We use vizdoom==1.1.13 as the codebase. See

Env Wrappers

Currently it includes these wrappers: frame-skip / episodic-life / action-repeat / image-resize / reward-config.


  • 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): the environment seed, default to 42;

  • max_episode_steps (int): the maximum number of steps for one episode, default to 525;

  • img_height (int): the desired observation image height, default to 84;

  • img_width (int): the desired observation image width, default to 84;

  • stack_num (int): the number of frames to stack for a single observation, default to 4;

  • frame_skip (int): the number of frames to execute one repeated action, only the last frame would be kept, default to 4;

  • use_inter_area_resize (bool): whether to use cv::INTER_AREA for image resize, default to True;

  • episodic_life (bool): make end-of-life == end-of-episode, but only reset on true game over. It helps the value estimation. Default to False;

  • use_combined_action (bool): whether to use a discrete action space as action input (for doom game engine), see Action Space, default to False (use raw action space);

  • force_speed (bool): if SPEED button is available, press it in every frame. Only available when using combined action. Default to False;

  • lmp_save_dir (str): the directory to save .lmp files for recording and replay (see tests/vizdoom/, default to "" (no lmp saving);

  • vzd_path (str): the vizdoom binary path, default to vizdoom/bin/vizdoom;

  • cfg_path (str): the .cfg file path, used in customized env setup, default to "";

  • wad_path (str): the .wad file path, used in customized env setup, default to "";

  • iwad_path (str): the rendering resource package path, default to vizdoom/bin/freedoom2;

  • map_id (str): the vizdoom map id, see setDoomMap, available options are "map01", "map02", ..., default to "map01";

  • game_args (str): the args string for vizdoom game, see addGameArgs, default to "";

  • reward_config (Dict[str, Tuple[float, float]]): how to calculate the reward (see below), default to {"FRAGCOUNT": [1, -1.5], "KILLCOUNT": [1, 0], "DEATHCOUNT": [-0.75, 0.75], "HITCOUNT": [0.01, -0.01], "DAMAGECOUNT": [0.003, -0.003], "HEALTH": [0.005, -0.003], "ARMOR": [0.005, -0.001], "AMMO2": [0.0002, -0.0001]};

The original vizdoom env calculates reward with only living reward and death penalty. Our preliminary result shows these two reward have negative effect on agent training. Instead, other reward related to some game variable is very useful. You can pass various reward config into vizdoom env. Each item in this dictionary has format of NAME: [pos_reward, neg_reward]. If we take HEALTH: [pos_health, neg_health] as an example:

delta = current[HEALTH] - last[HEALTH]
if delta >= 0:
    reward += delta * pos_health
    reward -= delta * neg_health

where last[*] is the corresponding value at the last timestep.

  • weapon_duration see below, default to 5;

  • selected_weapon_reward_config (Dict[int, float]): the available keys are 2 / 3 / ... / 7, it means if the agent holds i``th weapon for at least ``weapon_duration timestep, the reward will be added by selected_weapon_reward_config[i];

  • delta_button_config (Dict[str, Tuple[int, float, float]]): see Action Space.

Customized VizDoom Env

Use VizdoomCustom-v1 with cfg_path and wad_path:

env = envpool.make(

Observation Space

The observation channel number is defined in configuration file (e.g., GRAY8 or CRCGCB).

The game variables defined in configuration file are in observation (dm) / are in info (gym). Each variable tags a key. Currently it includes: "AMMO2", "AMMO3", "AMMO4", "AMMO5", "AMMO6", "AMMO7", "ARMOR", "DAMAGECOUNT", "DEATHCOUNT", "FRAGCOUNT", "HEALTH", "HITCOUNT", "KILLCOUNT", "SELECTED_WEAPON", "SELECTED_WEAPON_AMMO", "USER2"

Action Space

If use_combined_action is set to False, it only accepts the original action input (which is a list of float); otherwise:

All of the buttons are in discrete space, including delta button. In EnvPool we directly generate the combo action with the following rule:

  1. Each time the agent can only select at most one weapon

    • can only select at most one of SELECT_WEAPON0SELECT_WEAPON9 buttons

  2. Some buttons are pair-wised, they cannot be selected together (FF, TF, FT)


  3. Other non-delta buttons have two choices: F or T

  4. For delta buttons, the given delta_button_config specifies how it builds the action set (with format [num, min, max]). For example, if we pass delta_button_config={"TURN_LEFT_RIGHT_DELTA": [4, -2.0, 1.0]}, it will build TURN_LEFT_RIGHT_DELTA = [-2.0, -1.0, 0.0, 1.0] 4 discrete choices.

For example, if we have MOVE_FORWARD, TURN_LEFT and TURN_RIGHT three buttons (which is exactly health-gathering setting), we have 2x3=6 discrete actions according the above rule.

Available Tasks

  • Basic-v1

  • Cig-v1

  • D1Basic-v1

  • D2Navigation-v1

  • D3Battle-v1

  • D4Battle2-v1

  • DeadlyCorridor-v1

  • Deathmatch-v1

  • DefendTheCenter-v1

  • DefendTheLine-v1

  • HealthGathering-v1

  • HealthGatheringSupreme-v1

  • MultiDuel-v1

  • MyWayHome-v1

  • PredictPosition-v1

  • RocketBasic-v1

  • SimplerBasic-v1

  • TakeCover-v1

  • VizdoomCustom-v1