Artificial intelligence
Principles of artificial intelligence
Principles of artificial intelligence
1994 Special Issue: A model of hippocampal function
Neural Networks - Special issue: models of neurodynamics and behavior
The handbook of brain theory and neural networks
A cerebellar model of timing and prediction in the control of reaching
Neural Computation
Cambrian intelligence: the early history of the new AI
Cambrian intelligence: the early history of the new AI
What are the computations of the cerebellum, the basal ganglia and the cerebral cortex?
Neural Networks - Special issue on organisation of computation in brain-like systems
Machine Learning
Evolutionary Robotics: The Biology,Intelligence,and Technology
Evolutionary Robotics: The Biology,Intelligence,and Technology
Computational Explorations in Cognitive Neuroscience: Understanding the Mind by Simulating the Brain
Computational Explorations in Cognitive Neuroscience: Understanding the Mind by Simulating the Brain
Gateway to Memory: An Introduction to Neural Network Models of the Hippocampus and Learning
Gateway to Memory: An Introduction to Neural Network Models of the Hippocampus and Learning
On Intelligence
Learning Semantic Combinatoriality from the Interaction between Linguistic and Behavioral Processes
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Human Problem Solving
Neural Networks: A Comprehensive Foundation (3rd Edition)
Neural Networks: A Comprehensive Foundation (3rd Edition)
Predictive models in the brain
Connection Science
Neural Pathways of Embodied Simulation
Anticipatory Behavior in Adaptive Learning Systems
A Neurocomputational Model of Anticipation and Sustained Inattentional Blindness in Hierarchies
Anticipatory Behavior in Adaptive Learning Systems
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
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While classic artificial intelligence systems still struggle to incorporate commonsense knowledge properly, situated and embodied artificial intelligence (SEAI) aims to build animats that acquire a common-sense understanding of the world via interactions between simulated brains, bodies and environments. Neuroscientists believe that much of this common sense involves predictive models for physical activities, but the transfer of sensorimotor skill knowledge to cognition is non-trivial, indicating that SEAI may meet a daunting challenge of its own. This paper considers the neurological bases for implicit procedural and explicit declarative common sense, and the possibilities for its transfer from the former to the latter. This helps assess the prospects for SEAI eventually to surpass GOFAI (good old-fashioned AI) in the quest for generally intelligent systems.