Behavior-Driven Marine Larval Dispersal and Settlement with AI Agent-Based Modeling
The paper introduces SWARM, an AI agent-based modeling framework that integrates Large Language Models with biophysical simulations to overcome the limitations of static dispersal models by enabling Red Snapper larvae to exhibit adaptive behaviors, thereby improving the prediction of marine connectivity and informing ecosystem restoration strategies.