Decentralized neuro-symbolic cognitive architectures: Integrating federated reasoning, governance, and causal inference for trustworthy, resilient Artificial Intelligence

Artificial intelligence (AI) is increasingly central to solving complex societal, economic, and scientific problems, yet prevailing models remain constrained by their opacity, vulnerability to adversarial inputs, and reliance on centralized infrastructures. These limitations underscore the urgent need for approaches that combine the adaptability of neural networks with the interpretability and rule-based precision of symbolic systems. At the same time, decentralization has emerged as a critical paradigm for enhancing trust, resilience, and accountability in intelligent systems. Together, these threads converge on the concept of decentralized neuro-symbolic cognitive systems, which integrate distributed inference, symbolic reasoning, and governance mechanisms to create secure and transparent frameworks for machine intelligence. This article presents a comprehensive methodology for the design and operation of such systems, advancing beyond conventional hybrid AI by embedding causal intent routing, federated cognitive capsules, encrypted episodic memory, and immutable epistemic ledgers. These elements are supported by governance innovations such as the NeuroConstitution™, which enables tokenized, evolvable norms and ensures accountability through transparent dispute resolution. The framework is evaluated across key application domains, including healthcare, finance, governance, and climate modeling, with comparative benchmarks demonstrating gains in robustness, interpretability, and systemic trust. By uniting symbolic reasoning, neural inference, and decentralized governance, this research outlines a pathway toward AI systems that are not only technically powerful but also socially aligned and ethically defensible. The article concludes that decentralized neuro-symbolic architectures provide a sustainable foundation for advancing trustworthy AI capable of supporting critical infrastructures and decision-making in a rapidly evolving world.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-09-30
DOI
https://doi.org/10.5281/zenodo.17787528
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
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article

Decentralized neuro-symbolic cognitive architectures: Integrating federated reasoning, governance, and causal inference for trustworthy, resilient Artificial Intelligence

Zenodo (CERN European Organization for Nuclear Research)
Ethics and Social Impacts of AI
article

Decentralized neuro-symbolic cognitive architectures: Integrating federated reasoning, governance, and causal inference for trustworthy, resilient Artificial Intelligence

article en

Abstract

Artificial intelligence (AI) is increasingly central to solving complex societal, economic, and scientific problems, yet prevailing models remain constrained by their opacity, vulnerability to adversarial inputs, and reliance on centralized infrastructures. These limitations underscore the urgent need for approaches that combine the adaptability of neural networks with the interpretability and rule-based precision of symbolic systems. At the same time, decentralization has emerged as a critical paradigm for enhancing trust, resilience, and accountability in intelligent systems. Together, these threads converge on the concept of decentralized neuro-symbolic cognitive systems, which integrate distributed inference, symbolic reasoning, and governance mechanisms to create secure and transparent frameworks for machine intelligence. This article presents a comprehensive methodology for the design and operation of such systems, advancing beyond conventional hybrid AI by embedding causal intent routing, federated cognitive capsules, encrypted episodic memory, and immutable epistemic ledgers. These elements are supported by governance innovations such as the NeuroConstitution™, which enables tokenized, evolvable norms and ensures accountability through transparent dispute resolution. The framework is evaluated across key application domains, including healthcare, finance, governance, and climate modeling, with comparative benchmarks demonstrating gains in robustness, interpretability, and systemic trust. By uniting symbolic reasoning, neural inference, and decentralized governance, this research outlines a pathway toward AI systems that are not only technically powerful but also socially aligned and ethically defensible. The article concludes that decentralized neuro-symbolic architectures provide a sustainable foundation for advancing trustworthy AI capable of supporting critical infrastructures and decision-making in a rapidly evolving world.

Zenodo (CERN European Organization for Nuclear Research)
Visa (United Kingdom) (GB), Visa (United States) (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 37%
Ethics and Social Impacts of AI
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Decentralized neuro-symbolic cognitive architectures: Integrating federated reasoning, governance, and causal inference for trustworthy, resilient Artificial Intelligence · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS