Simulation of Language Evolution under Regulated Social Media Platforms: A Synergistic Approach of Large Language Models and Genetic Algorithms

This paper introduces a multi-agent framework that combines Large Language Models (LLMs) with Genetic Algorithms (GAs) to simulate language evolution in response to regulatory constraints on social media platforms. The framework allows agents to iteratively adapt their language strategies, with evaluations conducted in both abstract and realistic scenarios, showing significant improvements in dialogue continuity and information accuracy as interactions progress. This research highlights the potential for using LLMs and GAs to understand and model adaptive communication strategies in regulated environments, which is crucial for practitioners developing AI systems that operate within such constraints.