A theory of consciousness from a theoretical computer science perspective: Insights from the Conscious Turing Machine

Blum, Lenore; Blum, Manuel

doi:10.1073/pnas.2115934119

Cited by 35 publications

(34 citation statements)

References 65 publications

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“…For instance, IBM is exploring cognitive manufacturing by unifying millions of data points from systems to generate actionable insights across the whole value chain, from product design to operations and customer service [9] . Besides, Zheng et al presented a Self-X cognitive manufacturing network, which introduces a multi-agent reinforcement learning method based on industrial knowledge graphs and other related works [10] . Generally, researchers are investigating the use of cognitive technologies across a product's life cycle in various industries.…”

Section: Research Gaps In Big Green Data For Greentelligencementioning

confidence: 99%

“…By playing against itself, it learns the patterns and errors and becomes its own tutor. At a cognitive manufacturing network level, Zheng et al explored an industrial knowledge graph-based multi-agent reinforcement learning approach that utilizes high-level Self-X capabilities, such as self-configuration, -optimization, and -adjustment [10] . The study was supported by an illustrative example of a multi-robot reaching task to validate the proposed approach.…”

Section: Cognitive Intelligence-enabled Data Analytics For Green Manu...mentioning

confidence: 99%

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Enhancing big data for greentelligence across the production value chain

Agbozo¹,

Tao²,

Cao³

et al. 2022

Green Manuf Open

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The big data concept has been explosive, revealing, and transformative across manufacturing industries as it provides deeper insights into manufacturing operations for decision-making. However, big green data (BGA), a dedicated subset of big data, is not adequately structured for comprehensive sustainability analysis, particularly in smart factories. With our proposed green data balance (GDB), there will be accountability for each input and output composition in a production unit within the production value chain (PVC). Data will be exhaustively and accurately collected in each workshop to help uncover unknown issues in a production value chain while facilitating the development of sustainability metrics or index systems. Additionally, a structured big green data system will fuel “greentelligence”, using intelligent systems and technologies to speed up digitalization toward sustainable manufacturing by measuring, tracking, and minimizing adverse environmental impacts. Lastly, with the support of the cognitive intelligence data analytic system (CIDAS), real-time and near real-time comprehensive sustainability analytics can be performed, leading to Self-X metacognitive adjustments and corrective actions.

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Section: Research Gaps In Big Green Data For Greentelligencementioning

confidence: 99%

Section: Cognitive Intelligence-enabled Data Analytics For Green Manu...mentioning

confidence: 99%

Enhancing big data for greentelligence across the production value chain

Agbozo¹,

Tao²,

Cao³

et al. 2022

Green Manuf Open

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“…Although the self-model approach is sometimes viewed as counterculture or minority, it may not actually be in the minority among scientists. The field of study may be developing a conceptual convergence, since a large cohort of philosophers and scientists have made arguments that at least partly overlap it ( 1 – 19 ).…”

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confidence: 99%

A conceptual framework for consciousness

Graziano

2022

Proc. Natl. Acad. Sci. U.S.A.

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This article argues that consciousness has a logically sound, explanatory framework, different from typical accounts that suffer from hidden mysticism. The article has three main parts. The first describes background principles concerning information processing in the brain, from which one can deduce a general, rational framework for explaining consciousness. The second part describes a specific theory that embodies those background principles, the Attention Schema Theory. In the past several years, a growing body of experimental evidence—behavioral evidence, brain imaging evidence, and computational modeling—has addressed aspects of the theory. The final part discusses the evolution of consciousness. By emphasizing the specific role of consciousness in cognition and behavior, the present approach leads to a proposed account of how consciousness may have evolved over millions of years, from fish to humans. The goal of this article is to present a comprehensive, overarching framework in which we can understand scientifically what consciousness is and what key adaptive roles it plays in brain function.

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“…Computation time in particular plays a significant role in resolving the paradox of free will. We define a Conscious Turing Machine (CTM) [4] that goes through life making choices. During whatever time it evaluates alternatives, before committing to any one of them, it rightly "feels" it has free will about its choices.…”

mentioning

confidence: 99%

“…• The feeling of free will is the conscious thinking 4 -emphasis on conscious -that occurs during the time the CTM, faced with a choice, computes the consequences and utility of its possible actions, in order to choose whichever action best suits its goals. A conscious thought is the content broadcast from CTM's Short Term Memory (STM).…”

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confidence: 99%

A Theoretical Computer Science Perspective on Consciousness

Blum

2021

J. AI. Consci.

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The quest to understand consciousness, once the purview of philosophers and theologians, is now actively pursued by scientists of many stripes. This paper studies consciousness from the perspective of theoretical computer science. It formalizes the Global Workspace Theory (GWT) originated by the cognitive neuroscientist Bernard Baars and further developed by him, Stanislas Dehaene, and others. Our major contribution lies in the precise formal definition of a Conscious Turing Machine (CTM), also called a Conscious AI. We define the CTM in the spirit of Alan Turing’s simple yet powerful definition of a computer, the Turing Machine (TM). We are not looking for a complex model of the brain nor of cognition but for a simple model of (the admittedly complex concept of) consciousness. After formally defining CTM, we give a formal definition of consciousness in CTM. We later suggest why the CTM has the feeling of consciousness. The reasonableness of the definitions and explanations can be judged by how well they agree with commonly accepted intuitive concepts of human consciousness, the range of related concepts that the model explains easily and naturally, and the extent of its agreement with scientific evidence.

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A theory of consciousness from a theoretical computer science perspective: Insights from the Conscious Turing Machine

Cited by 35 publications

References 65 publications

Enhancing big data for greentelligence across the production value chain

Enhancing big data for greentelligence across the production value chain

A conceptual framework for consciousness

A Theoretical Computer Science Perspective on Consciousness

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