Personalized Medication and Activity Planning in PDDL+

Author:

Alaboud Fares K.,Coles Andrew

Abstract

The emergence of planners capable of reasoning with continuous dynamics, as expressed in PDDL+, has increased the range of problems that fall within the capabilities of PDDL planners. One such problem is planning patients’ activities and medication regimes, considering non-linear medication pharmacokinetics. In this paper we explore the application of contemporary PDDL+ planners to this problem. To address their performance limitations, we present a linearize–validate cycle; tasks are solved by iterative refinement of a linear approximation of the domain, solved by a linear planner, then validated at each stage against the full non-linear semantics. In doing this we allow this domain to fall within the capabilities of current planners; and in our evaluation we use OPTIC to demonstrate this.

Publisher

Association for the Advancement of Artificial Intelligence (AAAI)

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A Structure-Sensitive Translation from Hybrid to Numeric Planning;AIxIA 2023 – Advances in Artificial Intelligence;2023

2. Towards an AI Planning-Based Pipeline for the Management of Multimorbid Patients;Artificial Intelligence in Medicine;2022

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