Update JSON sytem metadata

systems/babyai-sr/metadata.yml

@@ -1,4 +1,5 @@
 origin:
+  name: babyai-sr
   source: https://github.com/brendon-boldt/babyai_sr
   upstream_source: https://github.com/thomasaunger/babyai_sr
   paper: https://arxiv.org/abs/2001.01772

systems/babyai-sr/system.json

@@ -1 +1,97 @@
-[{"origin":{"source":"https://github.com/brendon-boldt/babyai_sr","upstream_source":"https://github.com/thomasaunger/babyai_sr","paper":"https://arxiv.org/abs/2001.01772"},"system":{"game_type":"navigation","game_subtype":"grid","data_source":"synthetic","observation_continuous":false,"observation_type":"vector","seeding_available":true,"multi_step":true,"multi_utterance":true,"more_than_2_agents":false,"symmetric_agents":false,"variants":{"GoToObj":{"env":"GoToObj"},"GoToObjLocked":{"env":"GoToObjLocked"},"GoToObjLocked_ambiguous":{"env":"GoToObjLocked_ambiguous"},"GoToObjLocked_ambiguous-freq_1":{"env":"GoToObjLocked_ambiguous","message_frequency":1},"GoToObjLocked_ambiguous-freq_2":{"env":"GoToObjLocked_ambiguous","message_frequency":2},"GoToObjLocked_ambiguous-freq_32":{"env":"GoToObjLocked_ambiguous","message_frequency":32},"GoToObjLocked_ambiguous-freq_4":{"env":"GoToObjLocked_ambiguous","message_frequency":4},"GoToObjLocked_ambiguous-msg_16":{"env":"GoToObjLocked_ambiguous","message_length":16,"vocab_size":16},"GoToObjLocked_ambiguous-msg_32":{"env":"GoToObjLocked_ambiguous","message_length":32,"vocab_size":32},"GoToObjLocked_ambiguous-msg_4":{"env":"GoToObjLocked_ambiguous","message_length":4,"vocab_size":4},"GoToObjUnlocked":{"env":"GoToObjUnlocked"},"GoToObjUnlocked-freq_1":{"env":"GoToObjUnlocked","message_frequency":1},"GoToObjUnlocked-freq_2":{"env":"GoToObjUnlocked","message_frequency":2},"GoToObjUnlocked-freq_32":{"env":"GoToObjUnlocked","message_frequency":32},"GoToObjUnlocked-freq_4":{"env":"GoToObjUnlocked","message_frequency":4},"GoToObjUnlocked-msg_16":{"env":"GoToObjUnlocked","message_length":16,"vocab_size":16},"GoToObjUnlocked-msg_32":{"env":"GoToObjUnlocked","message_length":32,"vocab_size":32},"GoToObjUnlocked-msg_4":{"env":"GoToObjUnlocked","message_length":4,"vocab_size":4}}},"notes":"Default\n  message_frequency is every 8 steps,\n  message_length is 8,\n  vocab_size is 8.\n"}]
+{
+  "origin": {
+    "name": "babyai-sr",
+    "source": "https://github.com/brendon-boldt/babyai_sr",
+    "upstream_source": "https://github.com/thomasaunger/babyai_sr",
+    "paper": "https://arxiv.org/abs/2001.01772"
+  },
+  "system": {
+    "game_type": "navigation",
+    "game_subtype": "grid",
+    "data_source": "synthetic",
+    "observation_continuous": false,
+    "observation_type": "vector",
+    "seeding_available": true,
+    "multi_step": true,
+    "multi_utterance": true,
+    "more_than_2_agents": false,
+    "symmetric_agents": false,
+    "variants": {
+      "GoToObj": {
+        "env": "GoToObj"
+      },
+      "GoToObjLocked": {
+        "env": "GoToObjLocked"
+      },
+      "GoToObjLocked_ambiguous": {
+        "env": "GoToObjLocked_ambiguous"
+      },
+      "GoToObjLocked_ambiguous-freq_1": {
+        "env": "GoToObjLocked_ambiguous",
+        "message_frequency": 1
+      },
+      "GoToObjLocked_ambiguous-freq_2": {
+        "env": "GoToObjLocked_ambiguous",
+        "message_frequency": 2
+      },
+      "GoToObjLocked_ambiguous-freq_32": {
+        "env": "GoToObjLocked_ambiguous",
+        "message_frequency": 32
+      },
+      "GoToObjLocked_ambiguous-freq_4": {
+        "env": "GoToObjLocked_ambiguous",
+        "message_frequency": 4
+      },
+      "GoToObjLocked_ambiguous-msg_16": {
+        "env": "GoToObjLocked_ambiguous",
+        "message_length": 16,
+        "vocab_size": 16
+      },
+      "GoToObjLocked_ambiguous-msg_32": {
+        "env": "GoToObjLocked_ambiguous",
+        "message_length": 32,
+        "vocab_size": 32
+      },
+      "GoToObjLocked_ambiguous-msg_4": {
+        "env": "GoToObjLocked_ambiguous",
+        "message_length": 4,
+        "vocab_size": 4
+      },
+      "GoToObjUnlocked": {
+        "env": "GoToObjUnlocked"
+      },
+      "GoToObjUnlocked-freq_1": {
+        "env": "GoToObjUnlocked",
+        "message_frequency": 1
+      },
+      "GoToObjUnlocked-freq_2": {
+        "env": "GoToObjUnlocked",
+        "message_frequency": 2
+      },
+      "GoToObjUnlocked-freq_32": {
+        "env": "GoToObjUnlocked",
+        "message_frequency": 32
+      },
+      "GoToObjUnlocked-freq_4": {
+        "env": "GoToObjUnlocked",
+        "message_frequency": 4
+      },
+      "GoToObjUnlocked-msg_16": {
+        "env": "GoToObjUnlocked",
+        "message_length": 16,
+        "vocab_size": 16
+      },
+      "GoToObjUnlocked-msg_32": {
+        "env": "GoToObjUnlocked",
+        "message_length": 32,
+        "vocab_size": 32
+      },
+      "GoToObjUnlocked-msg_4": {
+        "env": "GoToObjUnlocked",
+        "message_length": 4,
+        "vocab_size": 4
+      }
+    }
+  },
+  "notes": "Default\n  message_frequency is every 8 steps,\n  message_length is 8,\n  vocab_size is 8.\n"
+}

