A Universal Knowledge Model and Cognitive Architecture for Prototyping
AGI
- URL: http://arxiv.org/abs/2401.06256v3
- Date: Sat, 27 Jan 2024 19:13:03 GMT
- Title: A Universal Knowledge Model and Cognitive Architecture for Prototyping
AGI
- Authors: Artem Sukhobokov, Evgeny Belousov, Danila Gromozdov, Anna Zenger and
Ilya Popov
- Abstract summary: Article identifies 42 cognitive architectures for creating general artificial intelligence (AGI)
It 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.
- Score: 0.0
- License: http://creativecommons.org/licenses/by-nc-nd/4.0/
- 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 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.
Related papers
- Categorical semiotics: Foundations for Knowledge Integration [0.0]
We tackle the challenging task of developing a comprehensive framework for defining and analyzing deep learning architectures.
Our methodology employs graphical structures that resemble Ehresmann's sketches, interpreted within a universe of fuzzy sets.
This approach offers a unified theory that elegantly encompasses both deterministic and non-deterministic neural network designs.
arXiv Detail & Related papers (2024-04-01T23:19:01Z) - Foundational Models Defining a New Era in Vision: A Survey and Outlook [151.49434496615427]
Vision systems to see and reason about the compositional nature of visual scenes are fundamental to understanding our world.
The models learned to bridge the gap between such modalities coupled with large-scale training data facilitate contextual reasoning, generalization, and prompt capabilities at test time.
The output of such models can be modified through human-provided prompts without retraining, e.g., segmenting a particular object by providing a bounding box, having interactive dialogues by asking questions about an image or video scene or manipulating the robot's behavior through language instructions.
arXiv Detail & Related papers (2023-07-25T17:59:18Z) - A Compositional Approach to Creating Architecture Frameworks with an
Application to Distributed AI Systems [16.690434072032176]
We show how compositional thinking can provide rules for the creation and management of architectural frameworks for complex systems.
The aim of the paper is not to provide viewpoints or architecture models specific to AI systems, but instead to provide guidelines on how a consistent framework can be built up with existing, or newly created, viewpoints.
arXiv Detail & Related papers (2022-12-27T18:05:02Z) - Analogical Concept Memory for Architectures Implementing the Common
Model of Cognition [1.9417302920173825]
We propose a new analogical concept memory for Soar that augments its current system of declarative long-term memories.
We demonstrate that the analogical learning methods implemented in the proposed memory can quickly learn a diverse types of novel concepts.
arXiv Detail & Related papers (2022-10-21T04:39:07Z) - Kernel Based Cognitive Architecture for Autonomous Agents [91.3755431537592]
This paper considers an evolutionary approach to creating a cognitive functionality.
We consider a cognitive architecture which ensures the evolution of the agent on the basis of Symbol Emergence Problem solution.
arXiv Detail & Related papers (2022-07-02T12:41:32Z) - AIGenC: An AI generalisation model via creativity [1.933681537640272]
Inspired by cognitive theories of creativity, this paper introduces a computational model (AIGenC)
It lays down the necessary components to enable artificial agents to learn, use and generate transferable representations.
We discuss the model's capability to yield better out-of-distribution generalisation in artificial agents.
arXiv Detail & Related papers (2022-05-19T17:43:31Z) - MRKL Systems: A modular, neuro-symbolic architecture that combines large
language models, external knowledge sources and discrete reasoning [50.40151403246205]
Huge language models (LMs) have ushered in a new era for AI, serving as a gateway to natural-language-based knowledge tasks.
We define a flexible architecture with multiple neural models, complemented by discrete knowledge and reasoning modules.
We describe this neuro-symbolic architecture, dubbed the Modular Reasoning, Knowledge and Language (MRKL) system.
arXiv Detail & Related papers (2022-05-01T11:01:28Z) - CogNGen: Constructing the Kernel of a Hyperdimensional Predictive
Processing Cognitive Architecture [79.07468367923619]
We present a new cognitive architecture that combines two neurobiologically plausible, computational models.
We aim to develop a cognitive architecture that has the power of modern machine learning techniques.
arXiv Detail & Related papers (2022-03-31T04:44:28Z) - Towards a Predictive Processing Implementation of the Common Model of
Cognition [79.63867412771461]
We describe an implementation of the common model of cognition grounded in neural generative coding and holographic associative memory.
The proposed system creates the groundwork for developing agents that learn continually from diverse tasks as well as model human performance at larger scales.
arXiv Detail & Related papers (2021-05-15T22:55:23Z) - Towards an Interface Description Template for AI-enabled Systems [77.34726150561087]
Reuse is a common system architecture approach that seeks to instantiate a system architecture with existing components.
There is currently no framework that guides the selection of necessary information to assess their portability to operate in a system different than the one for which the component was originally purposed.
We present ongoing work on establishing an interface description template that captures the main information of an AI-enabled component.
arXiv Detail & Related papers (2020-07-13T20:30:26Z) - Characterizing an Analogical Concept Memory for Architectures
Implementing the Common Model of Cognition [1.468003557277553]
We propose a new analogical concept memory for Soar that augments its current system of declarative long-term memories.
We demonstrate that the analogical learning methods implemented in the proposed memory can quickly learn a diverse types of novel concepts.
arXiv Detail & Related papers (2020-06-02T21:54:03Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.