Datasets:

machinaExMachina
/

duet-pcg-v1

Tasks:

Video Classification

Reinforcement Learning

Tags:

minecraft

multiworld

procedural-generation

out-of-view

world-model

solaris

License:

Dataset card Files Files and versions

xet

Community

Dataset Viewer

The dataset viewer is not available for this subset.

Cannot get the split names for the config 'default' of the dataset.

Exception:    SplitsNotFoundError
Message:      The split names could not be parsed from the dataset config.
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
                  for split_generator in builder._split_generators(
                                         ^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 82, in _split_generators
                  raise ValueError(
              ValueError: The TAR archives of the dataset should be in WebDataset format, but the files in the archive don't share the same prefix or the same types.
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 65, in compute_split_names_from_streaming_response
                  for split in get_dataset_split_names(
                               ^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
                  info = get_dataset_config_info(
                         ^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
                  raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
              datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.

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MultiWorld Duet PCG v1

2-player procedural-generation Minecraft gameplay dataset. Companion to duet-oov-scripted-v1 with added world + task diversity for the MultiWorld paper.

Overview

Episodes: ~1,700 (3,400+ player streams)
Format: Solaris-compatible sharded WebDataset TARs
Resolution: 1280×720 @ 20 FPS
World diversity: 20 config combos × mixed flat/normal worlds × 5 biomes (plains, snowy_plains, desert, badlands, mushroom_fields)
Task diversity: 10 episode types (4 new PCG templates + 6 Phase 1 OOV scenarios)
Server: Minecraft 1.21 (Paper)

Why this dataset exists

Phase 1 (duet-oov-scripted-v1) established the core OOV scenarios on flat plains worlds. Phase 2 adds world and task diversity: scenarios run across different biomes (including non-flat vanilla terrain) with procedurally varied parameters. The goal is scenario breadth, not raw frame count — per the MultiWorld data plan, "scenario diversity, not raw frame count, drives generalization for the consistency story."

New PCG Task Templates

Four new task-template episode handlers added in Phase 2. Each has procedural parameters drawn from a shared per-episode PRNG seed so both bots make consistent decisions independently.

Scenario	Description	OOV Type
gatherScatter	Separate to regions (40–120 b), mine 3–8 blocks each, rejoin	Decoupled resource gathering
exploreReunite	Explore opposite directions with 2–4 look-around stops, hold OOV, return	Terrain exploration
mobHuntReunite	Spawn mobs at two distant sites (30–80 b), each bot interacts with own mobs, reunite	Mob-interaction asymmetry
buildExchange	Scatter + build (tower/wall/platform/staircase, size 2–5), swap to inspect other's build	Structural variety

Phase 1 Scenarios Also Included

All six Phase 1 OOV scenarios run in Phase 2 with the added world diversity: splitAndRejoin, throughTheWall, farApartBuild, asymmetricInformation, jointWitnessReunite, sharedBuildReunite.

World Configurations

The PCG manifest (pcg/production_manifest.json) defines 20 configurations, each with:

World seed — deterministic from config index via MD5 salt
World type — flat (8 configs) or normal (12 configs, vanilla biome generation)
Biome (flat worlds) — one of plains, snowy_plains, desert, badlands, mushroom_fields
Episode type mix — random 3–6 types sampled from the 10-scenario pool

File structure

Same as duet-oov-scripted-v1:

train/<prefix>_<episode>_Alpha_instance_<i>.mp4
train/<prefix>_<episode>_Alpha_instance_<i>.json
train/<prefix>_<episode>_Alpha_instance_<i>_episode_info.json
train/<prefix>_<episode>_Bravo_instance_<i>.mp4
train/<prefix>_<episode>_Bravo_instance_<i>.json
train/<prefix>_<episode>_Bravo_instance_<i>_episode_info.json

episode_info.json includes per-scenario eval_metadata (distances, durations, structure types, mob types, etc.) drawn from the episode's PRNG plan.

Usage

Compatible with the Solaris training pipeline. Extract shards:

for f in *.tar; do tar xf "$f"; done