A multi-agent system combining contextual bandits, LLM agents, and semantic checkpoints improves convergence and robustness in adaptive method selection for sensitivity analysis and uncertainty quantification.
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Learning to Choose: An Empowerment-Guided Multi-Agent System with semantic communication for Adaptive Method Selection
A multi-agent system combining contextual bandits, LLM agents, and semantic checkpoints improves convergence and robustness in adaptive method selection for sensitivity analysis and uncertainty quantification.