Automating Workflow/Pipeline Design

Cognitive technologies, pp. 123–140

Abstract

Summary This chapter discusses the design of workflows (or pipelines), which represent solutions that involve more than one algorithm. This is motivated by the fact that many tasks require such solutions. This problem is non-trivial, as the number of possible workflows (and their configurations) can be rather large. This chapter discusses various methods that can be used to restrict the design options and thus reduce the size of the configuration space. These include, for instance, ontologies and context-free grammars. Each of these formalisms has its merits and shortcomings. Many platforms have resorted to planning systems that use operators. These can be designed to be in accordance with the given ontologies or grammars. As the search space may be rather large, it is important to leverage prior experience. This topic is addressed in one of the sections, which discusses rankings of plans that have proved to be useful in the past. The workflows/pipelines that have proved successful in the past can be retrieved and used as plans in future tasks. Thus, it is possible to exploit both planning and metalearning.

Authors 4

1. Pavel Brazdil corresponding

   Universidade do Porto

   Affiliation as printed

   Laboratory of Artificial Intelligence and Decision Support, University of Porto, Porto, Portugal

2. Jan N. van Rijn Aachen Leiden Institute of Advanced Computer Science

   Leiden University

   Affiliation as printed

   Leiden Institute of Advanced Computer Science, Leiden University, Leiden, The Netherlands

3. Carlos Soares

   Universidade do Porto

   Affiliation as printed

   Porto Business School, Porto, Portugal

4. Joaquin Vanschoren

   Eindhoven University of Technology

   Affiliation as printed

   Department of Mathematics and Computer Science, Technische Universiteit Eindhoven, Eindhoven, The Netherlands