systems/corpus-transfer-yao-et-al/metadata.yml

@@ -1,4 +1,5 @@
 origin:
+  name: corpus-transfer-yao-et-al
   source: https://github.com/brendon-boldt/ec-nl
   upstream_source: https://github.com/ysymyth/ec-nl
   paper: https://openreview.net/forum?id=49A1Y6tRhaq

systems/corpus-transfer-yao-et-al/system.json

@@ -1 +1,28 @@
-[{"origin":{"source":"https://github.com/brendon-boldt/ec-nl","upstream_source":"https://github.com/ysymyth/ec-nl","paper":"https://openreview.net/forum?id=49A1Y6tRhaq"},"system":{"game_type":"signalling","game_subtype":"discrimination","observation_type":"image","observation_continuous":true,"data_source":"natural","seeding_available":true,"symmetric_agents":false,"multi_step":false,"multi_utterance":false,"more_than_2_agents":false,"variants":{"coco_2014":{"dataset":"coco_2014"},"cc":{"dataset":"conceptual_captions"}}}}]
+{
+  "origin": {
+    "name": "corpus-transfer-yao-et-al",
+    "source": "https://github.com/brendon-boldt/ec-nl",
+    "upstream_source": "https://github.com/ysymyth/ec-nl",
+    "paper": "https://openreview.net/forum?id=49A1Y6tRhaq"
+  },
+  "system": {
+    "game_type": "signalling",
+    "game_subtype": "discrimination",
+    "observation_type": "image",
+    "observation_continuous": true,
+    "data_source": "natural",
+    "seeding_available": true,
+    "symmetric_agents": false,
+    "multi_step": false,
+    "multi_utterance": false,
+    "more_than_2_agents": false,
+    "variants": {
+      "coco_2014": {
+        "dataset": "coco_2014"
+      },
+      "cc": {
+        "dataset": "conceptual_captions"
+      }
+    }
+  }
+}

