Abstract The Algorithm Selection Problem is concerned with selecting the best algorithm to
solve a given problem on a case-by-case basis. It has become especially relevant in the last …

The task of algorithm selection involves choosing an algorithm from a set of algorithms on a
per-instance basis in order to exploit the varying performance of algorithms over a set of …

Algorithm selection (AS) techniques-which involve choosing from a set of algorithms the one
expected to solve a given problem instance most efficiently-have substantially improved the …

We present a new approach for learning to solve SMT formulas. We phrase the challenge of
solving SMT formulas as a tree search problem where at each step a transformation is …

The algorithm selection problem is to choose the most suitable algorithm for solving a given
problem instance. It leverages the complementarity between different approaches that is …

This paper presents MachSMT, an algorithm selection tool for Satisfiability Modulo Theories
(SMT) solvers. MachSMT supports the entirety of the SMT-LIB language and standardized …

The problem of selecting an algorithm that appears most suitable for a specific instance of
an algorithmic problem class, such as the Boolean satisfiability problem, is called instance …

Selecting a well-performing algorithm for a given task or dataset can be time-consuming and
tedious, but is crucial for the successful day-to-day business of develo** new AI & ML …

In this paper, we present MachSMT, an algorithm selection tool for Satisfiability Modulo
Theories (SMT) solvers. MachSMT supports the entirety of the SMT-LIB language. It employs …

Algorithm selection, a critical process of automated machine learning, aims to identify the
most suitable algorithm for solving a specific problem prior to execution. Mainstream …