Context Aware Multi Agent

Context-aware multi-agent systems aim to create groups of autonomous agents that can intelligently react to dynamic environments and changing conditions. Current research emphasizes the integration of large language models and reinforcement learning to enable agents to learn complex behaviors and coordinate effectively, often using agent-based modeling or neural cellular automata architectures. These systems are being explored for diverse applications, including smart home management, efficient energy distribution, and improved logistics, demonstrating their potential to optimize resource allocation and enhance decision-making in complex scenarios.