Artificial Cognition Architectures
Springer Science & Business Media, Aug 13, 2013 - Technology & Engineering - 263 pages
The goal of this book is to establish the foundation, principles, theory, and concepts that are the backbone of real, autonomous Artificial Intelligence. Presented here are some basic human intelligence concepts framed for Artificial Intelligence systems. These include concepts like Metacognition and Metamemory, along with architectural constructs for Artificial Intelligence versions of human brain functions like the prefrontal cortex. Also presented are possible hardware and software architectures that lend themselves to learning, reasoning, and self-evolution
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Artificial Cognitive System Architectures
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Abductive Reasoning ability ACNF action adapt algorithms allows Artificial Cognition Architectures Artificial Consciousness Artificial Intelligence Artificial Prefrontal Cortex Assessment Autonomic Nervous System autonomous behavior capabilities Cognition Architectures cognitive framework cognitive processing Cognitrons components computational concepts Conceptual Ontology constraints context create Crowder DART Data Steward decision described develop domain emotional memories environment evolve external genetic goals high-level human reasoning hypotheses illustrates Implicit Memory Informaon information fragments infrastructure input integrated interaction internal ISAAC cognitive Knowledge Relativity Knowledge Relativity Threads Locus of Control Long-Term Memory Lower Brain Function Mediator Cognitron memory systems Metacognitive Metacognitive and Metamemory Metamemory Nervous System Neural Fiber Network neural network nodes objects Occam Abduction Occam Learning overall PENLPE perceptrons possibilistic problem Procedural Memory processing system real-time robot self-evolving SELF’s cognitive semantic sensory Service situations software agents solutions Springer Science+Business Media stored structure synthetic theory tion topical map types utilized