A Universal Knowledge Model and Cognitive Architecture for Prototyping AGI
Artem Sukhobokov, Evgeny Belousov, Danila Gromozdov, Anna Zenger and, Ilya Popov

TL;DR
This paper proposes a comprehensive cognitive architecture for AGI, featuring a universal knowledge representation method and various functional blocks to emulate human-like intelligence.
Contribution
It introduces a new cognitive architecture with a universal knowledge model, integrating diverse knowledge representation methods in a unified framework for AGI development.
Findings
A universal knowledge representation method combining multiple formats.
Development of archigraph models for structuring knowledge fragments.
Design of a comprehensive cognitive architecture with multiple functional blocks.
Abstract
The article identified 42 cognitive architectures for creating general artificial intelligence (AGI) and proposed a set of interrelated functional blocks that an agent approaching AGI in its capabilities should possess. Since the required set of blocks is not found in any of the existing architectures, the article proposes a new cognitive architecture for intelligent systems approaching AGI in their capabilities. As one of the key solutions within the framework of the architecture, a universal method of knowledge representation is proposed, which allows combining various non-formalized, partially and fully formalized methods of knowledge representation in a single knowledge base, such as texts in natural languages, images, audio and video recordings, graphs, algorithms, databases, neural networks, knowledge graphs, ontologies, frames, essence-property-relation models, production…
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Taxonomy
TopicsEconomic and Technological Developments in Russia · Environmental Sustainability and Technology · Regional Economic Development and Innovation
MethodsSparse Evolutionary Training
