https://github.com/opendilab/gobigger-challenge-2021
Interested in multi-agents? The 1st Go-Bigger Multi-Agent Decision Intelligence Challenge is coming and a big bonus is waiting for you!
https://github.com/opendilab/gobigger-challenge-2021
challenge gobigger gym reinforcement-learning
Last synced: 2 days ago
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Interested in multi-agents? The 1st Go-Bigger Multi-Agent Decision Intelligence Challenge is coming and a big bonus is waiting for you!
- Host: GitHub
- URL: https://github.com/opendilab/gobigger-challenge-2021
- Owner: opendilab
- License: apache-2.0
- Created: 2021-10-08T08:03:29.000Z (about 4 years ago)
- Default Branch: main
- Last Pushed: 2022-10-09T03:23:23.000Z (about 3 years ago)
- Last Synced: 2025-03-31T23:51:07.626Z (7 months ago)
- Topics: challenge, gobigger, gym, reinforcement-learning
- Language: Python
- Homepage:
- Size: 58 MB
- Stars: 194
- Watchers: 4
- Forks: 33
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# GoBigger Challenge 2021
[en](https://github.com/opendilab/GoBigger-Challenge-2021/blob/main/README.md) / [中文](https://github.com/opendilab/GoBigger-Challenge-2021/blob/main/README_zh.md)
Do you remember the game named Feeding Frenzy? Here comes the Decision Intelligence version of the Feeding Frenzy —— AI BOB: Go-Bigger Multi-Agent Decision Intelligence Challenge!
What’s more, this competition is open to technology developers and students worldwide.
In this competition, your team needs to develop an intelligent agent to "eat" as many enemies as possible, to make your intelligent agent more powerful. Briefly, the stronger the intelligent agent, the higher the score.
Teamwork is essential to win this competition. You need to cooperate perfectly with your teammates to work out a strategy for the championship and you will experience the law of the jungle in the game.
We are looking forward to your brilliant performance in this challenge!
## Outline
* [Challenge Introduction](#challenge-introduction)
* [Task in Challenge](#task-in-challenge)
* [Submission](#submission)
* [Submission based on DI-engine](#submission-base-on-di-engine)
* [Try your first submission](#try-your-first-submission)
* [Resources](#resources)
* [Join and Contribute](#join-and-contribute)
* [License](#license)
## Challenge Introduction
Multi-agent confrontation is an important part of decision intelligence AI, and it is also a very challenging problem. In order to enrich the multi-agent confrontation environment, OpenDILab has developed a multi-agent confrontation competitive game named GoBigger. Based on GoBigger, the purpose of this challenge is to explore the research of multi-agent games and promote the training of technical talents in the fields of decision intelligence to create a "global leading", "original" and "open" decision intelligence AI open-source technology ecosystem.
This challenge needs competitors to submit their agents. We will return the score for agents to help competitors have a more accurate understanding of the performance of the submitted agent. At the end of the challenge, we will thoroughly test all submissions and the final ranking of the participating teams will be conducted.
## Task in Challenge
This challenge uses [Go-Bigger](https://github.com/opendilab/GoBigger) as the game environment. Go-Bigger is a multi-players competitive environment. For more details, please refer to the Go-Bigger documentation. In the match, each team participating in the challenge controls one team in the game (each team consists of multiple players). Contest participating teams need to submit an agent to control a certain team in the match and the players it contains and obtain higher scores through teamwork, thereby achieving a higher ranking in the match.
## Submission
Here in [submit](https://github.com/opendilab/GoBigger-Challenge-2021/blob/main/submit), we provide examples of submissions for all teams in our challenge. We also offer [BaseSubmission](https://github.com/opendilab/GoBigger-Challenge-2021/blob/main/submit/base_submission.py), and participants should implements their own submissions based on the code.
```python
class BaseSubmission:
def __init__(self, team_name, player_names):
self.team_name = team_name
self.player_names = player_names
def get_actions(self, obs):
'''
Overview:
You must implement this function.
'''
raise NotImplementedError
```
Note that all submission should extend with `BaseSubmission`. We will provide `team_name` and `player_names` for each submission as their basic parameters. `team_names` means the name of team that this submission controls. We also know that several players in a team are relative to the `player_names` in the parameters. We will call `get_actions()` when we try to get actions from this submission. So that participants should implement `get_actions()` in their submission. This function will receive `obs` as its parameters, similar to what we provide in the [tutorial](https://gobigger.readthedocs.io/en/latest/tutorial/space.html#observation-space). For example, submissions will get `obs` as follows:
```python
global_state, player_state = obs
```
`global_state` in detail:
```python
{
'border': [map_width, map_height], # the map size
'total_time': match_time, # the duration of a game
'last_time': last_time, # the length of time a game has been played
'leaderboard': {
team_name: team_size
} # the team with its size in this game
}
```
Participants can find their `team_name` in submission matched with the `team_name` in the `leaderboard`.
