Fields
Pick a domain and keep going deeper: field, subfield, topic. Every step lists the papers at that point or below it. The counts are papers that are accepted or in review; papers that were not accepted are in the full library.
Field
Reinforcement learning
Reinforcement learning studies agents that learn to act by trial and error or from logged experience. Work is evaluated by episodic return or normalised scores on standard environment suites (Atari, DeepMind Control, MuJoCo, Procgen, D4RL), at a fixed budget of environment steps, aggregated over many seeds with interval estimates because results are highly variable.