Resilient by Design -- Active Inference for Distributed Continuum Intelligence
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arXiv
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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Acceso en línea: | |
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| _version_ | 1866912716024709120 |
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| author | Donta, Praveen Kumar Lapkovskis, Alfreds Mingozzi, Enzo Dustdar, Schahram |
| author_facet | Donta, Praveen Kumar Lapkovskis, Alfreds Mingozzi, Enzo Dustdar, Schahram |
| contents | Failures are the norm in highly complex and heterogeneous devices spanning the distributed computing continuum (DCC), from resource-constrained IoT and edge nodes to high-performance computing systems. Ensuring reliability and global consistency across these layers remains a major challenge, especially for AI-driven workloads requiring real-time, adaptive coordination. This work-in-progress paper introduces a Probabilistic Active Inference Resilience Agent (PAIR-Agent) to achieve resilience in DCC systems. PAIR-Agent performs three core operations: (i) constructing a causal fault graph from device logs, (ii) identifying faults while managing certainties and uncertainties using Markov blankets and the free energy principle, and (iii) autonomously healing issues through active inference. Through continuous monitoring and adaptive reconfiguration, the agent maintains service continuity and stability under diverse failure conditions. Theoretical validations confirm the reliability and effectiveness of the proposed framework. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_07202 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Resilient by Design -- Active Inference for Distributed Continuum Intelligence Donta, Praveen Kumar Lapkovskis, Alfreds Mingozzi, Enzo Dustdar, Schahram Distributed, Parallel, and Cluster Computing Artificial Intelligence Multiagent Systems Networking and Internet Architecture Failures are the norm in highly complex and heterogeneous devices spanning the distributed computing continuum (DCC), from resource-constrained IoT and edge nodes to high-performance computing systems. Ensuring reliability and global consistency across these layers remains a major challenge, especially for AI-driven workloads requiring real-time, adaptive coordination. This work-in-progress paper introduces a Probabilistic Active Inference Resilience Agent (PAIR-Agent) to achieve resilience in DCC systems. PAIR-Agent performs three core operations: (i) constructing a causal fault graph from device logs, (ii) identifying faults while managing certainties and uncertainties using Markov blankets and the free energy principle, and (iii) autonomously healing issues through active inference. Through continuous monitoring and adaptive reconfiguration, the agent maintains service continuity and stability under diverse failure conditions. Theoretical validations confirm the reliability and effectiveness of the proposed framework. |
| title | Resilient by Design -- Active Inference for Distributed Continuum Intelligence |
| topic | Distributed, Parallel, and Cluster Computing Artificial Intelligence Multiagent Systems Networking and Internet Architecture |
| url | https://arxiv.org/abs/2511.07202 |