{"url":"/dataset/colosseumrl","name":"ColosseumRL","full_name":null,"description_markdown":"**ColosseumRL** is a framework for research in reinforcement learning in n-player games.\r\n\r\nColosseumRL contains a number of multiagent free-for-all games. Currently, we have Tron, Blokus, and 3 and 4-player tic-tac-toe. In the future, we will be adding Chinese checkers and other similar games. Tron is a fully-observable multiagent free-for-all turn-based snake variant where players try to survive the longest without crashing into walls or each other. Blokus is a fully-observable multiagent free-for-all turn-based game in which players place pieces on a board to claim space and strategically block opponents from placing their own pieces.","description_withheld":null,"homepage":"https://colosseumrl.igb.uci.edu/","introduced_date":"2019-12-10","introduced_date_note":null,"introduced_by":{"paper":null,"title":"ColosseumRL: A Framework for Multiagent Reinforcement Learning in $N$-Player Games","first_author":null,"url":null},"license":null,"modalities":[{"name":"Environment","url":"/datasets/modality/environment"}],"tasks":[{"name":"Multi-agent Reinforcement Learning","url":"/task/multi-agent-reinforcement-learning","datasets_with_task":"/datasets/task/multi-agent-reinforcement-learning"}],"languages":[],"variants":["ColosseumRL"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"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."}