# Participants

## 1. Task Creator

* Stakes and creates a FL task
* Specifies the basic information of a FL task, such as the number of minimum participants, the expected number of rounds, and the initial reward amount in the pool

## 2. FL Nodes

FL nodes are participants in a decentralised learning system where multiple entities collaboratively train a shared machine learning model without exchanging their local data. These nodes can be any devices or servers contributing computational resources and data to the training process.

FL nodes play critical roles in ensuring the integrity and efficiency of the FL Alliance working process. They are randomly allocated the roles of proposers and voters with the goal of avoiding collusion and other malicious behaviours. By distributing these roles randomly, the system ensures a fair and unbiased approach to model training and evaluation.

Specifically, developers join as FL nodes to collaboratively train a global model while using their local data and computing power. They are randomly allocated the following roles:

* **Proposers:** Responsible for performing local training using their own data and proposing updates to the global model.
* **Voters:** Responsible for aggregating local model updates, evaluating the global model, and casting votes to either support or oppose the proposed updates.


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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://docs.flock.io/flock-products/fl-alliance/participants.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.
