{"url":"/dataset/s2b","name":"S2B","full_name":"Symbolic Behaviour Benchmark","description_markdown":"Suite of OpenAI Gym-compatible multi-agent reinforcement learning environment centered around meta-referential games to benchmark for behavioral traits pertaining to symbolic behaviours, as described in [Santoro et al., 2021, \"Symbolic Behaviours in Artificial Intelligence\"](https://arxiv.org/abs/2102.03406), with a primary focus on the following behavioural traits: \r\n\r\n* receptive, \r\n* constructive,\r\n* malleable, and \r\n* separable.","description_withheld":null,"homepage":"https://github.com/Near32/SymbolicBehaviourBenchmark","introduced_date":"2022-07-16","introduced_date_note":null,"introduced_by":null,"license":{"name":"MIT License","url":null},"modalities":[],"tasks":[{"name":"Systematic Generalization","url":"/task/systematic-generalization","datasets_with_task":"/datasets/task/systematic-generalization"}],"languages":[],"variants":["S2B"],"data_loaders":[{"repo":"https://github.com/near32/symbolicbehaviourbenchmark","url":"https://github.com/Near32/SymbolicBehaviourBenchmark#readme","frameworks":["tf","pytorch","jax"]}],"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."}