We are a highly interdisciplinary research group working at the intersection among cognitive, social and computational sciences. LABSS is based at the Institute of Cognitive Sciences and Technologies (ISTC) of the National Research Council of Italy (CNR) and aims to foster an explorative approach to Agent Based Modeling and Simulation.

SSC 2016 Video

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!

Mission completed: SSC 2016, ESSA^4

We are glad to announce that the LABSS team has successfully completed the two main organizional tasks for the year 2016: the Social Simulation Conference, SSC 2016, and the ESSA Summer School (it was already autumn, but we don’t let details as such deter us).

We have our own Twitter voice now – @LABSS-CNR – and we are going to update this website more often. Stay tuned!

POSTDOC POSITION ANNOUNCEMENT

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.

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Social Simulation Conference 2016

The SOCIAL SIMULATION CONFERENCE, SSC 2016, the 6th joint meeting of ESSA, PAAA, and CSSSA, will be held in Rome, September 19-23, 2016.

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.

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Rosaria Conte on "La Repubblica" rethinking economy

Rethinking Economy and the Social Science with multi-disciplinar simulations (in Italian; click here for a Google translation to English.

Lessons

Mathematical modeling: dynamics of nonlinear systems and chaos.
Socio-economic framework.

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.

For info/scheduling click HERE or mail to cecconi.federico@gmail.com

Lecture @ Szeged

The mindmap from Mario Paolucci’s invited lecture in David Hales’ doctoral course in Sezged is downloadable on the xmind website.

Luis Gustavo Nardin wins the best student paper award at SSC 2014

We are delighted to announce that Luis Gustavo Nardin has obtained the “best student paper award at SSC 2014” with the paper From Anarchy to Monopoly: How Competition and Protection Shaped Mafia’s Behavior

On Agent-Based Modelling and Computational Social Science

We’re glad to announce a new paper from LABSS as a contribution to the debate on the approach to computational social science: On Agent-Based Modelling and Computational Social Science.

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.

doi: 10.3389/fpsyg.2014.00668

Mechanism change in a simulation of peer review: from junk support to elitism

New paper on peer review from LABSS and UniValencia: Mechanism change in a simulation of peer review: from junk support to elitism.

Our honest, totally unbiased, objective evaluation of this work is: reading it will change your life. You will sleep better. A sense of clarity will ensue. The pictures will spring up your imagination. The only paper you really need to read this year.

Ahem. Well maybe we’re a little bit overplaying it. Ok, here’s the abstract:

Peer review works as the hinge of the scientific process, mediating between research and the awareness/acceptance of its results. While it might seem obvious that science would regulate itself scientifically, the consensus on peer review is eroding; a deeper understanding of its workings and potential alternatives is sorely needed. Employing a theoretical approach supported by agent-based simulation, we examined computational models of peer review, performing what we propose to call redesign, that is, the replication of simulations using different mechanisms. Here, we show that we are able to obtain the high sensitivity to rational cheating that is present in literature. In addition, we also show how this result appears to be fragile against small variations in mechanisms. Therefore, we argue that exploration of the parameter space is not enough if we want to support theoretical statements with simulation, and that exploration at the level of mechanisms is needed. These findings also support prudence in the application of simulation results based on single mechanisms, and endorse the use of complex agent platforms that encourage experimentation of diverse mechanisms.

DOI 10.1007/s11192-014-1239-1

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