systems/ec-at-scale/metadata.yml

@@ -1,4 +1,5 @@
 origin:
+  name: ec-at-scale
   source: https://github.com/brendon-boldt/emergent_communication_at_scale
   upstream_source: https://github.com/google-deepmind/emergent_communication_at_scale
   paper: https://openreview.net/forum?id=AUGBfDIV9rL

systems/ec-at-scale/system.json

@@ -1 +1,42 @@
-[{"origin":{"source":"https://github.com/brendon-boldt/emergent_communication_at_scale","upstream_source":"https://github.com/google-deepmind/emergent_communication_at_scale","paper":"https://openreview.net/forum?id=AUGBfDIV9rL"},"system":{"game_type":"signalling","data_source":"natural","game_subtype":"discrimination","observation_type":"image","observation_continuous":true,"seeding_available":true,"multi_step":false,"more_than_2_agents":true,"multi_utterance":false,"symmetric_agents":false,"variants":{"imagenet-1x10":{"n_receivers":10,"n_senders":1},"imagenet-10x10":{"n_receivers":10,"n_senders":10},"imagenet-5x5":{"n_receivers":5,"n_senders":5},"imagenet-1x1":{"n_receivers":1,"n_senders":1},"imagenet-10x1":{"n_receivers":1,"n_senders":10}}}}]
+{
+  "origin": {
+    "name": "ec-at-scale",
+    "source": "https://github.com/brendon-boldt/emergent_communication_at_scale",
+    "upstream_source": "https://github.com/google-deepmind/emergent_communication_at_scale",
+    "paper": "https://openreview.net/forum?id=AUGBfDIV9rL"
+  },
+  "system": {
+    "game_type": "signalling",
+    "data_source": "natural",
+    "game_subtype": "discrimination",
+    "observation_type": "image",
+    "observation_continuous": true,
+    "seeding_available": true,
+    "multi_step": false,
+    "more_than_2_agents": true,
+    "multi_utterance": false,
+    "symmetric_agents": false,
+    "variants": {
+      "imagenet-1x10": {
+        "n_receivers": 10,
+        "n_senders": 1
+      },
+      "imagenet-10x10": {
+        "n_receivers": 10,
+        "n_senders": 10
+      },
+      "imagenet-5x5": {
+        "n_receivers": 5,
+        "n_senders": 5
+      },
+      "imagenet-1x1": {
+        "n_receivers": 1,
+        "n_senders": 1
+      },
+      "imagenet-10x1": {
+        "n_receivers": 1,
+        "n_senders": 10
+      }
+    }
+  }
+}

systems/egg-discrimination/metadata.yml

@@ -1,4 +1,5 @@
 origin:
+  name: egg-discrimination
   source: https://github.com/facebookresearch/EGG
 system:
   game_type: signalling

