Publication
ICAPS 2018
Workshop paper

Delfi: Online Planner Selection for Cost-Optimal Planning

Download paper

Abstract

Cost-optimal planning has not seen many successful approaches that work well across all domains. Some cost-optimal planners excel on some domains, while exhibiting less exciting performance on others. For a particular domain, however, there is often a cost-optimal planner that works extremely well. For that reason, portfolio-based techniques have recently become popular. These either decide offline on a particular resource allocation scheme for a given collection of planners or try to perform an online classification of a given planning task to select a planner to be applied to solving the task at hand. Our planner Delfi is an online portfolio planner. In contrast to existing techniques, Delfi exploits deep learning techniques to learn a model that predicts which of the planners in the portfolio can solve a given planning task within the imposed time and memory bounds. Delfi uses graphical representations of a planning task which allows exploiting existing tools for image convolution. In this planner abstract, we describe the techniques used to create our portfolio planner.

Date

24 Jun 2018

Publication

ICAPS 2018