Planning for LTLf /LDLf Goals in Non-Markovian Fully Observable Nondeterministic Domains
Planning for LTLf /LDLf Goals in Non-Markovian Fully Observable Nondeterministic Domains
Ronen I. Brafman, Giuseppe De Giacomo
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence
Main track. Pages 1602-1608.
https://doi.org/10.24963/ijcai.2019/222
In this paper, we investigate non-Markovian Nondeterministic Fully Observable Planning Domains (NMFONDs), variants of Nondeterministic Fully Observable Planning Domains (FONDs) where the next state is determined by the full history leading to the current state. In particular, we introduce TFONDs which are NMFONDs where conditions on the history are succinctly and declaratively specified using the linear-time temporal logic on finite traces LTLf and its extension LDLf. We provide algorithms for planning in TFONDs for general LTLf/LDLf goals, and establish tight complexity bounds w.r.t. the domain representation and the goal, separately. We also show that TFONDs are able to capture all NMFONDs in which the dependency on the history is "finite state". Finally, we show that TFONDs also capture Partially Observable Nondeterministic Planning Domains (PONDs), but without referring to unobservable variables.
Keywords:
Knowledge Representation and Reasoning: Action, Change and Causality
Planning and Scheduling: Theoretical Foundations of Planning
Planning and Scheduling: Conformant;Contingent planning