Width-Based Algorithms for Common Problems in Control, Planning and Reinforcement Learning

Width-Based Algorithms for Common Problems in Control, Planning and Reinforcement Learning

Nir Lipovetzky

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence
Early Career. Pages 4956-4960. https://doi.org/10.24963/ijcai.2021/702

Width-based algorithms search for solutions through a general definition of state novelty. These algorithms have been shown to result in state-of-the-art performance in classical planning, and have been successfully applied to model-based and model-free settings where the dynamics of the problem are given through simulation engines. Width-based algorithms performance is understood theoretically through the notion of planning width, providing polynomial guarantees on their runtime and memory consumption. To facilitate synergies across research communities, this paper summarizes the area of width-based planning, and surveys current and future research directions.
Keywords:
Planning and Scheduling: General
Planning and Scheduling: Planning Algorithms
Planning and Scheduling: Theoretical Foundations of Planning
Planning and Scheduling: Applications of Planning