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GENCO achieves up to 85x speedups in optimal power flow analysis while maintaining higher feasibility and optimality than classical methods.
Effective curling strategies can be learned entirely through self-supervision, matching expert heuristics without human-annotated data.
Bridging the gap between reinforcement learning and control theory could unlock new synergies in optimizing unknown dynamical systems.
Skip the expensive modeling step: this data-driven approach to traffic light control directly optimizes traffic flow using real-world data, slashing travel times and emissions in a massive Zürich simulation.
