ADA , On the road to dynamic cognition: How is Action Modeling equivalent to Biological stratification ?
It appears that the brain is a uniquely connected set of statistical processing units(SPU), functional memory storage modules that are connected via neurotransmitter mediated API like interfaces. A statistical processing unit is a processing module that emerges from connecting memory elements that have the ability to modulate output based on input and feedback up chain from output line or lines. The neurons and glial cells exhibit these properties.
In biology the action potential firing process encodes the varied information related from other contiguous neurons tasked with processing some bit of sensory information. neurotransmitters provide the API or application programming interface through which groups of neurons fire or process data in concert. Each functional module describes a set of neurons providing some processing function for a given sensory data set. The neo cortex of most mammals is separated into regions loosely devoted to processing data from the visual, auditory, somatosensory, gustatory, olfactory data sets for example. These regions emerge over time as mammalian individuals develop, as they experience new data the regions sample and process and interpret the data.
Most research in the artificial intelligence space indicates that many have started to get the importance of the statistical aspects of cognitive processing (Google, Boston Dynamics....) but no one understands how these disparate processing units combine to emerge a thinking machine .namely how you'd connect SPU's to emerge dynamic cognition.
The Action Delta Assessment algorithm of the Action Oriented Worflow paradigm I invented is a generalized algorithm for *emerging an SPU like function from any training data set by having ADA analyze the stratified data*, stratification is the process of fitting a data set to desired boundaries of computational importance, these are called "actions" in the paradigm and require an action modeling step.
Action modeling is done by describing a functional boundary of computational importance along a range of actions that are fixed in the system. These are then given contextual relevance to the desired functional boundary, in Action Oriented Workflow these boundaries are encapsulated by the concept of an "Entity". Entities are represented using a computer programming language (java). The next step involves identifying how a given Entity has it's unique actions (8) defined or modeled.
In biology "stratification" as I assert it, is equivalent to action modeling which is the act of taking sensory data and then processing it differently depending on which layers in the cortex are devoted to processing parts of the incoming signal (hierarchical decomposition and processing)...for example the stratification of processing in the visual field is functionally equivalent to the modeling of actions that must be performed for ADA to start doing its magic on a given data set.
So, ADA is an emulation of the raw cortical algorithm that when trained defines functional SPU's, but is not a generator of the unique self connection of SPU's which one must have to make a dynamic cognition (a "thinking" brain) . I assert that the medulla is an spu, the hypothalamus is an spu, the neocortex is a contiguous sheet of spu modules dedicated to specific sensory processing, the amygdala are spu's devoted to emotional processing....etc. ADA is a fractal algorithm...able to be composed in any direction along an incoming data set to model(biology:stratify) it to any desired processing resolution.
Some believe that the self connection of biological brains also generates from a fractal seed that may be related to the cortical algorithm and in fact derive from it...I am among them. I have already identified a state diagram that I believe can emerge a working connection between SPU's designed around ADA that could emerge dynamic cognition with sufficient training data. I plan on pursuing the construction of such a system in the next few years.
Food for thought: