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Measuring Sample Efficiency and Generalization in Reinforcement Learning Benchmarks: NeurIPS 2020 Procgen Benchmark., , , , , , , , , и 13 other автор(ы). NeurIPS (Competition and Demos), том 133 из Proceedings of Machine Learning Research, стр. 361-395. PMLR, (2020)Insights From the NeurIPS 2021 NetHack Challenge., , , , , , , , , и 19 other автор(ы). NeurIPS (Competition and Demos), том 176 из Proceedings of Machine Learning Research, стр. 41-52. PMLR, (2021)CleanRL: High-quality Single-file Implementations of Deep Reinforcement Learning Algorithms., , , , , , и . J. Mach. Learn. Res., (2022)MABe22: A Multi-Species Multi-Task Benchmark for Learned Representations of Behavior., , , , , , , , , и 13 other автор(ы). ICML, том 202 из Proceedings of Machine Learning Research, стр. 32936-32990. PMLR, (2023)The Multi-Agent Behavior Dataset: Mouse Dyadic Social Interactions., , , , , , , , , и 1 other автор(ы). NeurIPS Datasets and Benchmarks, (2021)The CityLearn Challenge 2022: Overview, Results, and Lessons Learned., , , , , , , , , и 16 other автор(ы). NeurIPS (Competition and Demos), том 220 из Proceedings of Machine Learning Research, стр. 85-103. PMLR, (2021)