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A Primer on Gibsonian Information
Across the scientific literature, information measurement in the nervous system is posed as a problem of information processing internal to the brain by constructs such as neuronal populations, sensory surprise, or cognitive models.
Layers, Folds, and Semi-Neuronal Information Processing
Using this observation as inspiration, we utilize a type of embodied agent that exhibits layered representational capacity: meta-brain models.
Meta-brain Models: biologically-inspired cognitive agents
We will propose combinations of layers composed using specialized types of models.
Connectionism, Complexity, and Living Systems: a comparison of Artificial and Biological Neural Networks
We then consider these principles in ways that might be implemented in the future development of ANNs.
Continual Developmental Neurosimulation Using Embodied Computational Agents
Using these agents to exemplify the embodied nature of computational autonomy, we move closer to modeling embodied experience and morphogenetic growth as components of cognitive developmental capacity.
Observer-dependent Collective Behavior For Biologically-inspired Processing Models
Observers consist of observers that exhibit environmental relativism, biorealism, and collective behavior.
Braitenberg Vehicles as Developmental Neurosimulation
As is standard among models of artificial and biological neural networks, an analogue of the fully mature brain is presented as a blank slate.
