A Novel Abstraction Framework for Online Planning

Abstractions are a useful tool for computing policies in large domains modeled as a Markov Decision Process. Prior work in this field is mostly focused on developing different notions for state abstractions. In this paper, we develop a novel framework for abstractions, which unifies prior work and directly exploits symmetry at the state-action pair level, thereby uncovering a much larger number of symmetries in a given domain. We describe the application of abstractions computed through this framework in UCT, a popular MCTS technique for online planning.ions are a useful tool for computing policies in large domains modeled as a Markov Decision Process. Prior work in this field is mostly focused on developing different notions for state abstractions. In this paper, we develop a novel framework for abstractions, which unifies prior work and directly exploits symmetry at the state-action pair level, thereby uncovering a much larger number of symmetries in a given domain. We describe the application of abstractions computed through this framework in UCT, a popular MCTS technique for online planning.