Computational Concept of the Psyche
- URL: http://arxiv.org/abs/2603.15586v2
- Date: Sun, 22 Mar 2026 12:34:32 GMT
- Title: Computational Concept of the Psyche
- Abstract summary: An overview of approaches to modeling the human psyche in the context of constructing an artificial one is presented.<n>A computational formalization is proposed for creating artificial general intelligence systems for an agent.
- Score: 0.12891210250935145
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: This article presents an overview of approaches to modeling the human psyche in the context of constructing an artificial one. Based on this overview, a concept of cognitive architecture is proposed, in which the psyche is viewed as the operating system of a living or artificial subject, comprising a space of states, including the state of needs that determine the meaning of a subject's being in relation to stimuli from the external world, and intelligence as a decision-making system regarding actions in this world to satisfy these needs. Based on this concept, a computational formalization is proposed for creating artificial general intelligence systems for an agent through experiential learning in a state space that includes agent's needs, taking into account their biological or existential significance for the intelligent agent, along with agent's sensations and actions. Thus, the problem of constructing artificial general intelligence is formalized as a system for making optimal decisions in the space of specific agent needs under conditions of uncertainty, maximizing success in achieving goals, minimizing existential risks, and maximizing energy efficiency. A minimal experimental implementation of the model is presented.
Related papers
- Evolving Cognitive Architectures [51.56484100374058]
This article proposes a research and development direction that would lead to the creation of next-generation intelligent technical systems.<n>A distinctive feature of these systems is their ability to undergo evolutionary change.
arXiv Detail & Related papers (2025-12-29T10:09:20Z) - Computational Concept of the Psyche (in Russian) [0.12891210250935145]
The article provides an overview of approaches to modeling the human psyche in the perspective of building an artificial one.<n>A concept of cognitive architecture is proposed, where psyche is considered as an operating system of a living or artificial subject.
arXiv Detail & Related papers (2025-09-06T10:22:27Z) - Neural Brain: A Neuroscience-inspired Framework for Embodied Agents [78.61382193420914]
Current AI systems, such as large language models, remain disembodied, unable to physically engage with the world.<n>At the core of this challenge lies the concept of Neural Brain, a central intelligence system designed to drive embodied agents with human-like adaptability.<n>This paper introduces a unified framework for the Neural Brain of embodied agents, addressing two fundamental challenges.
arXiv Detail & Related papers (2025-05-12T15:05:34Z) - Nature's Insight: A Novel Framework and Comprehensive Analysis of Agentic Reasoning Through the Lens of Neuroscience [11.174550573411008]
We propose a novel neuroscience-inspired framework for agentic reasoning.<n>We apply this framework to systematically classify and analyze existing AI reasoning methods.<n>We propose new neural-inspired reasoning methods, analogous to chain-of-thought prompting.
arXiv Detail & Related papers (2025-05-07T14:25:46Z) - Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems [132.77459963706437]
This book provides a comprehensive overview, framing intelligent agents within modular, brain-inspired architectures.<n>It explores self-enhancement and adaptive evolution mechanisms, exploring how agents autonomously refine their capabilities.<n>It also examines the collective intelligence emerging from agent interactions, cooperation, and societal structures.
arXiv Detail & Related papers (2025-03-31T18:00:29Z) - Brain-inspired AI Agent: The Way Towards AGI [5.867107330135988]
Researchers in brain-inspired AI seek inspiration from the operational mechanisms of the human brain, aiming to replicate its functional rules in intelligent models.<n>We propose the concept of a brain-inspired AI agent and analyze how to extract relatively feasible and agent-compatible cortical region functionalities.<n> Implementing these structures within an agent enables it to achieve basic cognitive intelligence akin to human capabilities.
arXiv Detail & Related papers (2024-12-12T02:15:48Z) - Position Paper: Agent AI Towards a Holistic Intelligence [53.35971598180146]
We emphasize developing Agent AI -- an embodied system that integrates large foundation models into agent actions.
In this paper, we propose a novel large action model to achieve embodied intelligent behavior, the Agent Foundation Model.
arXiv Detail & Related papers (2024-02-28T16:09:56Z) - 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) - Active Inference in Robotics and Artificial Agents: Survey and
Challenges [51.29077770446286]
We review the state-of-the-art theory and implementations of active inference for state-estimation, control, planning and learning.
We showcase relevant experiments that illustrate its potential in terms of adaptation, generalization and robustness.
arXiv Detail & Related papers (2021-12-03T12:10:26Z) - QKSA: Quantum Knowledge Seeking Agent [0.0]
We present the motivation and the core thesis towards the implementation of a Quantum Knowledge Seeking Agent (QKSA)
QKSA is a general reinforcement learning agent that can be used to model classical and quantum dynamics.
arXiv Detail & Related papers (2021-07-03T13:07:58Z) - Deep Interpretable Models of Theory of Mind For Human-Agent Teaming [0.7734726150561086]
We develop an interpretable modular neural framework for modeling the intentions of other observed entities.
We demonstrate the efficacy of our approach with experiments on data from human participants on a search and rescue task in Minecraft.
arXiv Detail & Related papers (2021-04-07T06:18:58Z)
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.