From the 1 of 5 linked papers with an AI index.
1 citations · 1 across the 2 of their papers we have counts for
5 papers
Diagrams-to-Dynamics (D2D): Exploring Causal Loop Diagram Leverage Points under Uncertainty
Jeroen F. Uleman, Loes Crielaard, Leonie K. Elsenburg +4
The paper introduces Diagrams-to-Dynamics (D2D), a method that transforms qualitative causal loop diagrams into exploratory system dynamics models without requiring empirical data,…
Abstract Markov Random Fields
Leon Lang, Clélia de Mulatier, Rick Quax +1
Markov random fields are known to be fully characterized by properties of their information diagrams, or I-diagrams. In particular, for Markov random fields, regions in the I-diagr…
Resilience of coupled systems under deep uncertainty and dynamic complexity: An integrative literature review
Jannie Coenen, VÃtor Vasconcelos, Heiman Wertheim +8
Resilience in coupled systems is increasingly critical in addressing global challenges such as climate change and pandemics. These systems show unpredictable behaviour due to dynam…
FREIDA: A Framework for developing quantitative agent based models based on qualitative expert knowledge
Frederike Oetker, Vittorio Nespeca, Rick Quax
Agent Based Models (ABMs) often deal with systems where there is a lack of quantitative data or where quantitative data alone may be insufficient to fully capture the complexities…
Information Decomposition Diagrams Applied beyond Shannon Entropy: A Generalization of Hu's Theorem
Leon Lang, Pierre Baudot, Rick Quax +1
In information theory, one major goal is to find useful functions that summarize the amount of information contained in the interaction of several random variables. Specifically, o…