AAAI

Association for the Advancement of Artificial Intelligence

Home / Proceedings / Proceedings of the International Conference on Automated Planning and Scheduling, 32 / Book One

Generalized Linear Integer Numeric Planning

Download PDF

Authors

Xiaoyou Lin,Qingliang Chen,Liangda Fang,Quanlong Guan,Weiqi Luo,Kaile Su

Jinan University, Guangzhou 510632, China,Jinan University, Guangzhou 510632, China,Jinan University, Guangzhou 510632, China Pazhou Lab, Guangzhou 510330, China Guangxi Key Laboratory of Trusted Software, Guilin University of Electronic Technology, Guilin 541004, China,Jinan University, Guangzhou 510632, China Guangdong Institute of Smart Education, Guangzhou 510632, China,Jinan University, Guangzhou 510632, China,Griffith University, Brisbane 4111, Australia


DOI:

10.1609/icaps.v32i1.19807


Abstract:

Classical planning aims to find a sequence of actions that guarantees goal achievement from an initial state. The representative framework of classical planning is based on propositional logic. Due to the weak expressiveness of propositional logic, many applications of interest cannot be formalized as a classical planning problem. Some extensions such as numeric planning and generalized planning (GP) are therefore proposed. Qualitative numeric planning (QNP) is a decidable class of numeric and generalized extensions and serves as a numeric abstraction of GP. However, QNP is still far from being perfect and needs further improvement. In this paper, we introduce another generalized version of numeric planning, namely generalized linear integer numeric planning(GLINP), which is a more suitable abstract framework of GP than QNP. In addition, we develop a general framework to synthesize solutions to GLINP problems. Finally, we evaluate our approach on a number of benchmarks, and experimental results justify the effectiveness and scalability of our proposed approach.