Qualitative Modeling and Simulation of Socio-Economic Phenomena

This paper describes an application of recently developed qualitative reasoning techniques to complex, socio-economic allocation problems. We explain why we believe traditional optimization methods are inappropriate and how qualitative reasoning could overcome some of these shortcomings. A case study is presented where an authority is expected to devise a policy that satisfies certain constraints. We describe how sets of rules of thumb implementing such a policy can be analyzed and validated by the decision maker using a program which automatically builds and simulates qualitative models of the underlying dynamical system. Such a program constructs and simulates models from incomplete descriptions of initial states and functional relationships between variables. We show that it nevertheless gives sufficient information to the decision maker.Qualitative Modeling, Qualitative Reasoning, Decision Making, Allocation

An "All Hands" Call to the Social Science Community: Establishing a Community Framework for Complexity Modeling Using Agent Based Models and Cyberinfrastructure

To date, many communities of practice (COP) in the social sciences have been struggling with how to deal with rapidly growing bodies of information. Many CoPs across broad disciplines have turned to community frameworks for complexity modeling (CFCMs) but this strategy has been slow to be discussed let alone adopted by the social sciences communities of practice (SS-CoPs). In this paper we urge the SS-CoPs that it is timely to develop and establish a CBCF for the social sciences for two major reasons: the rapid acquisition of data and the emergence of critical cybertools which can facilitate agent-based, spatially-explicit models. The goal of this paper is not to prescribe how a CFCM might be set up but to suggest of what components it might consist and what its advantages would be. Agent based models serve the establishment of a CFCM because they allow robust and diverse inputs and are amenable to output-driven modifications. In other words, as phenomena are resolved by a SS-CoP it is possible to adjust and refine ABMs (and their predictive ability) as a recursive and collective process. Existing and emerging cybertools such as computer networks, digital data collections and advances in programming languages mean the SS-CoP must now carefully consider committing the human organization to enabling a cyberinfrastructure tool. The combination of technologies with human interfaces can allow scenarios to be incorporated through 'if' 'then' rules and provide a powerful basis for addressing the dynamics of coupled and complex social ecological systems (cSESs). The need for social scientists to be more engaged participants in the growing challenges of characterizing chaotic, self-organizing social systems and predicting emergent patterns makes the application of ABMs timely. The enabling of a SS-CoP CFCM human-cyberinfrastructure represents an unprecedented opportunity to synthesize, compare and evaluate diverse sociological phenomena as a cohesive and recursive community-driven process.Community-Based Complex Models, Mathematics, Social Sciences

An Agent Operationalization Approach for Context Specific Agent-Based Modeling

The potential of agent-based modeling (ABM) has been demonstrated in various research fields. However, three major concerns limit the full exploitation of ABM; (i) agents are too simple and behave unrealistically without any empirical basis, (ii) \'proof of concept\' applications are too theoretical and (iii) too much value placed on operational validity instead of conceptual validity. This paper presents an operationalization approach to determine the key system agents, their interaction, decision-making and behavior for context specific ABM, thus addressing the above-mentioned shortcomings. The approach is embedded in the framework of Giddens\' structuration theory and the structural agent analysis (SAA). The agents\' individual decision-making (i.e. reflected decisions) is operationalized by adapting the analytical hierarchy process (AHP). The approach is supported by empirical system knowledge, allowing us to test empirically the presumed decision-making and behavioral assumptions. The output is an array of sample agents with realistic (i.e. empirically quantified) decision-making and behavior. Results from a Swiss mineral construction material case study illustrate the information which can be derived by applying the proposed approach and demonstrate its practicability for context specific agent-based model development.Agent Operationalization, Decision-Making, Analytical Hierarchy Process (AHP), Agent-Based Modeling, Conceptual Validation

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

Urban Simulation Models: Contributions as Analysis-Methodology in a Project of Urban Renewal

The recent urban transformations produced in cities indicate the need to propose new theoretical and methodological approaches in physical planning. Based on the idea of complexity, it is required to integrate, in the analysis, multiplicity of interrelated factors involved in urban development,moreover, to develop planning tools that can incorporate variables not initially considered (for example when the norms were sanctioned) and instruments that would provide assessment alternatives to planning decisions in real time. The simulation models are suggested as tools to detect the elements, relationships and the dynamics in a simplified form that allow experiencing on the results. That is to say, a theoretical position on to a computer model is translated to investigate (in an experimental way) possible solutions derived from manipulating the variables, before the phenomenon is materialized. In the case of urban planning, this condition is of particular relevance, given the importance to anticipate unwanted effects in the intervention context that may arise when urban projects are built. The paper evaluates the application of a simulation methodology,based on the dynamics of systems and the application of software that can anticipate the effects of certain decisions in an urban renewal project in the city of Córdoba, Argentina. It applies the General Systems Theory that is a contribution to the notion of complex thought and is trans-disciplinary. Based on the idea of complex and multidimensional city, the effects of a real estate development are analyzed and conclusions on the limits and possibilities of using this tool during the processes of urban management are provided.Fil: Marengo, Maria Cecilia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Córdoba. Facultad de Arquitectura, Urbanismo y Diseño. Instituto de Investigación de la Vivienda; Argentin

Actors and factors - bridging social science findings and urban land use change modeling

Recent uneven land use dynamics in urban areas resulting from demographic change, economic pressure and the cities’ mutual competition in a globalising world challenge both scientists and practitioners, among them social scientists, modellers and spatial planners. Processes of growth and decline specifically affect the urban environment, the requirements of the residents on social and natural resources. Social and environmental research is interested in a better understanding and ways of explaining the interactions between society and landscape in urban areas. And it is also needed for making life in cities attractive, secure and affordable within or despite of uneven dynamics.\ud The position paper upon “Actors and factors – bridging social science findings and urban land use change modeling” presents approaches and ideas on how social science findings on the interaction of the social system (actors) and the land use (factors) are taken up and formalised using modelling and gaming techniques. It should be understood as a first sketch compiling major challenges and proposing exemplary solutions in the field of interest