AIJan 11, 2024

A Universal Knowledge Model and Cognitive Architecture for Prototyping AGI

arXiv:2401.06256v314 citationsh-index: 4Cogn Syst Res
Originality Synthesis-oriented
AI Analysis

This addresses the challenge of integrating varied knowledge types for AGI systems, but appears incremental as it builds on existing architectures without demonstrated results.

The paper identified 42 existing cognitive architectures for AGI and proposed a new architecture with a universal knowledge representation method that can combine diverse formats like texts, images, and neural networks, using archigraph models for structuring.

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 systems, predicate calculus models, conceptual models, and others. To combine and structure various fragments of knowledge, archigraph models are used, constructed as a development of annotated metagraphs. As components, the cognitive architecture being developed includes machine consciousness, machine subconsciousness, blocks of interaction with the external environment, a goal management block, an emotional control system, a block of social interaction, a block of reflection, an ethics block and a worldview block, a learning block, a monitoring block, blocks of statement and solving problems, self-organization and meta learning block.

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