Planning Algorithm

Planning algorithms aim to find optimal sequences of actions to achieve a desired goal, a fundamental problem across robotics, AI, and autonomous systems. Current research emphasizes improving efficiency and robustness in complex, dynamic environments, focusing on techniques like hierarchical planning, diffusion models, and game-theoretic approaches, often incorporating machine learning for improved performance and generalization. These advancements are crucial for enabling safe and efficient operation of autonomous agents in real-world scenarios, ranging from autonomous driving and robotic manipulation to multi-agent coordination and resource management.