Due to huge investments by both the public and private sectors, artificial intelligence (AI) has
made tremendous progress in solving multiple real-world problems such as disease …

SMT solvers are foundational tools for reasoning about constraints in practical problems
both within and outside program analysis. Faster SMT solving improves the performance of …

With artificial intelligence (AI) being well established within the daily lives of research
communities, we turn our gaze toward an application area that appears intuitively unsuited …

We present Self-Driven Strategy Learning (SDSL), a lightweight online learning
methodology for automated reasoning tasks that involve solving a set of related problems …

This special issue contains six revised and extended versions of tool papers that appeared
in the proceedings of TACAS 2021, the 27th International Conference on Tools and …

Today, the algorithm selection paradigm has become one of the promising approaches in
the field of optimization problems. Its main goal is to solve each case of an optimization …

Automated reasoning (AR) and machine learning (ML) are two of the foundational pillars of
artificial intelligence (AI) and yet have developed largely independently. The integration of …

Human rationality comprises two facets: deductive reasoning--deriving conclusions from
premises, and inductive reasoning--inferring patterns from observations. These two forms of …

SMT solvers are essential for applications in artificial intelligence, software verification, and
optimisation. However, no single solver excels across all formula types, different …

The Algorithm Selection Problem (ASP) presents a significant challenge in numerous
industries, requiring optimal solutions for complex computational problems. Traditional …