# Welcome to FUXI-UP-Challenges

## Who are we?

We are the UP (i.e., user persona) group of FUXI (sound as /foo shee/) AI Lab, NetEase Games (<https://fuxi.163.com/en/>). Our research focus broadly ranges from bot detection, game matchmaking, personalized recommendation, user growth analysis, and many other related topics. Many successful and innovative efforts have been deployed into a variety of online practical scenarios in online games of NetEase and other game manufacturers. A more detailed introduction (in Chinese, English version is coming soon) can be referred to this URL (<https://fuxi-up-research.gitbook.io/open-project/>)

## About challenges

We collect many interesting and valuable research topics and relevant datasets from different scenarios in online Games. In order to encourage the talented from both academic and industrial spheres to join the meaningful problem-solving procedure, we set up a lot of open data challenges attached with awards or fast-track recruit offers.

## Challenge List

{% content-ref url="challenge/bigdatacup2021-rl4rs-challenge" %}
[bigdatacup2021-rl4rs-challenge](https://fuxi-up-research.gitbook.io/fuxi-up-challenges/challenge/bigdatacup2021-rl4rs-challenge)
{% endcontent-ref %}

## About datasets

Aligning with challenges, these excellent participants and us also explore the performance of current SOTA methods on some specific tasks. Therefore we collect these tasks, data and metrics included, and the corresponding baselines to build a lot of benchmarks.

## Datasets List

{% content-ref url="dataset/rl4rs" %}
[rl4rs](https://fuxi-up-research.gitbook.io/fuxi-up-challenges/dataset/rl4rs)
{% endcontent-ref %}


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://fuxi-up-research.gitbook.io/fuxi-up-challenges/readme.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.