E. Hachem

Heuristic Learning for Active Flow Control Using Coding Agents

This work introduces a constrained heuristic-learning protocol in which an agent iteratively proposes, evaluates, and revises controller implementations while interacting exclusively through the public benchmark interface, and suggests that heuristic learning through coding agents constitutes a credible and complementary alternative to conventional reinforcement learning.