Algorithms play an increasingly important role in economic situations. Often these situations are strategic, where the artificial intelligence may or may not be cooperative. We study the determinants and forms of algorithmic cooperation in the infinitely repeated prisoner's dilemma. We run a...

The paper explores algorithmically created personalized wages: what they are, what they mean, and what we can do about them. First, it establishes a taxonomy of five different forms of algorithmic wage differentiation:- productivity-based wage adjustments,- wages shifted through incentive...

Analytically solving the classic newsvendor problem relies on a known demand distribution. In practice, however, it is not easy to approximate a sufficiently accurate demand distribution. This results in the obtained analytical solution may not be optimal. To address this issue, we propose a...

One of the lessons learned from the global financial crisis in 2008 was raising attention to monitoring and maintaining household vulnerability, particularly household credit risk, by using the default rate as the indicator. The indicator would be worsening at the economic recession, likewise,...

Wayang Kulit, which is an original Indonesian culture, is conditioned by the meaning of life in every performance. However, Wayang Kulit is currently less popular among young people due to a lack of understanding of the art of Wayang Kulit performance. To be able to provide knowledge to the...

A typical Assembly Line Balancing (ALB) Problem aims to optimize the mass production process by assigning the tasks to stations. To deal with the high product variety and short product life cycles, robots are utilized in many production lines. Humans and collaborative robots share the same...

The quadratic assignment problem (QAP) is one of the most important combinatorial optimization problems in theory and practice. In this paper, we are proposing a hierarchical data-driven parallel memetic algorithm to solve the problem. A component-based hierarchical system architecture with a...

Machine learning risks reinforcing biases present in data, and, as we argue in this work, in what is absent from data. In healthcare, biases have marked medical history, leading to unequal care affecting marginalised groups. Patterns in missing data often reflect these group discrepancies, but...