It was an intense meeting, gathering people from all over the world and with different backgrounds. The SOCIAL SIMULATION CONFERENCE, SSC 2016, organized by the LABSS team at the National Research Council of Italy (September 19-23, 2016, Rome) is now condensed in a one minute and a half: enjoy the SSC 2016 video!
The Laboratory of Agent Based Social Simulation at the Institute of Cognitive Sciences and Technologies CNR is seeking candidates for a one-year post-doc position (renewable up to 3-years) to work on the EU Horizon 2020 project ‘PROTON’ for simulative research on the evolution of organized crime and terrorist networks.
We cordially invite researchers and practitioners from all over the world to Rome, “caput mundi”, to share their latest results and foster our understanding of social complexity problems by means of computational simulations.
SSC2016 will be the 6th joint meeting (previously known as WCSS) of the three main scientific societies for Social Simulation, Social Systems Science and Computational Social Science.
Mathematical modeling: dynamics of nonlinear systems and chaos.
Aprile, 16. 2015
This course is designed to be a bridge between the study of mathematics and the application of mathematics to various fields. It provides an overview of how the mathematical pieces of an applied problem fit together.
Mathematical modeling is the process of creating a mathematical representation of some phenomenon in order to gain a better understanding of that phenomenon. The main goal of this course is to learn how to make creative use of some mathematical tools, such as difference equations, ordinary and partial differential equations, and numerical analysis, to build a mathematical description of biological, social and economic phenomena.
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In the first part of the paper, the field of Agent-Based Modelling is discussed focusing on the role of generative theories, aiming at explaining phenomena by growing them. After a brief analysis of the major strengths of the field some crucial weaknesses are analysed. In particular, the generative power of ABM is found to have been underexploited, as the pressure for simple recipes has prevailed and shadowed the application of rich cognitive models. In the second part of the paper, the renewal of interest for Computational Social Science is focused upon, and several of its variants, such as deductive, generative, and complex CSS, are identified and described. In the concluding remarks, an interdisciplinary variant, which takes after ABM, reconciling it with the quantitative one, is proposed as a fundamental requirement for a new program of the CSS.