FlockVote: LLM-Driven Simulations of US Presidential Elections

The research, as presented on ArXiv, explores the application of Large Language Models (LLMs) in agent-based modeling to simulate US presidential elections. The success and validity of the simulations depend on the underlying data quality, model accuracy, and the degree of real-world complexity captured by the agent interactions.

• •FlockVote utilizes LLMs to create agent-based models for simulating US presidential elections.
• •The research's primary source is a paper available on ArXiv.
• •The paper explores the potential of LLMs in political science simulation.