Cognitive architecture is a blueprint for building intelligent systems that replicate how humans think—integrating memory, perception, learning, reasoning, and decision-making into a unified framework.
This book is a comprehensive guide to designing such architectures from the ground up, combining insights from artificial intelligence, neuroscience, psychology, and systems engineering.
With 25 chapters covering everything from symbolic and subsymbolic models to robotics, language, ethics, and multi-agent systems, it equips you with the theory, structure, and practical tools needed to build cognitive systems that scale, adapt, and evolve.
💡 What You’ll Learn
The evolution of cognitive modeling—from symbolic AI to hybrid and biologically inspired systems
Core components of cognition: memory, learning, attention, planning, and reasoning
Symbolic, subsymbolic, and hybrid frameworks—and how to integrate them
Temporal cognition, sequence learning, and agent-level decision-making
Real-time robotics, multi-agent systems, human-computer interaction, and language
Security, ethics, cultural adaptation, and context-aware cognition
Comparative studies of major architectures: ACT-R, SOAR, CLARION, and beyond
Tools, simulators, and best practices for scalable, testable development
🎯
Who This Book Is ForAI Researchers & AGI Theorists seeking systems-level integration
Engineers & Developers building autonomous agents, HCI, or robotics
Graduate Students in AI, neuroscience, cognitive science, and computational psychology
Cognitive Modelers exploring the link between architecture and human intelligence
Whether you're building adaptive robotics, exploring AGI, or designing explainable systems, this is the foundation—built for those who engineer intelligence, not just simulate it.