Optimal Planning

Optimal planning focuses on finding the best sequence of actions to achieve a desired goal, considering factors like time, cost, and risk. Current research emphasizes robust solutions in uncertain environments, employing diverse techniques such as reinforcement learning (including deep RL and distributional RL), mixed-integer programming, and heuristic search algorithms often combined with large language models or symbolic methods. These advancements are crucial for applications ranging from autonomous robotics and space exploration to resource management and epidemic control, improving efficiency, safety, and decision-making in complex systems.