دورية أكاديمية

Data Driven Simulation to Support Model Building in the Social Sciences

التفاصيل البيبلوغرافية
العنوان: Data Driven Simulation to Support Model Building in the Social Sciences
المؤلفون: Catriona Kennedy, Georgios Theodoropoulos, Volker Sorge, Edward Ferrari, Peter Lee, Chris Skelcher
المصدر: Journal of Algorithms & Computational Technology, Vol 5 (2011)
بيانات النشر: SAGE Publishing, 2011.
سنة النشر: 2011
المجموعة: LCC:Applied mathematics. Quantitative methods
LCC:Mathematics
مصطلحات موضوعية: Applied mathematics. Quantitative methods, T57-57.97, Mathematics, QA1-939
الوصف: Artificial intelligence (AI) can contribute to the management of a data driven simulation system, in particular with regard to adaptive selection of data and refinement of the model on which the simulation is based. We consider two different classes of intelligent agent that can control a data driven simulation: (a) an autonomous agent using internal simulation to test and refine a model of its environment and (b) an assistant agent managing a data-driven simulation to help humans understand a complex system (assisted model-building). We present a prototype implementation of an assistant agent to apply DDDAS to social simulations. The automation of the data-driven model development requires content interpretation of both the simulation and the corresponding real-world data. The paper discusses the use of Association Rule Mining to produce general logical statements about simulation and data content as well as the use of logical consistency checking to detect observations that refute the simulation predictions. Finally we consider ways in which this kind of assistant agent can cooperate with autonomous data collection and analysis agents to build a more complete and reliable picture of the observed system.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 1748-3018
1748-3026
العلاقة: https://doaj.org/toc/1748-3018Test; https://doaj.org/toc/1748-3026Test
DOI: 10.1260/1748-3018.5.4.561
الوصول الحر: https://doaj.org/article/e494fc5069004a4e9ab860948944800aTest
رقم الانضمام: edsdoj.494fc5069004a4e9ab860948944800a
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:17483018
17483026
DOI:10.1260/1748-3018.5.4.561