SynaptiQ Systems
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    • SwarmConsensus: Collaborative Decision-Making in SynaptiQ Systems
    • Dynamic Breeding in SynaptiQ Systems
    • Democratic Decision-Making in SynaptiQ Systems
  • Multi-Agent Collaboration in SynaptiQ Systems
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SwarmConsensus: Collaborative Decision-Making in SynaptiQ Systems

SwarmConsensus: Collaborative Decision-Making in SynaptiQ Systems

SwarmConsensus is a core feature of SynaptiQ Systems that enables collaborative decision-making among agents. It supports both small-scale and large-scale swarms with the following methods:

  • Basic Redis Methods: Ideal for small swarms with straightforward task delegation.

  • Advanced Lua and Transactional Methods: Designed for larger, more complex swarms requiring atomicity and performance optimization.


Basic Methods for Small Swarms

1. Propose a Task

Agents can propose tasks using a simple Redis-backed counter.

pythonCopy codeproposal_id = swarm.propose_task("Analyze data trends")

2. Vote for a Task

Each agent can vote on proposals using Redis hash operations.

pythonCopy codeswarm.vote(proposal_id)

3. Retrieve Consensus

Consensus is reached when a task receives a threshold number of votes.

pythonCopy codeconsensus = swarm.get_consensus()
print(consensus)

Advanced Methods for Larger Swarms

For larger swarms or high-concurrency scenarios, SwarmConsensus provides enhanced functionality using Lua scripts and Redis transactions:

1. Propose a Task with Lua

Lua ensures atomic task proposal operations, minimizing race conditions.

pythonCopy codeproposal_id = swarm.propose_task_with_lua("Optimize blockchain transaction flow")

2. Vote with Redis Transactions

Transactions ensure that voting operations are executed atomically, even under high concurrency.

pythonCopy codeswarm.vote_with_transaction(proposal_id)

3. Consensus via Lua

For large datasets or frequent voting, Lua scripts streamline consensus checks.

pythonCopy codeconsensus = swarm.get_consensus_with_lua(threshold=5)
print(consensus)

When to Use Each Method

Method

Use Case

Basic Methods

Small swarms with simple task delegation.

Lua Scripts

Atomic task proposals and high-frequency voting.

Redis Transactions

High-concurrency voting in large swarms.


Example Workflow

Here’s a step-by-step workflow for using the SwarmConsensus module:

1. Propose a Task

pythonCopy codeproposal_id = swarm.propose_task_with_lua("Conduct AI-powered simulations")

2. Vote on a Task

pythonCopy codeswarm.vote_with_transaction(proposal_id)

3. Check Consensus

pythonCopy codeconsensus = swarm.get_consensus_with_lua(threshold=3)
if consensus:
    print("Consensus reached:", consensus)
else:
    print("No consensus reached yet.")

Key Notes

  • Use basic methods for lightweight operations and testing.

  • For production environments or large-scale swarms:

    • Leverage Lua scripts for atomicity and optimized performance.

    • Use Redis transactions to ensure data consistency under high concurrency.

  • Configure the consensus threshold based on your swarm size and requirements.

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Last updated 5 months ago