RT Conference Proceedings
T1 Performance modelling of planners from homogeneous problem sets
A1 Rosa Turbides, Tomás Eduardo de la
A1 Cenamor Guijarro, Isabel Rosario
A1 Fernández Rebollo, Fernando
AB Empirical performance models play an important role in the development of planning portfolios that make a per-domain or per-problem configuration of its search components. Even though such portfolios have shown their power when compared to other systems in current benchmarks, there is no clear evidence that they are capable to differentiate problems (instances) having similar input properties (in terms of objects, goals, etc.) but fairly different runtime for a given planner. In this paper we present a study of empirical performance models that are trained using problems having the same configuration, with the objective of guiding the models to recognize the underlying differences existing among homogeneous problems. In addition we propose a set of new features that boost the prediction capabilities under such scenarios. The results show that the learned models clearly performed over random classifiers, which reinforces the hypothesis that the selection of planners can be done on a per-instance basis when configuring a portfolio.
PB Aaai Press. Association For The Advancement Of Artificial Intelligence
YR 2017
FD 2017-06-18
LK https://hdl.handle.net/10016/30500
UL https://hdl.handle.net/10016/30500
LA eng
NO This work has been partially supported by the Spanish projects TIN2014-55637-C2-1-R and TIN2015-65686-C5-1-R.
DS e-Archivo
RD 17 jul. 2024