Rendezvous Problem

The rendezvous problem focuses on efficiently coordinating the meeting of multiple agents, whether robots, spacecraft, or software entities, often in challenging or uncertain environments. Current research emphasizes the use of reinforcement learning, particularly with neural network architectures like transformers and attention-based models, to optimize rendezvous strategies, especially in scenarios with limited communication or dynamic obstacles. These advancements are crucial for improving the efficiency and robustness of multi-agent systems in diverse applications, ranging from space exploration and debris removal to multi-robot coordination and autonomous navigation.