Research Index

A novel framework combining LLM-based multi-agent systems with predictive battery thermal management for coordinating urban EV fleets. The system leverages natural language interaction for fleet operators while optimizing battery longevity and energy efficiency through distributed intelligence and real-time thermal management.

A novel system combining multi-agent LLMs and dynamic wireless power transfer to optimize real-time charging for autonomous EV fleets. The system uses predictive analytics to coordinate vehicle movements and charging infrastructure, while defending against potential cyber-attacks through secure multi-agent protocols.

A novel framework combining bio-inspired multi-agent systems with deep reinforcement learning for optimizing EV charging networks. The system uses MAS-GPT for agent coordination and implements nature-inspired optimization for both energy distribution and charging station placement, while considering real-time grid constraints and user behavior patterns.

A novel approach combining bio-inspired multi-agent systems with optical wireless power transfer for dynamic EV fleet management. The system uses adaptive LED arrays and reinforcement learning to optimize both power distribution and charging schedules, while incorporating real-time fleet behavior patterns.