Leveraging Generative Agents: Autonomous AI with Simulated Personas for Interactive Simulacra and Collaborative Research

Abstract

The advent of large language models (LLMs) and AI learning have fundamentally reshaped the research landscape, paving the way for novel problem-solving approaches. This paper introduces a unique framework that leverages the capabilities of autonomous AI agents with simulated personas to drive collaborative research in groundbreaking ways. Inspired by a recent study of autonomous agents mirroring human behavior, this concept encourages the use of a cadre of AI agents, each possessing specialized expertise for collective endeavors. By replicating human diversity in teamwork, this approach targets complex and hitherto unsolva- ble issues. The key to this strategy is persona and emotional simulation, enabling these AI agents to facilitate cross- disciplinary and interdisciplinary research within a decentered author model, and providing innovative solutions to wicked problems. Expertise can be drawn upon from disparate fields, including STEM, business, education, arts and humanities, and more. Enhanced by the advancements in AI research, specifically with LLMs like OpenAI's ChatGPT 3.5 and 4, this model offers profound potential to nurture research culture within universities by identifying barriers and proposing strategies to surmount them, drawing from international models for inspiration. This proposed decentered collaborative research model, despite con- straints, holds immense promise in reinventing the research paradigm.