On the Configuration of Robust Static Parallel Portfolios for Efficient Plan Generation

Abstract

Automated Planning has achieved a significant step forward in the last decade, and many advanced planning engines have been introduced. Nowadays, increases in computational power are mostly achieved through hardware parallelisation. In view of the increasing availability of multicore machines and of the intrinsic complexity of designing parallel algorithms, a natural exploitation of parallelism is to combine existing sequential planning engines into parallel portfolios. In this work, we introduce three techniques for an automatic configuration of static parallel portfolios of planning engines. The aim of generated portfolios is to provide a good tradeoff performance between coverage and runtime, on previously unseen problems. Our empirical results demonstrate that our techniques for configuring parallel portfolios combine strengths of planning engines, and fully exploit multicore machines. 2 Configuration of Robust Parallel Portfolios Automated Planning is about finding a sequence of actions, a plan, that transforms the environment from a given initial state to some goal state [6]. An action is specified via a precondition, i.e., what must hold prior its application, and effects, i.e., how the environment is transformed after its

sunny-as2: Enhancing SUNNY for Algorithm Selection

“…Likewise, in the domain of AI planning, portfolio parallelization has also been investigated. An example is the static parallel portfolio proposed by Vallati, Chrpa, and Kitchin (2018) where planners are scheduled to each available CPU core.…”