A common assumption for logic-based argumentation is that an argument is a pair 〈Φ, α〉 where Φ is minimal subset of the knowledgebase such that Φ is consistent and Φ entails the claim α. Different logics provide different definitions for consistency and entailment and hence give us different options for formalising arguments and counterarguments. The expressivity of classical propositional logi...

In this paper, we make an investigation into the structure of routine design problems. By analyzing the design problem solving process, we show that the designer acquires a special kind of design knowledge, which we called path variability knowledge. Based on this kind of knowledge, we conclude that routine design can be regarded as a class of well-structured problems. Therefore, contrary to th...

As self-learning pricing algorithms become popular, there are growing concerns among academics and regulators that could learn to collude tacitly on non-competitive prices thereby harm competition. I study popular reinforcement learning show they develop collusive behavior in a simulated market environment. To derive counterfactual resembles traditional tacit collusion, conduct experiments with...

Algorithmic risk assessment is hailed as offering criminal justice officials a science-led system to triage offender populations better manage low- versus high-risk individuals. Risk algorithms have reached the pretrial world best practices method aid in reforms reduce reliance upon money bail and moderate detention’s material contribution mass incarceration. Still, these promises are elusive i...

In this paper, we review algorithmic bias in education, discussing the causes of that and reviewing empirical literature on specific ways is known to have manifested education. While other recent work has reviewed mathematical definitions fairness expanded approaches reducing bias, our focuses instead solidifying current understanding concrete impacts education—which groups are be impacted whic...