Initially visible models of subnetwork construction algorithms in AGTIntellegence networking
AGTIntelligence network (hereinafter – the Network) – a subnetwork on the Internet that connects people and gadgets with the AGTInw application installed in order to receive or provide work on the Network.
Simple program (simple procedure) – a parametric program which, with different parameters, can be loaded simultaneously many times with different parameters (the number of times required in the Subnetwork) on one Gadget and all this number is successfully and quickly executed by the Gadget.
AGTIsynapse – A connection between two Agents that has its own weight, and possibly its own simple program of operation. The Agent accepts (installs in the Application on his/her Gadget) the Synapse either automatically or manually (at the Owner’s will).
The weight (AGTIpower) of an Agent is a tensor function (of time and other parameters) available for each Agent, different at each moment, available to all Agents (possibly partially), and serving for clustering of the Network by targeting.
In order for the Agents creating the Subnetwork to be able to recruit the necessary Agents to each layer of their Subnetwork, it is reasonable to create a methodology for labeling Agents with Weights – tensor functions (of time and other parameters). Agent A corresponds to T(A).
A group of Agents (usually connected by a synapse-matrix) creating a Subnetwork P selects the target parameters of P, i.e., its practical functions, a participation payment C(T(A)) and a performance bonus PR(A), the participants of the layers are selected (by their acceptance) according to the parameter weights appropriate for each layer, thus clustering the Subnetwork.
Within and between the layers of the Subnetwork are created Synapses P(A,B) – tensors in the form of simple programs, possibly generated automatically by algorithm by the creators of the Subnetwork for each Synapse, P(A,B) are loaded into Gadgets A and B, and may be different, but guarantee fast interaction between A and B. The interaction in a given Subnetwork between A and B goes through a particular Synapse P(A,B).
P(A,B) may have some stochastic parameter p with some probability distribution of values (at a given time, or from an address in the Network, Subnetwork, etc.). Then the Subnet itself begins to behave probabilistically, like a living brain. Let us call such a subnetwork stochastic.
Thus, the methodology of building Subnetworks in AGTIntelligence network is described in general and in further articles we will specify already approximate algorithms that will launch the Network into useful work for people.