Towards a Domain Specific Modeling Framework for General Collective Intelligence Platforms

Abstract

A General Collective Intelligence or GCI is a hypothetical platform able to self-organize individuals into potentially massive networks of cooperation on a self-sustaining basis, where those networks might radically increase the group’s general problem-solving ability and hence ability to solve any problem in general, which translates to a radical increase in the capacity of the group to achieve any of it’s collective goals. This potential to significantly increase collective outcomes has been confirmed through analysis of GCI based platform designs targeting social good, such as a proposed “Social Impact Marketplace”. In software, GCI is predicted to create the potential to enable social media platforms, blockchain platforms, or any other type of platform, to self-assemble at a speed, scale, and size of user base not currently possible, while also providing functionality that reliably solves problems that are currently not reliably solvable. In order to achieve this, GCI leverages the concept of “functional state spaces” to provide a semantic representation of the functionality in each domain of software behavior. This paper explores the concept of functional state spaces as a framework for domain specific modeling, as well as how such functional state spaces potentially provide a semantic representation of the functionality in each domain that is universal and therefore suitable for a General Collective Intelligence platform capable of targeting any given problem in any given domain.