`player_state` in detail:
```
{
player_name: {
'feature_layers': list(numpy.ndarray), # features of player
'rectangle': [left_top_x, left_top_y, right_bottom_x, right_bottom_y], # the vision's position in the map
'overlap': {
'food': [[position.x, position.y, radius], ...],
'thorns': [[position.x, position.y, radius], ...],
'spore': [[position.x, position.y, radius], ...],
'clone': [[[position.x, position.y, radius, player_name, team_name], ...],
}, # all balls' info in vision
'team_name': team_name, # the team which this player belongs to
}
}
```
However, we will only provide the submission with the `player_state` matched with its players. That means, if `player_a` and `player_b` (both are player names) are in the team that belongs to this submission, and `player_c` does not belong to this team, participants will only get `player_a` and `player_b` in the submission.
After getting the `obs`, submissions should return `actions` in `get_actions()`. `actions` should look like this:
```python
{
player_a: actions_a,
player_b: actions_b
}
```
Remember that both `player_a` and `player_b` should be the name in your submission's `player_names`. And `actions_a` should be a list that contains their items, which are the same as what we propose in [action-space](https://gobigger.readthedocs.io/en/latest/tutorial/space.html#action-space).
### Examples and Test
We provide [RandomSubmission](https://github.com/opendilab/GoBigger-Challenge-2021/blob/main/submit/random_submission.py) and [BotSubmission](https://github.com/opendilab/GoBigger-Challenge-2021/blob/main/submit/bot_submission.py). `RandomSubmission` provide actions randomly, and `BotSubmission` provide actions based on a script. Both of them could be an example of your submission. See more details in the code.
We also provide an example for the pipeline of the submission. Please refer to [submission_example](https://github.com/opendilab/GoBigger-Challenge-2021/blob/main/submit/submission_example/) for more details. You can also develop your agent in this directory. Once you finish your `my_submission.py`, you can call `python -u test.py` to check your submission and finally get the `.tar.gz` file to upload.
### Supplements
If you want to add other things to your submissions, such as model checkpoints or other materials, please place them in `./supplements` and tar them with submission.
### Finally
You should place all your code and materials under `my_submission/`. Use `tar zcf submission.tar.gz my_submission/` to get your final submission files. The final `submission.tar.gz` should be:
```
- my_submission
| - __init__.py
| - requirements.txt
| - my_submission.py
| - supplements/
| - checkpoints or other materials
```
Attention: `__init__.py` should be an empty file.
## Submission based on DI-engine
We also develop [submission_example_di](https://github.com/opendilab/GoBigger-Challenge-2021/blob/main/di_baseline/) based on [DI-engine](https://github.com/opendilab/DI-engine). You can place your ckpt in supplements to get a completed submission.
## Try your first submission
Maybe you are not very familiar with our competition but don't worry; we provide the simplest case submission! Try the following code to quickly generate a `my_submission.tar.gz` for submission!
```
$ cd submit/submission_example
$ python -u test.py
```
The above `test.py` will check whether your submission is correct. If it is correct, you will get the following output:
```
Success!
###################################################################
# #
# Now you can upload my_submission.tar.gz as your submission. #
# #
###################################################################
```
Now you only need to submit your `my_submission.tar.gz`!
* Note: This submission is made of a random policy. You can check the code and change the policy to get better performance.
## Resources
* Challenge Settings: [en](https://github.com/opendilab/GoBigger-Challenge-2021/blob/main/challenge_settings.md) / [中文](https://github.com/opendilab/GoBigger-Challenge-2021/blob/main/challenge_settings_zh.md)
* Evaluation: [en](https://github.com/opendilab/GoBigger-Challenge-2021/blob/main/evaluation.md) / [中文](https://github.com/opendilab/GoBigger-Challenge-2021/blob/main/evaluation_zh.md)
## Join and Contribute
Welcome to OpenDI Lab GoBigger community! Scan the QR code and add us on Wechat:
Or you can contact us with [slack](https://opendilab.slack.com/join/shared_invite/zt-v9tmv4fp-nUBAQEH1_Kuyu_q4plBssQ#/shared-invite/email) or email (opendilab@pjlab.org.cn).
## License
GoBigger-Challenge-2021 was released under the Apache 2.0 license.