Personalized Medication and Activity Planning in PDDL+


  • Fares K. Alaboud King’s College London
  • Andrew Coles King’s College London



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.




How to Cite

Alaboud, F. K., & Coles, A. (2021). Personalized Medication and Activity Planning in PDDL+. Proceedings of the International Conference on Automated Planning and Scheduling, 29(1), 492-500.