A Methodology for Complex Social Simulations

Social simulation - an emerging field of computational social science - has progressed from simple toy models to increasingly realistic models of complex social systems, such as agent-based models where heterogeneous agents interact with changing natural or artificial environments. These larger, multidisciplinary projects require a scientific research methodology distinct from, say, simpler social simulations with more limited scope, intentionally minimal complexity, and typically under a single investigator. This paper proposes a methodology for complex social simulations - particularly inter- and multi-disciplinary socio-natural systems with multi-level architecture - based on a succession of models akin to but distinct from the late Imre Lakatos' notion of a 'research programme'. The proposed methodology is illustrated through examples from the Mason-Smithsonian project on agent-based models of the rise and fall of polities in Inner Asia. While the proposed methodology requires further development, so far it has proven valuable for advancing the scientific objectives of the project and avoiding some pitfalls.Agent-Based Modeling Methodology, M2M, Social Simulation, Computational Social Science, Social Complexity, Inner Asia

For an Integrated Approach to Agent-Based Modeling of Science

The goal of this paper is to provide a sketch of what an agent-based model of the scientific process could be. It is argued that such a model should be constructed with normative claims in mind: i.e. that it should be useful for scientific policy making. In our tentative model, agents are researchers producing ideas that are points on an epistemic landscape. We are interested in our agents finding the best possible ideas. Our agents are interested in acquiring credit from their peers, which they can do by writing papers that are going to get cited by other scientists. They can also share their ideas with collaborators and students, which will help them eventually get cited. The model is designed to answer questions about the effect that different possible behaviors have on both the individual scientists and the scientific community as a whole.Agent-Based Models, Science Dynamics, Social Networks, Scientometrics, Evolutionary Computation

Overview on agent-based social modelling and the use of formal languages

Transdisciplinary Models and Applications investigates a variety of programming languages used in validating and verifying models in order to assist in their eventual implementation. This book will explore different methods of evaluating and formalizing simulation models, enabling computer and industrial engineers, mathematicians, and students working with computer simulations to thoroughly understand the progression from simulation to product, improving the overall effectiveness of modeling systems.Postprint (author's final draft

Reconstructing the question of school choice : towards a geographical agent-based model for Chile

The aim of this paper is to reformulate the question of school choice in a voucher system, by moving towards a perspective, assessing competition between schools and the choice of students using Geographic Information Systems (GIS) and Agent-Based Modeling (ABM). How spatial structure affects competition among schools? How do socio-geographic structuration and social interaction affect this process? We show a preview of the proposed model and main social mechanisms of school choice: Quality, Distance, Cost, Expectations, Homophily and Mimesis for students and their families, and Selection, Supply and Local Competition for schools

Technological and social networks of a pastoralist artificial society: agent-based modeling of mobility patterns

This paper explores the advantages of simulation to raise the question of how digital and social networks affect the mobility in a pastoralist artificial society in the context of environmental degradation. We aim to explore mechanisms and develop scenarios, which are going to be validated through further research. We use a model of a simple pastoralist society in a world without borders to migration by adding the possibility of experiencing the effects of social structures (such as family and friends) and technological networks (e.g., social media). It appears obvious that pastoralist mobility depends on other dimensions as land tenure and traditional knowledge; however, isolating these two effects and experimenting in a simple society allow us to filter the multidimensionality of mobility decisions and concentrate on comparing scenarios in several different social structures and technological network combinations. The results show an expected behavior of more connection and more mobility, and a non-linear emergent behavior where pastoralists wait for a longer amount of time to mobilize when they interact using powerful social and technological networks. This occurs until they decide to move, and then, they mobilize more quickly and strongly than they did when communication was non-existent between them. The literature on migration explains this emergent non-linear behavior

Asking the Oracle: introducing forecasting principles into agent-based modelling

This paper presents a set of guidelines, imported from the field of forecasting, that can help social simulation and, more specifically, agent-based modelling practitioners to improve the predictive performance and the robustness of their models. The presentation starts with a discussion on the current debate on prediction in social processes, followed by an overview of the recent experience and lessons learnt from the field of forecasting. This is the basis to define standard practices when developing agent-based models under the perspective of forecasting experimentation. In this context, the guidelines are structured in six categories that correspond to key issues that should be taken into account when building a predictor agent-based model: the modelling process, the data adequacy, the space of solutions, the expert involvement, the validation, and the dissemination and replication. The application of these guidelines is illustrated with an existing agent-based model. We conclude by tackling some intrinsic difficulties that agent-based modelling often faces when dealing with prediction models.project Social Ambient Assisting Living - Methods (SociAAL), supported by Spanish Council for Science and Innovation, with grant TIN2011-28335-C02-01 and the Spanish MICINN project CSD2010-00034 (SimulPast CONSOLIDER-INGENIO 2010). We also thank the support from the Programa de Creación y Consolidación de Grupos de Investigación UCM-BSCH, GR35/10-A (921354

Combinatorial versus sequential auctions to allocate PPP highway projects

This article models a procurement process for allocating multiple related public-private partnership (PPP) highway projects. Traditionally, public infrastructure procurement processes have used a sequential allocation mechanism, despite the potential benefits of allocating all projects at once. The main contribution of this research is to address the question whether these projects should be auctioned individually, in sequential auctions, or at the same time, in a combinatorial auction. Our goal is to understand the impact of the allocation process in terms of efficiency and social welfare. In sequential auctions, bidders submit their offers for each project independently. However, in combinatorial auctions, contractors have the ability to bid for their preferred packages (combinations of projects), reflecting synergies or entry costs, if any, in their valuations. We have compared the impact in terms of efficient allocation and social welfare of both mechanisms in order to help policymakers to take future decisions when facing these processes. The methodology used to address these core questions in the multidisciplinary environment described is based on social simulations, which involves conducting analysis by means of computational simulations. For this work we have created a sophisticated valuation model adapted to the public infrastructure sector and we have developed a simulator which includes multiple types of bidders, projects and several scenarios. The experimental setup is based on the second wave of the Colombian 4G program, a case involving the allocation of 9 highway construction projects across the country. We have also included references to multiple examples of real markets in which these mechanisms could be implemented. Therefore, this research provides a valuable reference for policymakers chasing to enhance market design that could be applied in many real-world scenarios. The results reveal that the combinatorial mechanism improves the process in terms of optimal allocation and efficiency, yielding significant savings for all parties

Overview on Agent-Based Social Modelling and the Use of Formal Languages

The use of agent-based modelling and simulation techniques in the social sciences has flourished in the recent decades. The main reason is that the object of study in these disciplines, human society present or past, is difficult to analyse through classical analytical techniques. Population dynamics and structures are inherently complex. Thus, other methodological techniques need to be found to more adequately study this field. In this context, agent-based modelling is encouraging the introduction of computer simulations to examine behavioural patterns in complex systems. Simulation provides a tool to artificially examine societies where a big number of actors with decision capacity coexist and interact. However, formal modelling in these areas has not traditionally been used compared to other fields of science, in particular in their use of formal languages during the modelling process. In this chapter, the authors aim to revise the most relevant aspects on modelling in social sciences and to discuss the use formal languages by social scientists