General Collective Intelligence as a System for Facilitating Parallel and Distributed Computing

Abstract

A General Collective Intelligence or GCI is a hypothetical platform able to self-organize individuals or intelligent agents working on behalf of those individuals, into potentially massive networks of cooperation on a self-sustaining basis, where those networks might exponentially increase the complexity and duration of reasoning the group is able to execute. When applied to the computing processes that might be executed by each individual, the algorithm represented by GCI creates the potential to take any computing process that has been abstracted into a logical model (a model in which each component of logic might be implemented in a separate functional component), and to automatically search for and apply patterns of solution by which it might be possible to increase outcomes. Such patterns might involve distributing processing across multiple instances of those functional components, and scaling processing by increasing the instances of those functional components in series and in parallel, as well as ensuring this effort has more value than cost to performance so it is possible to sustain the effort at doing so, until computing outcomes are scaled as necessary to achieve a given target, or until returns from scaling diminish to the point that further investment in scaling is unproductive. This paper explores how such processes of cooperation might include all forms of parallel and distributed activity, how that cooperative activity might be abstracted into a logical model, and how GCI might facilitate parallel and distributed computing through that model.

General Collective Intelligence as a Platform for Computational Social Systems

“…This suggests that through abstracting all collective reasoning processes so they can be represented as paths through this conceptual space, this conceptual space can in turn be used as the basis for domain specific modeling that can potentially be used to implement any logic modeled that way for any platform [7]. In addition, through abstracting all networks of cooperation so they can be represented as paths through this cooperation state space, this cooperation state space can in turn potentially be used for scaling the execution of any computing process through means such as parallel or distributed computing [8]. Through implementing social computing platforms in terms of these abstract models of logic and of cooperation, such platforms might be deployed within a GCI, which leverages these abstract models.…”

Increasing the Societal Impact of Science, Technology, Engineering, and Math with General Collective Intelligence

“…Similarly, it is hypothesized that scaling a collectively intelligent value chain can be represented as a path through a "cooperation space" [26], a functional state space with the capacity to represent all possible modes of cooperation through which social outcomes might be scaled. Assuming that the cooperation space can also be spanned by a set of basic operations, where these operations act on activities as their domain object, then cooperation might be defined to scale outcomes to any degree.…”