Automated Design of Search with Composability

We propose a new perspective on the automated design of combinatorial search algorithms through an approach that operates at a much higher semantic level than previous algorithm configurators do. Instead of blindly tuning numerical or categorical parameters based on black-box optimization or resorting to a handful of predefined strategies, we propose to automatically search over compositions of search strategies using a light-weight language, while exploiting the semantic knowledge of the modeling language itself to guide the configuration process. Although somewhat reminiscent of the old AI vision that machines will be able to program themselves to solve novel tasks, we believe that the idea restricted to this simple but powerful search language has a chance of success in practice.