Jumanji

EnvPool provides native C++ batched implementations for the public task IDs in jumanji==1.1.2.

SearchAndRescue-v0 returns the sum of the searchers’ rewards as its scalar cooperative reward. Individual rewards are available in info["searcher_rewards"] with shape (num_envs, 2).

Note

Some existing Jumanji oracle fixtures load short state/reward trajectories for replay. Those checks cover replay and rendering compatibility, not arbitrary-action semantic alignment. Native rule and determinism tests run separately; full action-driven oracle coverage is still pending.

Render Compare

Representative reset-frame renders for all Jumanji tasks. Each panel shows EnvPool env.render() on the left and the pinned official jumanji==1.1.2 Matplotlib renderer on the right. The generation script resets the official oracle first, passes the supported reset-state fields into EnvPool, and writes the side-by-side comparison image from those synchronized reset states.

../_images/jumanji_official_compare.png

Options

  • task_id (str): see available tasks below;

  • num_envs (int): how many environments you would like to create;

  • batch_size (int): the expected batch size for return result, default to num_envs;

  • num_threads (int): the maximum thread number for executing the actual env.step, default to batch_size;

  • seed (int | Sequence[int]): the environment seed. When a sequence is provided, it must contain exactly one seed per environment. Default to 42;

  • max_episode_steps (int): the maximum number of steps for one episode.

Supported Tasks

  • BinPack-v2

  • CVRP-v1

  • Cleaner-v0

  • Connector-v3 (Connector-v2 remains as a compatibility alias)

  • FlatPack-v0

  • Game2048-v1

  • GraphColoring-v1

  • JobShop-v0

  • Knapsack-v1

  • LevelBasedForaging-v0

  • MMST-v0

  • Maze-v0

  • Minesweeper-v0

  • MultiCVRP-v0

  • PacMan-v1

  • RobotWarehouse-v0

  • RubiksCube-partly-scrambled-v0

  • RubiksCube-v0

  • SearchAndRescue-v0

  • SlidingTilePuzzle-v0

  • Snake-v1

  • Sokoban-v0

  • Sudoku-v0

  • Sudoku-very-easy-v0

  • TSP-v1

  • Tetris-v0

Example

import envpool

env = envpool.make_gymnasium("Sokoban-v0", num_envs=8, seed=0)
obs, info = env.reset()