611 citations · 855 across the 28 of their papers we have counts for
4 papers · 1 filter
On the Foundations of Cycles in Bayesian Networks
Christel Baier, Clemens Dubslaff, Holger Hermanns +1
Bayesian networks (BNs) are a probabilistic graphical model widely used for representing expert knowledge and reasoning under uncertainty. Traditionally, they are based on directed…
What Do We Want From Explainable Artificial Intelligence (XAI)? -- A Stakeholder Perspective on XAI and a Conceptual Model Guiding Interdisciplinary XAI Research
Markus Langer, Daniel Oster, Timo Speith +5
Previous research in Explainable Artificial Intelligence (XAI) suggests that a main aim of explainability approaches is to satisfy specific interests, goals, expectations, needs, a…
Towards a Framework Combining Machine Ethics and Machine Explainability
Kevin Baum, Holger Hermanns, Timo Speith
We find ourselves surrounded by a rapidly increasing number of autonomous and semi-autonomous systems. Two grand challenges arise from this development: Machine Ethics and Machine…
Multi-Objective Approaches to Markov Decision Processes with Uncertain Transition Parameters
Dimitri Scheftelowitsch, Peter Buchholz, Vahid Hashemi +1
Markov decision processes (MDPs) are a popular model for performance analysis and optimization of stochastic systems. The parameters of stochastic behavior of MDPs are estimates fr…