8 stories tagged Framework
Researchers propose a comprehensive framework for AI-driven autonomous systems that combines connectionist and symbolic AI, organized around cognitive functions and long-term memory, to bridge pattern recognition and logical reasoning.
Researchers propose a monotonic evaluation framework for wildfire risk systems that measures whether higher predicted risk scores consistently correspond to increased operational load — such as number of fires, intervention time, and deployed resources — rather than relying on traditional metrics like F1-score or IoU.
Researchers propose CPSAINT, a seven-layer integrity decomposition paired with the FRIESA-K risk functional, to quantify residual risk in agentic AI. The framework bridges the gap between describing failure mechanisms and producing transferable risk estimates, enabling safer deployment of autonomous AI agents.
Researchers at CNPO developed G-SHARE, a guideline-based structured reasoning framework that diagnoses human-factor events in nuclear power plants with greater reliability and logical consistency than existing AI approaches.
Researchers introduced SDOF, a new framework that improves how AI agents work together by enforcing strict process rules. This could make multi-agent systems more reliable for real-world business tasks.
Researchers introduce OneManCompany (OMC), a framework to structure multi-agent systems with dynamic team formation and governance. This approach decouples organizational strategy from individual agent skills, enabling more flexible and scalable AI workflows.
MMORF is a framework for designing multi-objective retrosynthesis planning systems. It leverages language model-based multi-agent systems to balance quality, safety, and cost objectives.
ATANT is an open evaluation framework for measuring continuity in AI systems. It assesses the ability to persist and update meaningful context across time.