Maximizing the classification accuracy and minimizing the number of selected features are
two primary objectives in feature selection (FS), which is inherently a multiobjective task …

Understanding black box models has become paramount as systems based on opaque
Artificial Intelligence (AI) continue to flourish in diverse real-world applications. In response …

Heuristics are widely used for dealing with complex search and optimization problems.
However, manual design of heuristics can be often very labour extensive and requires rich …

Optimization can be found in many real-life applications. Designing an effective algorithm for
a specific optimization problem typically requires a tedious amount of effort from human …

The increasing number of vehicles in urban areas draws significant attention to traffic signal
control (TSC), which can enhance the efficiency of the entire network by properly switching …

Efficient truck dispatching is crucial for optimizing container terminal operations within
dynamic and complex scenarios. Despite good progress being made recently with more …

Scheduling heuristics are commonly used to solve dynamic scheduling problems in real-
world applications. However, designing effective heuristics can be time-consuming and …

Ensuring quality human-AI interaction (HAII) in safety-critical industries is essential. Failure
to do so can lead to catastrophic and deadly consequences. Despite this urgency, existing …

Cognitive diagnosis assessment is a fundamental and crucial task for student learning. It
models the student-exercise interaction, and discovers the students' proficiency levels on …

Drug discovery is an expensive and risky process. To combat the challenges in drug
discovery, an increasing number of researchers and pharmaceutical companies recognize …