gym-soccer

by openai

openai / gym-soccer
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Status: Archive (code is provided as-is, no updates expected)

gym-soccer

The Soccer environment is a multiagent domain featuring continuous state and action spaces. Currently, several tasks are supported:

Soccer

The soccer task initializes a single offensive agent on the field and rewards +1 for scoring a goal and 0 otherwise. In order to score a goal, the agent will need to know how to approach the ball and kick towards the goal. The sparse nature of the goal reward makes this task very difficult to accomplish.

SoccerEmptyGoal

The SoccerEmptyGoal task features a more informative reward signal than the Soccer task. As before, the objective is to score a goal. However, SoccerEmtpyGoal rewards the agent for approaching the ball and moving the ball towards the goal. These frequent rewards make the task much more accessible.

SoccerAgainstKeeper

The objective of the SoccerAgainstKeeper task is to score against a goal keeper. The agent is rewarded for moving the ball towards the goal and for scoring a goal. The goal keeper uses a hand-coded policy developed by the Helios RoboCup team. The difficulty in this task is learning how to shoot around the goal keeper.

Installation

cd gym-soccer
pip install -e .

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