Research IdeaNov 27, 2025
Meta-RLVR: Self-Evolving Reward Functions for Energy-Aware Multi-Agent Systems
A novel framework that combines Test-Time Reinforcement Learning with multi-agent systems to develop adaptive reward functions for energy management in smart grids. The system learns to optimize both agent coordination and energy efficiency through self-evolution of reward mechanisms, addressing both the limitations of current multi-agent LLM systems and energy management challenges.
reinforcement-learningmulti-agent-systemsenergy-optimization