Cognitive Intelligence and the Brain: Synthesizing Human Brain Functions

Abstract

In order for a SELF to function autonomously, and have the abilities to learn, reason, infer, evolve, perform self-assessment and self-actuation, we propose a cognitive framework similar to the human brain. What we describe in this chapter is an Artificial Cognitive Neural Framework (ACNF) that provides the ability to organize information semantically into meaningful fuzzy concepts and information fragments that create cognitive hypotheses as part of a SELF’s topology [129], similar to human processing. This approach addresses the problems of autonomous information processing by accepting that the system must purposefully communicate concepts fuzzily within its processing system, often inconsistently, in order to adapt to a changing real-world, real-time environment. Additionally, we describe a processing framework that allows a SELF to deal with real-time information environments, including heterogeneous types of fuzzy, noisy, and obfuscated data from a variety of sources with the objective of improving actionable decisions using Recombinant kNowledge Assimilation (RNA) processing [70, 71] integrated within an ACNF to recombine and assimilate knowledge based upon human cognitive processes. The cognitive processes are formulated and embedded in a neural network of genetic algorithms and stochastic decision making with the goal of recombinantly minimizing ambiguity and maximizing clarity while simultaneously achieving a desired result [58, 95].