A Survey on Context-Aware Multi-Agent Systems: Techniques, Challenges and Future Directions

• DOI: 10.48550/arxiv.2402.01968
• Publication Date: 2024-02-02
• Authors: Hung Du; Srikanth Thudumu; Rajesh Vasa; Kon Mouzakis
• Keywords: FOS: Computer and information sciences; Computer Science - Machine Learning; Artificial Intelligence (cs.AI); Computer Science - Artificial Intelligence; Computer Science - Multiagent Systems; Multiagent Systems (cs.MA); Machine Learning (cs.LG)

Research interest in autonomous agents is on the rise as an emerging topic. The notable achievements of Large Language Models (LLMs) have demonstrated considerable potential to attain human-like intelligence agents. However, challenge lies enabling these learn, reason, and navigate uncertainties dynamic environments. Context awareness emerges a pivotal element fortifying multi-agent systems when dealing with situations. Despite existing research focusing both context-aware systems, there lack comprehensive surveys outlining techniques for integrating systems. To address this gap, survey provides overview state-of-the-art First, we outline properties that facilitate integration between Subsequently, propose general process each phase encompassing diverse approaches drawn from various application domains such collision avoidance driving, disaster relief management, utility supply chain human-AI interaction, others. Finally, discuss challenges provide future directions field.