Reviewing agent-based modelling of socio-ecosystems: a methodology for the analysis of climate change adaptation and sustainability

The integrated - environmental, economic and social - analysis of climate change calls for a paradigm shift as it is fundamentally a problem of complex, bottom-up and multi-agent human behaviour. There is a growing awareness that global environmental change dynamics and the related socio-economic implications involve a degree of complexity that requires an innovative modelling of combined social and ecological systems. Climate change policy can no longer be addressed separately from a broader context of adaptation and sustainability strategies. A vast body of literature on agent-based modelling (ABM) shows its potential to couple social and environmental models, to incorporate the influence of micro-level decision making in the system dynamics and to study the emergence of collective responses to policies. However, there are few publications which concretely apply this methodology to the study of climate change related issues. The analysis of the state of the art reported in this paper supports the idea that today ABM is an appropriate methodology for the bottom-up exploration of climate policies, especially because it can take into account adaptive behaviour and heterogeneity of the system's components.Review, Agent-Based Modelling, Socio-Ecosystems, Climate Change, Adaptation, Complexity.

From Social Simulation to Integrative System Design

As the recent financial crisis showed, today there is a strong need to gain "ecological perspective" of all relevant interactions in socio-economic-techno-environmental systems. For this, we suggested to set-up a network of Centers for integrative systems design, which shall be able to run all potentially relevant scenarios, identify causality chains, explore feedback and cascading effects for a number of model variants, and determine the reliability of their implications (given the validity of the underlying models). They will be able to detect possible negative side effect of policy decisions, before they occur. The Centers belonging to this network of Integrative Systems Design Centers would be focused on a particular field, but they would be part of an attempt to eventually cover all relevant areas of society and economy and integrate them within a "Living Earth Simulator". The results of all research activities of such Centers would be turned into informative input for political Decision Arenas. For example, Crisis Observatories (for financial instabilities, shortages of resources, environmental change, conflict, spreading of diseases, etc.) would be connected with such Decision Arenas for the purpose of visualization, in order to make complex interdependencies understandable to scientists, decision-makers, and the general public.Comment: 34 pages, Visioneer White Paper, see http://www.visioneer.ethz.c

Challenges in Complex Systems Science

FuturICT foundations are social science, complex systems science, and ICT. The main concerns and challenges in the science of complex systems in the context of FuturICT are laid out in this paper with special emphasis on the Complex Systems route to Social Sciences. This include complex systems having: many heterogeneous interacting parts; multiple scales; complicated transition laws; unexpected or unpredicted emergence; sensitive dependence on initial conditions; path-dependent dynamics; networked hierarchical connectivities; interaction of autonomous agents; self-organisation; non-equilibrium dynamics; combinatorial explosion; adaptivity to changing environments; co-evolving subsystems; ill-defined boundaries; and multilevel dynamics. In this context, science is seen as the process of abstracting the dynamics of systems from data. This presents many challenges including: data gathering by large-scale experiment, participatory sensing and social computation, managing huge distributed dynamic and heterogeneous databases; moving from data to dynamical models, going beyond correlations to cause-effect relationships, understanding the relationship between simple and comprehensive models with appropriate choices of variables, ensemble modeling and data assimilation, modeling systems of systems of systems with many levels between micro and macro; and formulating new approaches to prediction, forecasting, and risk, especially in systems that can reflect on and change their behaviour in response to predictions, and systems whose apparently predictable behaviour is disrupted by apparently unpredictable rare or extreme events. These challenges are part of the FuturICT agenda

Symptoms of complexity in a tourism system

Tourism destinations behave as dynamic evolving complex systems, encompassing numerous factors and activities which are interdependent and whose relationships might be highly nonlinear. Traditional research in this field has looked after a linear approach: variables and relationships are monitored in order to forecast future outcomes with simplified models and to derive implications for management organisations. The limitations of this approach have become apparent in many cases, and several authors claim for a new and different attitude. While complex systems ideas are amongst the most promising interdisciplinary research themes emerged in the last few decades, very little has been done so far in the field of tourism. This paper presents a brief overview of the complexity framework as a means to understand structures, characteristics, relationships, and explores the implications and contributions of the complexity literature on tourism systems. The objective is to allow the reader to gain a deeper appreciation of this point of view.Comment: 32 pages, 3 figures, 1 table; accepted in Tourism Analysi

The size distribution of cities: a kinetic explanation

We present a kinetic approach to the formation of urban agglomerations which is based on simple rules of immigration and emigration. In most cases, the Boltzmann-type kinetic description allows to obtain, within an asymptotic procedure, a Fokker--Planck equation with variable coefficients of diffusion and drift, which describes the evolution in time of some probability density of the city size. It is shown that, in dependence of the microscopic rules of migration, the equilibrium density can follow both a power law for large values of the size variable, which contains as particular case a Zipf's law behavior, and a lognormal law for middle and low values of the size variable. In particular, connections between the value of Pareto index of the power law at equilibrium and the disposal of the population to emigration are outlined. The theoretical findings are tested with recent data of the populations of Italy and Switzerland

Some considerations concerning the challenge of incorporating social variables into epidemiological models of infectious disease transmission

Incorporation of ‘social’ variables into epidemiological models remains a challenge. Too much detail and models cease to be useful; too little and the very notion of infection —a highly social process in human populations—may be considered with little reference to the social. The French sociologist Emile Durkheim proposed that the scientific study of society required identification and study of ‘social currents.’ Such ‘currents’ are what we might today describe as ‘emergent properties,’ specifiable variables appertaining to individuals and groups, which represent the perspectives of social actors as they experience the environment in which they live their lives. Here we review the ways in which one particular emergent property, hope, relevant to a range of epidemiological situations, might be used in epidemiological modelling of infectious diseases in human populations. We also indicate how such an approach might be extended to include a range of other potential emergent properties to repre

Boltzmann-type models with uncertain binary interactions

In this paper we study binary interaction schemes with uncertain parameters for a general class of Boltzmann-type equations with applications in classical gas and aggregation dynamics. We consider deterministic (i.e., a priori averaged) and stochastic kinetic models, corresponding to different ways of understanding the role of uncertainty in the system dynamics, and compare some thermodynamic quantities of interest, such as the mean and the energy, which characterise the asymptotic trends. Furthermore, via suitable scaling techniques we derive the corresponding deterministic and stochastic Fokker-Planck equations in order to gain more detailed insights into the respective asymptotic distributions. We also provide numerical evidences of the trends estimated theoretically by resorting to recently introduced structure preserving uncertainty quantification methods

Boltzmann type control of opinion consensus through leaders

The study of formations and dynamics of opinions leading to the so called opinion consensus is one of the most important areas in mathematical modeling of social sciences. Following the Boltzmann type control recently introduced in [G. Albi, M. Herty, L. Pareschi arXiv:1401.7798], we consider a group of opinion leaders which modify their strategy accordingly to an objective functional with the aim to achieve opinion consensus. The main feature of the Boltzmann type control is that, thanks to an instantaneous binary control formulation, it permits to embed the minimization of the cost functional into the microscopic leaders interactions of the corresponding Boltzmann equation. The related Fokker-Planck asymptotic limits are also derived which allow to give explicit expressions of stationary solutions. The results demonstrate the validity of the Boltzmann type control approach and the capability of the leaders control to strategically lead the followers opinion