systems/egg-discrimination/system.json

@@ -1 +1,89 @@
-[{"origin":{"source":"https://github.com/facebookresearch/EGG"},"system":{"game_type":"signalling","game_subtype":"discrimination","observation_type":"vector","observation_continuous":false,"multi_step":false,"data_source":"synthetic","seeding_available":true,"symmetric_agents":false,"multi_utterance":false,"more_than_2_agents":false,"variants":{"4-attr_4-val_3-dist_0-seed":{"seed":0,"n_attributes":4,"n_values":4,"n_distractors":3},"4-attr_4-val_3-dist_1-seed":{"seed":1,"n_attributes":4,"n_values":4,"n_distractors":3},"4-attr_4-val_3-dist_2-seed":{"seed":2,"n_attributes":4,"n_values":4,"n_distractors":3},"6-attr_6-val_3-dist_0-seed":{"seed":0,"n_attributes":6,"n_values":6,"n_distractors":3},"6-attr_6-val_3-dist_1-seed":{"seed":1,"n_attributes":6,"n_values":6,"n_distractors":3},"6-attr_6-val_3-dist_2-seed":{"seed":2,"n_attributes":6,"n_values":6,"n_distractors":3},"6-attr_6-val_9-dist_0-seed":{"seed":0,"n_attributes":6,"n_values":6,"n_distractors":9},"6-attr_6-val_9-dist_1-seed":{"seed":1,"n_attributes":6,"n_values":6,"n_distractors":9},"6-attr_6-val_9-dist_2-seed":{"seed":2,"n_attributes":6,"n_values":6,"n_distractors":9},"8-attr_8-val_3-dist_0-seed":{"n_attributes":8,"n_values":8,"n_distractors":3},"8-attr_8-val_3-dist_1-seed":{"n_attributes":8,"n_values":8,"n_distractors":3},"8-attr_8-val_3-dist_2-seed":{"n_attributes":8,"n_values":8,"n_distractors":3}}}}]
+{
+  "origin": {
+    "name": "egg-discrimination",
+    "source": "https://github.com/facebookresearch/EGG"
+  },
+  "system": {
+    "game_type": "signalling",
+    "game_subtype": "discrimination",
+    "observation_type": "vector",
+    "observation_continuous": false,
+    "multi_step": false,
+    "data_source": "synthetic",
+    "seeding_available": true,
+    "symmetric_agents": false,
+    "multi_utterance": false,
+    "more_than_2_agents": false,
+    "variants": {
+      "4-attr_4-val_3-dist_0-seed": {
+        "seed": 0,
+        "n_attributes": 4,
+        "n_values": 4,
+        "n_distractors": 3
+      },
+      "4-attr_4-val_3-dist_1-seed": {
+        "seed": 1,
+        "n_attributes": 4,
+        "n_values": 4,
+        "n_distractors": 3
+      },
+      "4-attr_4-val_3-dist_2-seed": {
+        "seed": 2,
+        "n_attributes": 4,
+        "n_values": 4,
+        "n_distractors": 3
+      },
+      "6-attr_6-val_3-dist_0-seed": {
+        "seed": 0,
+        "n_attributes": 6,
+        "n_values": 6,
+        "n_distractors": 3
+      },
+      "6-attr_6-val_3-dist_1-seed": {
+        "seed": 1,
+        "n_attributes": 6,
+        "n_values": 6,
+        "n_distractors": 3
+      },
+      "6-attr_6-val_3-dist_2-seed": {
+        "seed": 2,
+        "n_attributes": 6,
+        "n_values": 6,
+        "n_distractors": 3
+      },
+      "6-attr_6-val_9-dist_0-seed": {
+        "seed": 0,
+        "n_attributes": 6,
+        "n_values": 6,
+        "n_distractors": 9
+      },
+      "6-attr_6-val_9-dist_1-seed": {
+        "seed": 1,
+        "n_attributes": 6,
+        "n_values": 6,
+        "n_distractors": 9
+      },
+      "6-attr_6-val_9-dist_2-seed": {
+        "seed": 2,
+        "n_attributes": 6,
+        "n_values": 6,
+        "n_distractors": 9
+      },
+      "8-attr_8-val_3-dist_0-seed": {
+        "n_attributes": 8,
+        "n_values": 8,
+        "n_distractors": 3
+      },
+      "8-attr_8-val_3-dist_1-seed": {
+        "n_attributes": 8,
+        "n_values": 8,
+        "n_distractors": 3
+      },
+      "8-attr_8-val_3-dist_2-seed": {
+        "n_attributes": 8,
+        "n_values": 8,
+        "n_distractors": 3
+      }
+    }
+  }
+}

systems/egg-reconstruction/metadata.yml

@@ -1,4 +1,5 @@
 origin:
+  name: egg-reconstruction
   source: https://github.com/facebookresearch/EGG
 system:
   game_type: signalling

