Persona-based Multi-Agent Collaboration for Brainstorming

TL;DR

This paper introduces a framework for persona-based multi-agent collaboration in brainstorming, demonstrating how different agent personas and collaboration modes enhance idea diversity, depth, and cross-domain coverage.

Contribution

It proposes a novel persona-based agent selection framework that improves brainstorming outcomes through curated persona domains and varied collaboration dynamics.

Findings

Persona choice influences idea domains.

Collaboration mode affects idea diversity.

Multi-agent persona-driven brainstorming enhances idea depth and coverage.

Abstract

We demonstrate the importance of persona-based multi-agents brainstorming for both diverse topics and subject matter ideation. Prior work has shown that generalized multi-agent collaboration often provides better reasoning than a single agent alone. In this paper, we propose and develop a framework for persona-based agent selection, showing how persona domain curation can improve brainstorming outcomes. Using multiple experimental setups, we evaluate brainstorming outputs across different persona pairings (e.g., Doctor vs VR Engineer) and A2A (agent-to-agent) dynamics (separate, together, separate-then-together). Our results show that (1) persona choice shapes idea domains, (2) collaboration mode shifts diversity of idea generation, and (3) multi-agent persona-driven brainstorming produces idea depth and cross-domain coverage.