Optimising Partial-Order Plans Via Action Reinstantiation
Optimising Partial-Order Plans Via Action Reinstantiation
Max Waters, Lin Padgham, Sebastian Sardina
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence
Main track. Pages 4143-4151.
https://doi.org/10.24963/ijcai.2020/573
This work investigates the problem of optimising a partial-order plan’s (POP) flexibility through the simultaneous transformation of its action ordering and variable binding constraints. While the former has been extensively studied through the notions of deordering and reordering, the latter has received much less attention. We show that a plan’s variable bindings are often related to resource usage and their reinstantiation can yield more flexible plans. To do so, we extend existing POP optimality criteria to support variable reinstantiation, and prove that checking if a plan can be optimised further is NP-complete. We also propose a MaxSAT-based technique for increasing plan flexibility and provide a thorough experimental evaluation that suggests that there are benefits in action reinstantiation.
Keywords:
Planning and Scheduling: Planning and Scheduling