Defining Functional Models of Artificial Intelligence Solutions to Create a Library that an Artificial General Intelligence can use to Increase General Problem Solving Ability

Abstract

The AI industry continues to enjoy robust growth. With the growing number of AI algorithms, the question becomes how to leverage all these models intelligently in a way that reliably converges on AGI. One approach is to gather all these models ingo a single library that a system of artificial intelligence might use to increase it's general problem solving ability. This paper explores the requirements for building such a library, the requirements for that library to be searchable for AI algorithms that might have the capacity to significantly increase impact on any given problem, and the requirements for the use of that library to reliably converge on AGI. This paper also explores the importance to such an effort of defining a common set of semantic functional building blocks that AI models can be represented in terms of. In particular, how that functional decomposition might be used to organize large scale cooperation to create such an AI library, where that cooperation has not yet proved possible otherwise. And how such collaboration, as well as how such a library, might significantly increase the impact of each AI and AGI researcher’s work.

Human Intelligence and General Collective Intelligence as Phase Changes in Animal Intelligence

“…Being a functional model independent of implementation, this model has been used to define a model for Artificial General Intelligence or AGI [14]. HCFM combined with this model of AGI might potentially enable all current models of AI and AGI to be decoupled into a library of functional components that an AGI can use to reliably increase it's general problem solving ability, in a way that reliably converges on the functionality required for human-like general problem solving ability [15]. HCMF has also been used to define a model for General Collective Intelligence or GCI [16], [17] a system that combines groups into a single entity with the potential capacity for general problem solving ability that is vastly greater than that of any individual in the group.…”

Does Creating an Artificial General Intelligence Require General Collective Intelligence in Order to be Reliably Achievable?

“…If the total number of reasoning processes required in human cognition to connect N concepts in human-like reasoning is at minimum on the order or N 3 , then defining a human-like conceptual space of 20 K concepts requires on the order of 6*10 12 reasoning processes, or some lower number of reasoning processes representing reasoning generalizations capable of navigating between generalizations of those concepts. Assume that each concept generalization on average contains N concepts and N reasoning processes linking those concepts to the concept generalization.…”

“…Representing the cognitive processes (reasoning or understanding processes) of an Artificial General Intelligence as being AI solutions that solve specific problems [3], then based on the same functional model, achieving human-like general problem-solving ability in an Artificial General Intelligence requires the AGI to have the ability to use some combination of available AI solutions, or to create new AI solutions, to solve any given problem within human capacity to solve, where that problem is defined in any given context within human capacity to understand.…”

Defining Functional Models of Collective Intelligence Solutions to Create a Library a General Collective Intelligence can use to Increase General Problem Solving Ability

“…As described in the case of cognitive functions for an individual system of cognition such as an AGI [14], reasoning (cognitive functions) representing the functions of a given AI solution, may be modeled and those models combined into a library that an AGI might use to increase its general problem solving ability. The basic functional modeling approach is to:…”