Abstract: A computer-implemented method comprising a mathematical formulation of the social energy flow of Karma and a machine learning framework combining mathematical graph computation, which form a global sentiment aggregator for the measurement of social energy flows and which is formulated as a data processing, filtering and sampling framework which fuses structural, interpretable graph machine learning with graph neural networks and introduces a Graph Attention Mechanism (GAM) whereby machine learning guides an interpretable graph computation substrate in order to generate general, structured predictions for the past, present and future. This enables the framework to handle large data sets on a global scale in the graph neural network while affording interpretability within the less scalable graph computational substrate which in turn optimizes the use of memory, computer storage and processing power over traditional designs, thereby making global-scale computations on commodity hardware feasible.

Abstract: A computer-implemented method for automating manufacturing supply chain planning, comprising: (a) providing a computer processor for processing data; (b) providing at least one input device; (c) providing at least one output device; (d) providing a computer readable storage device; (e) providing a first ontology for defining a product in terms of the method of manufacture of said product or for defining a plurality of products in terms of the method of manufacture of said products; (f) providing a second ontology for defining the capabilities of a plurality of manufacturing facilities; and g) providing a knowledge representation and reasoning system executed on said computer processor.

Abstract: A computer-implemented method for operating a robotic manufacturing network, comprising: (a) providing a communications network; (b) providing a plurality of computer processor nodes for processing data wherein said computer processor nodes are participants on said communication network; (c) providing a plurality of manufacturing facilities; (d) providing a plurality of transport agents connecting said manufacturing facilities; (e) providing a plurality of actors selected from the group consisting of said manufacturing facilities and said transport agents wherein said actors are participants in said robotic manufacturing network and communicate on said communications network; (f) providing a robotic capability model as manufacturing supply chain planning service whereby autonomous manufacturing supply chain functionality is created that transforms product specifications into optimized manufacturing production plans thereby permitting products to be made by a population of networked manufacturing agents.

Abstract: A computer-implemented method for operating a robotic manufacturing network, comprising: (a) providing a communications network; (b) providing a plurality of computer processor nodes for processing data wherein said computer processor nodes are participants on said communication network; (c) providing a plurality of manufacturing facilities; (d) providing a plurality of transport agents connecting said manufacturing facilities; (e) providing a plurality of actors selected from the group consisting of said manufacturing facilities and said transport agents wherein said actors are participants in said robotic manufacturing network and communicate on said communications network; (f) providing a robotic capability model as manufacturing supply chain planning service whereby autonomous manufacturing supply chain functionality is created that transforms product specifications into optimized manufacturing production plans thereby permitting products to be made by a population of networked manufacturing agents.

Abstract: A computer-implemented method for automating manufacturing supply chain planning, comprising: (a) providing a computer processor for processing data; (b) providing at least one input device; (c) providing at least one output device; (d) providing a computer readable storage device; (e) providing a first ontology for defining a product in terms of the method of manufacture of said product or for defining a plurality of products in terms of the method of manufacture of said products; (f) providing a second ontology for defining the capabilities of a plurality of manufacturing facilities; and g) providing a knowledge representation and reasoning system executed on said computer processor.