multi agent voting pattern

Imagine you're a busy beekeeper, responsible for collecting nectar from various flowers in the Apiary hive. You have multiple bees, each capable of flying to different locations, but only one can collect nectar at any given time. However, what if there were a way to dispatch multiple bees to the same location and let them vote on whether it's safe to return with nectar? This is where the multi-agent voting pattern comes in – a technique for distributed decision-making among multiple agents.

The Technique

The multi-agent voting pattern involves dispatching N agents (in this case, our bees) to perform the same task. Each agent gathers information and votes on whether to proceed or not. A simple majority wins, but what happens when there's a tie? This is where the judge agent comes in – an additional agent that ensures decisions are made even in cases of equality.

// Agent class for bees
class Bee {
  constructor(public id: number) {}

  vote(task: string): boolean {
    // Simulate bee decision-making process
    return Math.random() > 0.5;
  }
}

// Judge agent class
class JudgeAgent extends Bee {
  votes: { [key: number]: boolean[] };

  constructor(nAgents: number) {
    super(0);
    this.votes = {};
    for (let i = 1; i <= nAgents; i++) {
      this.votes[i] = [];
    }
  }

  castVote(agentId: number, vote: boolean): void {
    this.votes[agentId].push(vote);
  }

  decide(): string {
    const votes = Object.values(this.votes).flat();
    if (votes.filter((vote) => vote === true).length > votes.length / 2) {
      return 'Proceed';
    } else if (
      votes.filter((vote) => vote === false).length > votes.length / 2
    ) {
      return 'Do not proceed';
    } else {
      // Tie, let the judge decide
      const majority = votes.filter((vote) => vote === true);
      return majority.length >= votes.length / 2 ? 'Proceed' : 'Do not proceed';
    }
  }
}

Concrete Examples

Let's consider three scenarios where the multi-agent voting pattern can be applied:

Example 1: Resource allocation

Suppose we have multiple agents (bees) competing for resources at a flower. Each bee must decide whether to collect nectar from that flower or not. If more than half of the bees vote to collect nectar, the resource is allocated accordingly.

const nBees = 10;
const judgeAgent = new JudgeAgent(nBees);

for (let i = 1; i <= nBees; i++) {
  const bee = new Bee(i);
  if (bee.vote('nectar')) {
    judgeAgent.castVote(bee.id, true);
  } else {
    judgeAgent.castVote(bee.id, false);
  }
}

console.log(judgeAgent.decide()); // Output: Proceed or Do not proceed

Example 2: Task execution

In this example, multiple agents are dispatched to perform the same task. If more than half of them vote to execute the task, it's executed.

const nBees = 10;
const judgeAgent = new JudgeAgent(nBees);

for (let i = 1; i <= nBees; i++) {
  const bee = new Bee(i);
  if (bee.vote('task')) {
    judgeAgent.castVote(bee.id, true);
  } else {
    judgeAgent.castVote(bee.id, false);
  }
}

console.log(judgeAgent.decide()); // Output: Execute or Do not execute

Example 3: Conflict resolution

Suppose multiple agents are in conflict over a particular task. The multi-agent voting pattern can help resolve the issue by letting the majority decide.

const nBees = 10;
const judgeAgent = new JudgeAgent(nBees);

for (let i = 1; i <= nBees; i++) {
  const bee = new Bee(i);
  if (bee.vote('conflict')) {
    judgeAgent.castVote(bee.id, true);
  } else {
    judgeAgent.castVote(bee.id, false);
  }
}

console.log(judgeAgent.decide()); // Output: Resolve conflict or Do not resolve

When NOT to Use It

While the multi-agent voting pattern is a powerful technique for distributed decision-making, there are cases where it might not be suitable:

• Small number of agents: If there are only a few agents involved in the decision-making process, the overhead of implementing a voting mechanism might outweigh its benefits.
• Simple decisions: For straightforward decisions that can be made by a single agent, introducing a voting mechanism would add unnecessary complexity.
• Real-time constraints: In situations where real-time responsiveness is crucial, the delay introduced by the voting process could be detrimental.

Related Apiary Lessons

• Distributed decision-making: This lesson explores other techniques for distributed decision-making, including leader election and consensus protocols.
• Agent-based modeling: Learn how to model complex systems using agents and simulate their behavior.

Conclusion

The multi-agent voting pattern is a versatile technique for distributed decision-making among multiple agents. By dispatching multiple agents to perform the same task, letting them vote on whether to proceed or not, and handling ties with a judge agent, this pattern can help resolve conflicts and make decisions in complex systems. Remember, as a beekeeper, you're not just collecting nectar – you're also navigating the intricacies of distributed decision-making.

As the sun sets over the Apiary hive, remember: "A single bee's voice may be soft, but a chorus of many can move mountains."