RecSim provides configurable simulation environments for recommender systems research, supporting sequential user interaction modeling and RL-based recommendation algorithms. It allows researchers to define user preference models, latent state dynamics, and response behaviors to evaluate recommendation strategies in controlled settings. The platform integrates with TensorFlow and supports bandit algorithms for GLMs.