scalable architectures.

This is not theory for theory’s sake. It’s a field guide for engineers, AI researchers, and roboticists who want to build machines that adapt, decide, and act in the real world with the same resilience and sophistication as living creatures.

If you are serious about robotics—if you want to break through the brittle limits of today’s automation—then this is the book that shows you where the future begins.