Abstract
Domains with high levels of complexity and uncertainty pose significant challenges for decision-makers. Complex systems have too many linkages and feedbacks among system elements to easily apply analytical methods, and yet are too structured for statistical methods. Uncertainty, in terms of lacking information on system conditions and inter-relationships as well as inherent stochasticity, makes it difficult to predict outcomes from changes to system dynamics. In such situations, simulation models are key tools to integrate knowledge and to help improve understanding of systems responses in order to guide decisions.
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Fall, A. (2004). Supporting Decisions in Complex, Uncertain Domains with Declarative Languages. In: Jayaraman, B. (eds) Practical Aspects of Declarative Languages. PADL 2004. Lecture Notes in Computer Science, vol 3057. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24836-1_2
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DOI: https://doi.org/10.1007/978-3-540-24836-1_2
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