Combat Task 介绍

Combat Task（对抗任务）CommNet

 

We simulate a simple battle involving two opposing teams in a 15 * 5 grid as shown in Fig. 2(middle).
Each team consists of m = 5 agents and their initial positions are sampled uniformly in a 5 * 5
square around the team center, which is picked uniformly in the grid. At each time step, an agent can
perform one of the following actions: move one cell in one of four directions; attack another agent
by specifying its ID j (there are m attack actions, each corresponding to one enemy agent); or do
nothing. If agent A attacks agent B, then B’s health point will be reduced by 1, but only if B is inside
the firing range of A (its surrounding 3 * 3 area). Agents need one time step of cooling down after
an attack, during which they cannot attack. All agents start with 3 health points, and die when their
health reaches 0. A team will win if all agents in the other team die. The simulation ends when one
team wins, or neither of teams win within 40 time steps (a draw).

 

 

The model controls one team during training, and the other team consist of bots that follow a hardcoded
policy. The bot policy is to attack the nearest enemy agent if it is within its firing range. If not,
it approaches the nearest visible enemy agent within visual range. An agent is visible to all bots if it
is inside the visual range of any individual bot. This shared vision gives an advantage to the bot team.
When input to a model, each agent is represented by a set of one-hot binary vectors fi; t; l; h; cg encoding its unique ID, team ID, location, health points and cooldown. A model controlling an agent
also sees other agents in its visual range (3 * 3 surrounding area). The model gets reward of -1 if the
team loses or draws at the end of the game. In addition, it also get reward of 􀀀0:1 times the total
health points of the enemy team, which encourages it to attack enemy bots.