Reinforcement Learning Guides Live Fish Schools
This arXiv preprint by Hiroaki Kawashima (submitted March 17, 2026) investigates guiding live fish schools using 2D virtual fish trained with model-free reinforcement learning and evaluated in simulation and real-world trials. Simulations show learned policies succeed even when simulated fish frequently ignore stimuli, while live experiments demonstrate the policy steers schools toward specified target directions and significantly outperforms no-stimulus and heuristic 'stay-at-edge' baselines.
Scoring Rationale
Novel experimentally validated RL application to collective animal behavior, but limited by preprint status and narrow biological generalizability.
Practice interview problems based on real data
1,500+ SQL & Python problems across 15 industry datasets — the exact type of data you work with.
Try 250 free problems
