https://github.com/openai/gym-soccer

https://github.com/openai/gym-soccer

Last synced: about 16 hours ago
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• Host: GitHub
• URL: https://github.com/openai/gym-soccer
• Owner: openai
• Created: 2016-08-24T23:20:17.000Z (over 8 years ago)
• Default Branch: master
• Last Pushed: 2023-04-02T11:45:25.000Z (almost 2 years ago)
• Last Synced: 2025-02-03T12:59:13.218Z (8 days ago)
• Language: Python
• Size: 5.86 KB
• Stars: 303
• Watchers: 160
• Forks: 171
• Open Issues: 12
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

• awesome-deep-rl - OpenAI Gym Soccer - A multiagent domain featuring continuous state and action spaces. (Environments)

README

        
**Status:** Archive (code is provided as-is, no updates expected)

# gym-soccer

The [Soccer environment](https://github.com/LARG/HFO) 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

```bash

cd gym-soccer

pip install -e .

```