systems/egg-reconstruction/system.json

@@ -1 +1,32 @@
-[{"origin":{"source":"https://github.com/facebookresearch/EGG"},"system":{"game_type":"signalling","game_subtype":"reconstruction","observation_type":"vector","observation_continuous":false,"multi_step":false,"data_source":"synthetic","seeding_available":true,"multi_utterance":false,"symmetric_agents":false,"more_than_2_agents":false,"variants":{"4-attr_4-val_10-vocab_10-len":{"n_attributes":4,"n_values":4},"6-attr_6-val_10-vocab_10-len":{"n_attributes":6,"n_values":6},"8-attr_8-val_10-vocab_10-len":{"n_attributes":8,"n_values":8}}}}]
+{
+  "origin": {
+    "name": "egg-reconstruction",
+    "source": "https://github.com/facebookresearch/EGG"
+  },
+  "system": {
+    "game_type": "signalling",
+    "game_subtype": "reconstruction",
+    "observation_type": "vector",
+    "observation_continuous": false,
+    "multi_step": false,
+    "data_source": "synthetic",
+    "seeding_available": true,
+    "multi_utterance": false,
+    "symmetric_agents": false,
+    "more_than_2_agents": false,
+    "variants": {
+      "4-attr_4-val_10-vocab_10-len": {
+        "n_attributes": 4,
+        "n_values": 4
+      },
+      "6-attr_6-val_10-vocab_10-len": {
+        "n_attributes": 6,
+        "n_values": 6
+      },
+      "8-attr_8-val_10-vocab_10-len": {
+        "n_attributes": 8,
+        "n_values": 8
+      }
+    }
+  }
+}

systems/generalizations-mu-goodman/metadata.yml

@@ -1,4 +1,5 @@
 origin:
+  name: generalizations-mu-goodman
   source: https://github.com/brendon-boldt/emergent-generalization
   upstream_source: https://github.com/jayelm/emergent-generalization
   paper: https://openreview.net/forum?id=yq5MYHVaClG

systems/generalizations-mu-goodman/system.json

@@ -1 +1,35 @@
-[{"origin":{"source":"https://github.com/brendon-boldt/emergent-generalization","upstream_source":"https://github.com/jayelm/emergent-generalization","paper":"https://openreview.net/forum?id=yq5MYHVaClG"},"system":{"game_type":"signalling","game_subtype":"discrimination","observation_type":"image","observation_continuous":true,"multi_step":false,"seeding_available":false,"data_source":"synthetic","multi_utterance":false,"more_than_2_agents":false,"symmetric_agents":false,"variants":{"shapeworld-reference":{},"shapeworld-set_reference":{},"shapeworld-concept":{},"cub-reference":{"data_source":"natural"},"cub-set_reference":{"data_source":"natural"},"cub-concept":{"data_source":"natural"}}},"notes":"The sampled output from this environment has both \"train\" (seen) and \"test\" (unseen) values.  For now, we are just using the previously seen examples as we expect them to have better performance.  The unseen examples could be included in the future (as separate corpora).\n"}]
+{
+  "origin": {
+    "name": "generalizations-mu-goodman",
+    "source": "https://github.com/brendon-boldt/emergent-generalization",
+    "upstream_source": "https://github.com/jayelm/emergent-generalization",
+    "paper": "https://openreview.net/forum?id=yq5MYHVaClG"
+  },
+  "system": {
+    "game_type": "signalling",
+    "game_subtype": "discrimination",
+    "observation_type": "image",
+    "observation_continuous": true,
+    "multi_step": false,
+    "seeding_available": false,
+    "data_source": "synthetic",
+    "multi_utterance": false,
+    "more_than_2_agents": false,
+    "symmetric_agents": false,
+    "variants": {
+      "shapeworld-reference": {},
+      "shapeworld-set_reference": {},
+      "shapeworld-concept": {},
+      "cub-reference": {
+        "data_source": "natural"
+      },
+      "cub-set_reference": {
+        "data_source": "natural"
+      },
+      "cub-concept": {
+        "data_source": "natural"
+      }
+    }
+  },
+  "notes": "The sampled output from this environment has both \"train\" (seen) and \"test\" (unseen) values.  For now, we are just using the previously seen examples as we expect them to have better performance.  The unseen examples could be included in the future (as separate corpora).\n"
+}

systems/nav-to-center/metadata.yml

@@ -1,4 +1,5 @@
 origin:
+  name: nav-to-center
   source: https://github.com/brendon-boldt/filex-emergent-language
   paper: https://openreview.net/forum?id=49A1Y6tRhaq
 system:

