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June 10, 20260 citationsOpen Access

EvoMind: A Governed Cognitive Architecture for Autonomous Reasoning, Planning, Memory, and Desktop Agents

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GAGabriel AllitGabriel Entertainment (United States)

Key Points

  • The research aims to develop a cognitive architecture that separates cognitive processes from language generation and emphasizes governance.
  • Developed a closed-loop cognitive cycle organized around perception, memory, decision support, and execution.
  • Integrated governance features such as policy enforcement and validation workflows.
  • Documented architecture and methodologies to support external evaluation and reproducibility.
  • EvoMind demonstrates effective memory formation and decision support within its cognitive architecture.
  • Governance measures are successfully implemented, contributing to controlled autonomy.
  • The architecture acts as a research platform for future developments and evaluations in autonomous reasoning.

Abstract

EvoMind is a governed cognitive architecture and research platform for autonomous reasoning, memory, planning, learning, and desktop-agent execution. The architecture is organized around a closed-loop cognitive cycle consisting of perception, world-model maintenance, memory formation and retrieval, decision support, planning, governance enforcement, execution through the Raziel control layer, observation, and learning or adaptation. A primary design goal of EvoMind is the separation of cognition from language generation. The architecture emphasizes governance, auditability, provenance, reversibility, and bounded autonomy through explicit approval boundaries, policy enforcement, claim-boundary controls, and validation workflows. This release contains architecture documentation, governance documentation, validation methodology, benchmark-readiness mapping, citation metadata, public-safe diagrams, a technical whitepaper, and supporting publication artifacts. The package is intended as a research artifact and architectural reference rather than a claim of achieved artificial general intelligence. The included documentation explicitly distinguishes implemented capabilities, experimental subsystems, future-work areas, and unverified claims. Future releases will focus on external evaluation, reproducibility artifacts, benchmark evidence, and expanded deployment documentation.

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Cite This Study

Gabriel Allit (2026) studied this question.

synapsesocial.com/papers/6a28fe326f82f25be989b9fahttps://doi.org/10.5281/zenodo.20580152
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  4. 4From Intent to Verified Work Products: Governed Semantic Capability Composition in EvoMind2026 · 2 citations
  5. 5Cognitive Development in Artificial Agents: A Theoretical Proposal2025