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.

翻译：本文识别了42种用于构建通用人工智能（AGI）的认知架构，并提出了一组相互关联的功能模块，这些模块是具备接近AGI能力的智能体所应具备的。由于现有架构均未包含全部所需模块，本文提出了一种新的认知架构，适用于能力接近AGI的智能系统。作为该架构框架内的关键解决方案之一，本文提出了一种通用的知识表示方法，能够将自然语言文本、图像、音频和视频记录、图、算法、数据库、神经网络、知识图谱、本体、框架、实体-属性-关系模型、产生式系统、谓词演算模型、概念模型等多种非形式化、部分形式化及完全形式化的知识表示方法融合到单一知识库中。为组合和结构化不同知识片段，本文使用了基于带注释元图发展的档案图模型。所开发的认知架构组件包括机器意识、机器潜意识、与外部环境交互的模块、目标管理模块、情感控制系统、社交交互模块、反思模块、伦理模块与世界观模块、学习模块、监控模块、问题陈述与求解模块、自组织与元学习模块。