Autonomous Search: Towards the Easy Tuning of Constraint Programming Solvers

Crawford B.; Soto R.; Olivares R.; Herrera R.; Monfroy E.; Paredes F.

dc.contributor.author	Crawford B.
dc.contributor.author	Soto R.
dc.contributor.author	Olivares R.
dc.contributor.author	Herrera R.
dc.contributor.author	Monfroy E.
dc.contributor.author	Paredes F.
dc.date.accessioned	2020-09-02T22:15:42Z
dc.date.available	2020-09-02T22:15:42Z
dc.date.issued	2014
dc.identifier	10.1007/978-3-319-07857-1_29
dc.identifier.citation	434 PART I, , 165-168
dc.identifier.issn	18650929
dc.identifier.uri	https://hdl.handle.net/20.500.12728/4161
dc.description	Constraint programming (CP) allows users to solve combinatorial problems by simply launching the corresponding model in a search engine. However, achieving good results may clearly depend on the correct search engine configuration, which demands advanced knowledge from the modeler. Recently, Autonomous Search (AS) appeared as a new technique that enables a given search engine to control and adapt its own configuration based on self-tuning. The goal is to be more efficient without the knowledge of an expert user. In this paper, we illustrate how the integration of AS into CP is carried out, reducing as a consequence the user involvement in solver tuning. © Springer International Publishing Switzerland 2014.
dc.language.iso	en
dc.publisher	Springer Verlag
dc.subject	Autonomous Search
dc.subject	Constraint Programming
dc.subject	Constraint Satisfaction
dc.subject	Constraint theory
dc.subject	Search engines
dc.subject	Autonomous searches
dc.subject	Combinatorial problem
dc.subject	Constraint programming
dc.subject	Constraint Satisfaction
dc.subject	Engine configuration
dc.subject	Expert users
dc.subject	Selftuning
dc.subject	User involvement
dc.subject	Computer programming
dc.title	Autonomous Search: Towards the Easy Tuning of Constraint Programming Solvers
dc.type	Conference Paper