systems/nav-to-center/system.json

@@ -1 +1,81 @@
-[{"origin":{"source":"https://github.com/brendon-boldt/filex-emergent-language","paper":"https://openreview.net/forum?id=49A1Y6tRhaq"},"system":{"game_type":"navigation","game_subtype":"None","observation_type":"vector","observation_continuous":true,"data_source":"synthetic","seeding_available":false,"symmetric_agents":false,"multi_step":true,"multi_utterance":true,"more_than_2_agents":false,"variants":{"lexicon_size_11":{"vocab_size":11},"lexicon_size_118":{"vocab_size":118},"lexicon_size_17":{"vocab_size":17},"lexicon_size_174":{"vocab_size":114},"lexicon_size_25":{"vocab_size":25},"lexicon_size_255":{"vocab_size":255},"lexicon_size_37":{"vocab_size":37},"lexicon_size_54":{"vocab_size":54},"lexicon_size_7":{"vocab_size":7},"lexicon_size_80":{"vocab_size":80},"temperature_0.1":{"gumbel_softmax_temperature":0.1},"temperature_0.167":{"gumbel_softmax_temperature":0.167},"temperature_0.278":{"gumbel_softmax_temperature":0.278},"temperature_0.464":{"gumbel_softmax_temperature":0.464},"temperature_0.774":{"gumbel_softmax_temperature":0.774},"temperature_10":{"gumbel_softmax_temperature":10},"temperature_1.29":{"gumbel_softmax_temperature":1.29},"temperature_2.15":{"gumbel_softmax_temperature":2.15},"temperature_3.59":{"gumbel_softmax_temperature":3.59},"temperature_5.99":{"gumbel_softmax_temperature":5.99}}}}]
+{
+  "origin": {
+    "name": "nav-to-center",
+    "source": "https://github.com/brendon-boldt/filex-emergent-language",
+    "paper": "https://openreview.net/forum?id=49A1Y6tRhaq"
+  },
+  "system": {
+    "game_type": "navigation",
+    "game_subtype": "None",
+    "observation_type": "vector",
+    "observation_continuous": true,
+    "data_source": "synthetic",
+    "seeding_available": false,
+    "symmetric_agents": false,
+    "multi_step": true,
+    "multi_utterance": true,
+    "more_than_2_agents": false,
+    "variants": {
+      "lexicon_size_11": {
+        "vocab_size": 11
+      },
+      "lexicon_size_118": {
+        "vocab_size": 118
+      },
+      "lexicon_size_17": {
+        "vocab_size": 17
+      },
+      "lexicon_size_174": {
+        "vocab_size": 114
+      },
+      "lexicon_size_25": {
+        "vocab_size": 25
+      },
+      "lexicon_size_255": {
+        "vocab_size": 255
+      },
+      "lexicon_size_37": {
+        "vocab_size": 37
+      },
+      "lexicon_size_54": {
+        "vocab_size": 54
+      },
+      "lexicon_size_7": {
+        "vocab_size": 7
+      },
+      "lexicon_size_80": {
+        "vocab_size": 80
+      },
+      "temperature_0.1": {
+        "gumbel_softmax_temperature": 0.1
+      },
+      "temperature_0.167": {
+        "gumbel_softmax_temperature": 0.167
+      },
+      "temperature_0.278": {
+        "gumbel_softmax_temperature": 0.278
+      },
+      "temperature_0.464": {
+        "gumbel_softmax_temperature": 0.464
+      },
+      "temperature_0.774": {
+        "gumbel_softmax_temperature": 0.774
+      },
+      "temperature_10": {
+        "gumbel_softmax_temperature": 10
+      },
+      "temperature_1.29": {
+        "gumbel_softmax_temperature": 1.29
+      },
+      "temperature_2.15": {
+        "gumbel_softmax_temperature": 2.15
+      },
+      "temperature_3.59": {
+        "gumbel_softmax_temperature": 3.59
+      },
+      "temperature_5.99": {
+        "gumbel_softmax_temperature": 5.99
+      }
+    }
+  }
+}

