google-research/recsim
A configurable simulation platform for training and evaluating recommender systems using reinforcement learning.
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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.
Frequently asked
- What is google-research/recsim?
- A configurable simulation platform for training and evaluating recommender systems using reinforcement learning.
- Is recsim open source?
- Yes — google-research/recsim is open source, released under the Apache-2.0 license.
- What language is recsim written in?
- google-research/recsim is primarily written in Python.
- How popular is recsim?
- google-research/recsim has 785 stars on GitHub.
- Where can I find recsim?
- google-research/recsim is on GitHub at https://github.com/google-research/recsim.