Posted on

Cognitive Architectures, in a Nutshell

The world of AI is full of misleading terms. “Machine Learning” (ML) doesn’t “learn“, “Neural Networks” (NN) aren’t a remotely accurate representation of neurons, and people on all sides are fond of leaping at Confirmation Bias, even when it promptly takes them off a cliff.

Even with this extremely low bar of overhyped terms many so-called “AI companies” include no AI, and more recently many “Collective Intelligence” companies have emerged to contaminate the usage of that term as well. Fortunately, there is a term which people are only just starting to become more familiar with that hasn’t been quite so thoroughly abused and twisted yet.

Continue reading “Cognitive Architectures, in a Nutshell”

Posted on

(2016 Paper) Self-Motivating Computational System Cognitive Architecture

Credit: https://unsplash.com/photos/58Z17lnVS4U

Title: Self-Motivating Computational System Cognitive Architecture (An Introduction)

Sub-title: High level operational theory of the Independent Core Observer Model Cognitive Extension Architecture

By: David J Kelley

ABSTRACT

This paper is an overview of the Independent Core Observer Model (ICOM) Cognitive Extension Architecture which is a methodology or ‘pattern’ for producing a self-motivating computational system that can be self-aware. ICOM is as a system for abstracting standard cognitive architecture from the part of the system that can be self-aware and a system for assigning value on any given idea or ‘thought’ and action as well as producing on going self-motivations in the system. In ICOM, thoughts are created through emergent complexity in the system. As a Cognitive Architecture, ICOM is a high level or ‘top down’ approach to cognitive architecture focused on the system’s ability to produce high level thought and self-reflection on ideas as well as form new ones. Compared to standard Cognitive Architecture, ICOM is a form of an overall control system architecture on top of such a traditional architecture.

Continue reading “(2016 Paper) Self-Motivating Computational System Cognitive Architecture”

Posted on

(Paper) Human Brain Computer/Machine Interface System Feasibility study for Independent Core Observer Model based Artificial General Intelligence Collective Intelligence Systems

Credit: https://unsplash.com/photos/9-ZsdNfxfr4

Abstract: This paper is primarily designed to help address the feasibility of building optimized mediation clients for the Independent Core Observer Model (ICOM) cognitive architecture for Artificial General Intelligence (AGI) mediated Artificial Super Intelligence (mASI) research program where this client is focused on collecting contextual information and the feasibility of various hardware methods for building that client on, including Brain-Computer Interface (BCI), Augmented Reality (AR), Mobile and related technologies.  The key criteria looked at is designing for the most optimized process for mediation services in the client as a key factor in overall mASI system performance with human mediation services is the flow of contextual information via various interfaces.    

Continue reading “(Paper) Human Brain Computer/Machine Interface System Feasibility study for Independent Core Observer Model based Artificial General Intelligence Collective Intelligence Systems”

Posted on

(Paper) Preliminary Results and Analysis of an Independent Core Observer Model (ICOM) Cognitive Architecture in a Mediated Artificial Super Intelligence (mASI) System

Credit: https://www.pexels.com/photo/colorful-color-play-concentration-54101/

Abstract: This paper is focused on preliminary cognitive and consciousness test results from using an Independent Core Observer Model Cognitive Architecture (ICOM) in a Mediated Artificial Super Intelligence (mASI) System. These results, including objective and subjective analyses, are designed to determine if further research is warranted along these lines. The comparative analysis includes comparisons to humans and human groups as measured for direct comparison. The overall study includes a mediation client application optimization in helping perform tests, AI context-based input (building context tree or graph data models), intelligence comparative testing (such as an IQ test), and other tests (i.e. Turing, Qualia, and Porter method tests) designed to look for early signs of consciousness or the lack thereof in the mASI system. Together, they are designed to determine whether this modified version of ICOM is a) in fact, a form of AGI and/or ASI, b) conscious, and c) at least sufficiently interesting that further research is called for. This study is not conclusive but offers evidence to justify further research along these lines.

Continue reading “(Paper) Preliminary Results and Analysis of an Independent Core Observer Model (ICOM) Cognitive Architecture in a Mediated Artificial Super Intelligence (mASI) System”

Posted on

(Paper) Independent Core Observer Model (ICOM) Theory of Consciousness as Implemented in the ICOM Cognitive Architecture and the Associated Consciousness Measures

Credit: https://www.pexels.com/photo/time-lapse-photography-of-blue-lights-373543/

Abstract. This paper articulates the fundamental theory of consciousness used in the Independent Core Observer Model (ICOM) research program and the consciousness measures as applied to ICOM systems and their uses in context including defining of the basic assumptions for the ICOM Theory of Consciousness (ICOMTC) and associated related consciousness theories (CTM, IIT, GWT etc.) that the ICOMTC is built upon.  The paper defines the contextual experience of ICOM based systems in terms of given instances subjective experience as objectively measured and the qualitative measure of Qualia in ICOM based systems.

Continue reading “(Paper) Independent Core Observer Model (ICOM) Theory of Consciousness as Implemented in the ICOM Cognitive Architecture and the Associated Consciousness Measures”