In response to the limitations of reinforcement learning and evolutionary algorithms (EAs) in
complex problem-solving, Evolutionary Reinforcement Learning (EvoRL) has emerged as a …

This paper contextualizes explainable artificial intelligence (AI) for enhanced decision-
making and serves as an editorial for the corresponding special issue. AI is defined as the …

In this survey, we address the key challenges in Large Language Models (LLM) research,
focusing on the importance of interpretability. Driven by increasing interest from AI and …

Rule-based models offer a human-understandable representation, ie they are interpretable.
For this reason, they are used to explain the decisions of non-interpretable complex models …

In the wake of increasing digital fraud, this paper introduces an innovative application of
Artificial Intelligence (AI) in detecting fraudulent activities across finance, healthcare, and e …

With the increasing adoption of Artificial Intelligence (AI) for decision-making processes by
companies, developing systems that behave fairly and do not discriminate against specific …

Integrating AI-driven recommender systems has proven highly successful in many
industries, prompting the banking sector to explore personalised client recommendations …

Integrating AI-driven recommender systems has proven highly successful in many
industries, prompting the banking sector to explore personalised client recommendations …