{"url":"/dataset/smac-off-near-parallel","name":"Off_Near_parallel","full_name":"SMAC+_Off_Near_parallel_20","description_markdown":"smac+ offensive near scenario with 20 parallel episodic buffer","description_withheld":null,"homepage":"https://osilab-kaist.github.io/smac_plus/","introduced_date":"2022-07-07","introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[],"tasks":[{"name":"SMAC+","url":"/task/smac-1","datasets_with_task":"/datasets/task/smac-1"}],"languages":[],"variants":["Off_Near_parallel"],"data_loaders":[],"num_papers_in_archive":7,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/smac-on-smac-off-near-parallel","task":"SMAC+","dataset_variant":"Off_Near_parallel","rows":10,"metrics":["Median Win Rate"],"first_row_in_archive_order":{"model":"QMIX","paper":"/paper/qmix-monotonic-value-function-factorisation","metrics":{"Median Win Rate":"95.0"},"code_links":[{"title":"ray-project/ray","url":"https://github.com/ray-project/ray/tree/master/rllib"},{"title":"opendilab/DI-engine","url":"https://github.com/opendilab/DI-engine/blob/main/ding/policy/qmix.py"},{"title":"oxwhirl/pymarl","url":"https://github.com/oxwhirl/pymarl"},{"title":"starry-sky6688/marl-algorithms","url":"https://github.com/starry-sky6688/marl-algorithms"},{"title":"oxwhirl/smac","url":"https://github.com/oxwhirl/smac"},{"title":"facebookresearch/benchmarl","url":"https://github.com/facebookresearch/benchmarl"},{"title":"hhhusiyi-monash/UPDeT","url":"https://github.com/hhhusiyi-monash/UPDeT"},{"title":"TonghanWang/NDQ","url":"https://github.com/TonghanWang/NDQ"},{"title":"nju-rl/acorm","url":"https://github.com/nju-rl/acorm"},{"title":"TonghanWang/DOP","url":"https://github.com/TonghanWang/DOP"},{"title":"puyuan1996/MARL","url":"https://github.com/puyuan1996/MARL"},{"title":"xiuyu0000/new_papers_codes","url":"https://github.com/xiuyu0000/new_papers_codes/tree/main/qmix"},{"title":"cathyhxh/ctds","url":"https://github.com/cathyhxh/ctds"},{"title":"jugg1er/air","url":"https://github.com/jugg1er/air"},{"title":"ifpen/wfcrl-benchmark","url":"https://github.com/ifpen/wfcrl-benchmark"},{"title":"gingkg/smac","url":"https://github.com/gingkg/smac"},{"title":"15534081591/QMIX","url":"https://github.com/15534081591/QMIX"},{"title":"2023-MindSpore-1/ms-code-221","url":"https://github.com/2023-MindSpore-1/ms-code-221/tree/main/qmix"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/disentangling-sources-of-risk-for","title":"Disentangling Sources of Risk for Distributional Multi-Agent Reinforcement Learning","date":"2021-09-29","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/decomposed-soft-actor-critic-method-for","title":"Decomposed Soft Actor-Critic Method for Cooperative Multi-Agent Reinforcement Learning","date":"2021-04-14","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/dfac-framework-factorizing-the-value-function","title":"DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-Learning","date":"2021-02-16","rows_on_this_dataset":3,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":1,"samples_ran":1,"samples_unverified":0,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/qtran-learning-to-factorize-with","title":"QTRAN: Learning to Factorize with Transformation for Cooperative Multi-Agent Reinforcement Learning","date":"2019-05-14","rows_on_this_dataset":1,"code_links":4,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":1,"samples_ran":0,"samples_unverified":1,"pointer_only_for_licence":1,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/qmix-monotonic-value-function-factorisation","title":"QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning","date":"2018-03-30","rows_on_this_dataset":1,"code_links":18,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":11,"samples_ran":9,"samples_unverified":2,"pointer_only_for_licence":6,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/value-decomposition-networks-for-cooperative","title":"Value-Decomposition Networks For Cooperative Multi-Agent Learning","date":"2017-06-16","rows_on_this_dataset":1,"code_links":10,"syntology":null},{"paper":"/paper/counterfactual-multi-agent-policy-gradients","title":"Counterfactual Multi-Agent Policy Gradients","date":"2017-05-24","rows_on_this_dataset":1,"code_links":7,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":1,"samples_ran":1,"samples_unverified":0,"pointer_only_for_licence":1,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":4,"samples_harvested":14,"samples_ran":11,"samples_unverified":3,"pointer_only_for_licence":8,"papers_with_no_sample_that_ran":1,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}