15 research outputs found
OpenCog Hyperon: A Framework for AGI at the Human Level and Beyond
An introduction to the OpenCog Hyperon framework for Artificiai General
Intelligence is presented. Hyperon is a new, mostly from-the-ground-up
rewrite/redesign of the OpenCog AGI framework, based on similar conceptual and
cognitive principles to the previous OpenCog version, but incorporating a
variety of new ideas at the mathematical, software architecture and
AI-algorithm level. This review lightly summarizes: 1) some of the history
behind OpenCog and Hyperon, 2) the core structures and processes underlying
Hyperon as a software system, 3) the integration of this software system with
the SingularityNET ecosystem's decentralized infrastructure, 4) the cognitive
model(s) being experimentally pursued within Hyperon on the hopeful path to
advanced AGI, 5) the prospects seen for advanced aspects like reflective
self-modification and self-improvement of the codebase, 6) the tentative
development roadmap and various challenges expected to be faced, 7) the
thinking of the Hyperon team regarding how to guide this sort of work in a
beneficial direction ... and gives links and references for readers who wish to
delve further into any of these aspects
A Universal Knowledge Model and Cognitive Architecture for Prototyping AGI
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