The General Theory of General Intelligence: A Pragmatic Patternist Perspective
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Abstract (arXiv)
A multi-decade exploration into the theoretical foundations of artificial and natural general intelligence, which has been expressed in a series of books and papers and used to guide a series of practical and research-prototype software systems, is reviewed at a moderate level of detail. The review covers underlying philosophies (patternist philosophy of mind, foundational phenomenological and logical ontology), formalizations of the concept of intelligence, and a proposed high level architecture for AGI systems partly driven by these formalizations and philosophies. The implementation of specific cognitive processes such as logical reasoning, program learning, clustering and attention allocation in the context and language of this high level architecture is considered, as is the importance of a common (e.g. typed metagraph based) knowledge representation for enabling "cognitive synergy" between the various processes. The specifics of human-like cognitive architecture are presented as manifestations of these general principles, and key aspects of machine consciousness and machine ethics are also treated in this context. Lessons for practical implementation of advanced AGI in frameworks such as OpenCog Hyperon are briefly considered.
Key facts. Cited by 8 papers in the map (data through 13 Oct 2026). Builds on 18 of its 87 references that are in the map. First posted on arXiv 28 Mar 2021.
Builds on
18 of 87 references.
References · 18
- 2020Neurosymbolic AI: The 3rd Wavecited by 254
- 2017The Consciousness Priorcited by 106
- 2018An Introduction to Probabilistic Programmingcited by 63
- 2016The AGI Containment Problemcited by 36
- 2020First Neural Conjecturing Datasets and Experimentscited by 26
- 2017Toward a Formal Model of Cognitive Synergycited by 5
- 2015Open Ended Intelligence: The individuation of Intelligent Agentscited by 4
- 2020Folding and Unfolding on Metagraphscited by 4
- 2020Paraconsistent Foundations for Probabilistic Reasoning, Programming and Concept Formationcited by 4
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6 more
- 2019A theory of incremental compressioncited by 2
- 2020Guiding Symbolic Natural Language Grammar Induction via Transformer-Based Sequence Probabilitiescited by 2
- 2021Patterns of Cognition: Cognitive Algorithms as Galois Connections Fulfilled by Chronomorphisms On Probabilistically Typed Metagraphscited by 2
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- 2020Combinatorial Decision Dags: A Natural Computational Model for General Intelligencecited by 1
- 2020Maximal Algorithmic Caliber and Algorithmic Causal Network Inference: General Principles of Real-World General Intelligence?cited by 1
Built on by
Citing papers per year: 2023: 1; 2024: 0; 2025: 5; 2026: 2.
8 papers.
- 2023OpenCog Hyperon: A Framework for AGI at the Human Level and Beyondcited by 9
- 2025Agent Identity Evals: Measuring Agentic Identitycited by 5
- 2025Quantum AIXI: Universal Intelligence via Quantum Informationcited by 2
- 2025What the F*ck Is Artificial General Intelligence?cited by 0
- 2025Hamiltonian Formalism for Comparing Quantum and Classical Intelligencecited by 0
- 2025Computational Concept of the Psyche (in Russian)cited by 0
- 2026Creativity in AI as Emergence from Domain-Limited Generative Modelscited by 0
- 2026Computational Concept of the Psychecited by 0
- 2026Computational Concept of the Psyche16 Mar 2026
- 2026Creativity in AI as Emergence from Domain-Limited Generative Models13 Jan 2026
- 2025Computational Concept of the Psyche (in Russian)6 Sep 2025
- 2025Agent Identity Evals: Measuring Agentic Identity23 Jul 2025
- 2025Hamiltonian Formalism for Comparing Quantum and Classical Intelligence17 Jun 2025
- 2025Quantum AIXI: Universal Intelligence via Quantum Information27 May 2025
- 2025What the F*ck Is Artificial General Intelligence?31 Mar 2025
- 2023OpenCog Hyperon: A Framework for AGI at the Human Level and Beyond19 Sep 2023