Combined Arms

environment gif

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

Name Value
Actions Discrete
Agents 162
Parallel API True
Manual Control No
Action Shape (9),(25)
Action Values Discrete(9),(25)
Observation Shape (13,13,35), (13,13,51)
Observation Values [0,2]
Import pettingzoo.magent import combined_arms_v1
Agents agents= [redmelee_[0-44], redranged_[0-35], bluemelee_[0-44], blueranged_[0-35]]

Agent Environment Cycle

environment aec diagram

Combined Arms

A large-scale team battle. Here there are two types of agents on each team, ranged units which can attack father and move faster but have less HP, and melee units which can only attack close units and move more slowly but have more HP. Unlike battle and battlefield, agents can attack units on their own team (they just are not rewarded for doing so).

Melee action options: [do_nothing, move_4, attack_4]

Ranged action options: [do_nothing, move_12, attack_12]

Reward is given as:

If multiple options apply, rewards are added together

Observation space: [empty, obstacle, agent_maps, agent_minimaps, binary_agent_id(10), one_hot_action, last_reward, agent_position]

Map size: 45x45


combined_arms_v1.env(step_reward-0.01, dead_penalty=-0.1, attack_penalty=-1, attack_opponent_reward=2, max_frames=1000)

step_reward: reward added unconditionally

dead_penalty: reward added when killed

attack_penalty: reward added for attacking

attack_opponent_reward: Reward added for attacking an opponent

max_frames: number of frames (a step for each agent) until game terminates