Warlords#

This environment is part of the Atari environments. Please read that page first for general information.

Import	`from pettingzoo.atari import warlords_v3`
Actions	Discrete
Parallel API	Yes
Manual Control	No
Agents	`agents= ['first_0', 'second_0', 'third_0', 'fourth_0']`
Agents	4
Action Shape	(1,)
Action Values	[0,5]
Observation Shape	(210, 160, 3)
Observation Values	(0,255)

Four player last man standing!

Defend your fortress from the ball and hit it towards your opponents.

When your fortress falls, you receive -1 reward and are done. If you are the last player standing, you receive +1 reward.

Official wizard_of_wor manual

Environment parameters#

Environment parameters are common to all Atari environments and are described in the base Atari documentation .

Action Space (Minimal)#

In any given turn, an agent can choose from one of 6 actions.

Action	Behavior
0	No operation
1	Fire
2	Move up
3	Move right
4	Move left
5	Move down

Version History#

v3: Minimal Action Space (1.18.0)
v2: Breaking changes to entire API (1.4.0)
v1: Fixes to how all environments handle premature death (1.3.0)
v0: Initial versions release (1.0.0)

Usage#

AEC#

from pettingzoo.atari import warlords_v3

env = warlords_v3.env(render_mode="human")
env.reset(seed=42)

for agent in env.agent_iter():
    observation, reward, termination, truncation, info = env.last()

    if termination or truncation:
        action = None
    else:
        # this is where you would insert your policy
        action = env.action_space(agent).sample()

    env.step(action)
env.close()

Parallel#

from pettingzoo.atari import warlords_v3

env = warlords_v3.parallel_env(render_mode="human")
observations, infos = env.reset()

while env.agents:
    # this is where you would insert your policy
    actions = {agent: env.action_space(agent).sample() for agent in env.agents}

    observations, rewards, terminations, truncations, infos = env.step(actions)
env.close()

API#

class pettingzoo.atari.warlords.warlords.raw_env(**kwargs)[source]#