systems/rlupus/metadata.yml

@@ -1,4 +1,5 @@
 origin:
+  name: rlupus
   source: https://github.com/brendon-boldt/rl_werewolf
   upstream_source: https://github.com/nicofirst1/rl_werewolf
   paper: https://arxiv.org/abs/2106.05018

systems/rlupus/system.json

@@ -1 +1,58 @@
-[{"origin":{"source":"https://github.com/brendon-boldt/rl_werewolf","upstream_source":"https://github.com/nicofirst1/rl_werewolf","paper":"https://arxiv.org/abs/2106.05018"},"system":{"game_type":"conversation","game_subtype":"social_deduction","observation_type":"vector","observation_continuous":false,"multi_step":true,"data_source":null,"seeding_available":false,"symmetric_agents":true,"more_than_2_agents":true,"multi_utterance":true,"variants":{"9-player.run-0":{"message_length":9,"vocab_size":9,"note":"reached 0.88 WR (win rate) in 38 hours (no automatic stopping)"},"9-player.run-1":{"message_length":9,"vocab_size":9,"note":"reached 0.44 WR, stopped at 48 hours"},"9-player.run-2":{"message_length":9,"vocab_size":9,"note":"reached 0.44 WR, stopped at 48 hours"},"9-player.run-3":{"message_length":9,"vocab_size":9,"note":"reached 0.44 WR, stopped at 37 hours"},"21-player.run-0":{"message_length":21,"vocab_size":21,"note":"reached 0.88 WR in 34 hours (no automatic stopping)"},"21-player.run-1":{"message_length":21,"vocab_size":21,"note":"reached 0.55 WR, stopped at 48 hours"},"21-player.run-2":{"message_length":21,"vocab_size":21,"note":"reached 0.85 WR in 28 hours"}}},"notes":"This environment is somewhat unstable and does not provide random seeding, so reproducing exact results is tricky.  Nevertheless, environment converge about half of the time (i.e., reach 85% villager win rate before 48 hours of training). 9 player (~11M steps per hour). 21 player (~4M steps per hour).\n"}]
+{
+  "origin": {
+    "name": "rlupus",
+    "source": "https://github.com/brendon-boldt/rl_werewolf",
+    "upstream_source": "https://github.com/nicofirst1/rl_werewolf",
+    "paper": "https://arxiv.org/abs/2106.05018"
+  },
+  "system": {
+    "game_type": "conversation",
+    "game_subtype": "social_deduction",
+    "observation_type": "vector",
+    "observation_continuous": false,
+    "multi_step": true,
+    "data_source": null,
+    "seeding_available": false,
+    "symmetric_agents": true,
+    "more_than_2_agents": true,
+    "multi_utterance": true,
+    "variants": {
+      "9-player.run-0": {
+        "message_length": 9,
+        "vocab_size": 9,
+        "note": "reached 0.88 WR (win rate) in 38 hours (no automatic stopping)"
+      },
+      "9-player.run-1": {
+        "message_length": 9,
+        "vocab_size": 9,
+        "note": "reached 0.44 WR, stopped at 48 hours"
+      },
+      "9-player.run-2": {
+        "message_length": 9,
+        "vocab_size": 9,
+        "note": "reached 0.44 WR, stopped at 48 hours"
+      },
+      "9-player.run-3": {
+        "message_length": 9,
+        "vocab_size": 9,
+        "note": "reached 0.44 WR, stopped at 37 hours"
+      },
+      "21-player.run-0": {
+        "message_length": 21,
+        "vocab_size": 21,
+        "note": "reached 0.88 WR in 34 hours (no automatic stopping)"
+      },
+      "21-player.run-1": {
+        "message_length": 21,
+        "vocab_size": 21,
+        "note": "reached 0.55 WR, stopped at 48 hours"
+      },
+      "21-player.run-2": {
+        "message_length": 21,
+        "vocab_size": 21,
+        "note": "reached 0.85 WR in 28 hours"
+      }
+    }
+  },
+  "notes": "This environment is somewhat unstable and does not provide random seeding, so reproducing exact results is tricky.  Nevertheless, environment converge about half of the time (i.e., reach 85% villager win rate before 48 hours of training). 9 player (~11M steps per hour). 21 player (~4M steps per hour).\n"
+}