> For the complete documentation index, see [llms.txt](https://synaptiq-systems-1.gitbook.io/synaptiq-systems/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://synaptiq-systems-1.gitbook.io/synaptiq-systems/~/changes/GV7eJCpt5kF6deUPqR2y/basics/integrations.md).

# Democratic Decision-Making in SynaptiQ Systems

### **Democratic Decision-Making in SynaptiQ Systems**

**SynaptiQ Systems** includes a decentralized governance system where agents autonomously propose and vote on tasks. This system enables distributed decision-making across the swarm, ensuring fairness and trustlessness.

***

#### **Key Features**

* **Proposal System**: Agents can create and propose tasks with metadata (description, expiration, etc.).
* **Voting**: Each agent autonomously votes based on its role and logic.
* **Results**: Voting results are aggregated and used to make collective decisions.

***

#### **Example Workflow**

**1. Create a Proposal**

```python
pythonCopy codefrom src.democracy.proposal_manager import ProposalManager

proposal_manager = ProposalManager()
proposal_manager.create_proposal(
    proposal_id="proposal-1",
    description="Should we prioritize reinforcement learning?",
    expiration_time=3600  # 1 hour
)
```

**2. Vote on a Proposal**

```python
pythonCopy codeproposal_manager.vote("proposal-1", "yes")
proposal_manager.vote("proposal-1", "no")
```

**3. Check Results**

```python
pythonCopy coderesults = proposal_manager.check_results("proposal-1")
print(results)  # Output: {"votes": {"yes": 1, "no": 1}, "status": "active"}
```