AGI Laboratory Developed New Consciousness Model for Artificial General Intelligence

AGI Laboratory Developed New Consciousness Model for Artificial General Intelligence

Jan 30, 2018 press by DavidJKelley

The research theory is in a white paper which is titled: “The Independent Core Observer Model Computational Theory of Consciousness and the Mathematical model for Subjective Experience”

Abstract: This paper outlines the Independent Core Observer Model (ICOM) Theory of Consciousness defined as a computational model of consciousness that is objectively measurable and an abstraction produced by a mathematical model where the subjective experience of the system is only subjective from the point of view of the abstracted logical core or conscious part of the system where it is modeled in the core of the system objectively. Given the lack of agreed upon definitions around consciousness theory, this paper sets precise definitions designed to act as a foundation or baseline for additional theoretical and real-world research in ICOM based AGI (Artificial General Intelligence) systems that can have qualia measured objectively.

Intro: 

The Independent Core Observer Model Theory of Consciousness is partially built on the Computational Theory of Mind (Rescorla 2016) where one of the core issues with research into artificial general intelligence (AGI) is the absence of objective measurements and data as they are ambiguous given the lack of agreed-upon objective measures of consciousness (Seth 2007). To continue serious work in the field we need to be able to measure consciousness in a consistent way that is not presupposing different theories of the nature of consciousness (Dienes and Seth 2012) and further not dependent on various ways of measuring biological systems (Dienes and Seth 2010) but focused on the elements of a conscious mind in the abstract. With the more nebulous Computational Theory of Mind, research into the human brain does show some underlying evidence of a computational model (Siong, Brass, Heinze and Hayness 2008) in humans. Given the artificial general intelligence (AGI) research related to the ICOM cognitive architecture has been built upon these additional assumptions and definitions put forth here to critical to objectively measure that research. The purpose of this paper is to define a more detailed basis of measurement of qualia through the ICOM Theory of Consciousness and help objectively measure consciousness in terms of qualia. The ICOM Theory of Consciousness is one that can be objectively measured including the objective measurement of qualia if our assumptions are accurate allowing research to move forward and further refine our methods.

Conclusion:

The Independent Core Observer Model Theory of Consciousness (ICOMTC) addresses key issues with being able to measure physical and objective details well as the subjective experience of the system (known as qualia) including mapping complex emotional structures, as seen in previously published research related to ICOM cognitive architecture (Kelley 2016). It is in our ability to measure, that we have the ability to test additional theories and make changes to the system as it currently operates. Slowly we increasingly see a system that can make decisions that are illogical and emotionally charged yet objectively measurable (Chalmers 1995) and it is in this space that true artificial general intelligence that will work ‘logically’ similar to the human mind that we hope to see success. ICOMTC allows us to model objectively subjective experience in an operating software system that is or can be made self-aware and act as the foundation for creating ASI.

If you want to read the rest in between you need to wait for the 2018 International Conference on Information Science and Technology Conference when it will be released (see IST2018) on April 20th.  You can get a preview in a presentation at the Science of Consciousness Conference 2018 on April 2-7th in Tucson, Arizona where we have been invited to do a Poster Session on the topic where we will make available outstanding research that was previously unpublished.

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