Agent-Based Models and Simulations in Economics and Social Sciences: from conceptual exploration to distinct ways of experimenting

Now that complex Agent-Based Models and computer simulations spread over economics and social sciences - as in most sciences of complex systems -, epistemological puzzles (re)emerge. We introduce new epistemological tools so as to show to what precise extent each author is right when he focuses on some empirical, instrumental or conceptual significance of his model or simulation. By distinguishing between models and simulations, between types of models, between types of computer simulations and between types of empiricity, section 2 gives conceptual tools to explain the rationale of the diverse epistemological positions presented in section 1. Finally, we claim that a careful attention to the real multiplicity of denotational powers of symbols at stake and then to the implicit routes of references operated by models and computer simulations is necessary to determine, in each case, the proper epistemic status and credibility of a given model and/or simulation

Agent-Based Models and Simulations in Economics and Social Sciences

Now that complex Agent-Based Models and computer simulations spread over economics and social sciences - as in most sciences of complex systems -, epistemological puzzles (re)emerge. We introduce new epistemological concepts so as to show to what extent authors are right when they focus on some empirical, instrumental or conceptual significance of their model or simulation. By distinguishing between models and simulations, between types of models, between types of computer simulations and between types of empiricity obtained through a simulation, section 2 gives the possibility to understand more precisely - and then to justify - the diversity of the epistemological positions presented in section 1. Our final claim is that careful attention to the multiplicity of the denotational powers of symbols at stake in complex models and computer simulations is necessary to determine, in each case, their proper epistemic status and credibility.Agent-Based Models and Simulations ; Epistemology ; Economics ; Social Sciences ; Conceptual Exploration ; Model World ; Credible World ; Experiment ; Denotational Hierarchy

Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: NL

Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: N

Domain-specific reasoning for method engineering based on Toulmin's argumentation theory

Methods describe and embody a broad range of relevant knowledge of enterprises. Usually they have to account for requirements stated by a multitude of various stakeholders. These are typically those that are in charge of business related actions and those that are in charge to support such actions with an IT-Infrastructure. The statement of requirements as well as the validation of methods and in particular process models with respect to those requirements relies drastically on natural language. Natural language seems to be a substantial component to explain and to give an understanding about process models or certain aspects of it. This fact requires closing the gap between the natural language and the respective modelling language. This paper proposes argumentative method engineering for purposefully depicting design decisions and convictions for method engineering through arguments. The approach is derived from Toulmin’s Argumentation Model and explicates the process of negotiating with various stakeholders. So, a model, depicting a method, specified by means of argumentative method engineering, not just includes the claims about a certain domain, it further justifies these claims by referring to already established knowledge. While it can’t be ensured that certain requirements are considered in future project, if the reasons for design decisions of method engineering are transcribed in natural language text, but the semi- formalising of arguments regarding these methods allows such an assurance. So the argumentative approach enables the sophisticated management and reuse of knowledge during the development and extension of methods. The approach is evaluated using a case study, in which a software development method was outsourced to contractors

Method Engineering as Design Science

In this paper, we motivate, devise, demonstrate, and evaluate an approach for the research-based development of information systems development methods (ISDMs). This approach, termed “method engineering as design science” (ME-DS), emerged from the identified need for scholars to develop ISDMs using proper research methods that meet the standards of both rigor and relevance. ISDMs occupy a position of central importance to information systems development and scholars have therefore invested extensive resources over the years in developing such methods. The method engineering (ME) discipline has developed different frameworks and methods to guide such development work and, for that purpose, they are well-suited. Still, there remains a need for applications and evaluations of ISDMs based on the demands for knowledge justification. Unfortunately, in many cases, scholars come up short with regard to how ISDMs are generated and empirically validated. While design science (DS) stresses knowledge justification, prominent DS approaches seem to be biased toward the development of IT artifacts, making this approach ill-suited for the development of method artifacts. We therefore propose eight principles that marry ME and DS, resulting in a process model with six activities to support research-based development of ISDMs. We demonstrate and evaluate ME-DS by assessing three existing research papers that propose ISDMs. These retrospectives show how ME-DS directs attention to certain aspects of the research process and provides support for future ISDM development

Argumentative Landscapes: The Functions of Models in Social Epistemology

We argue that the appraisal of models in social epistemology requires conceiving of them as argumentative devices, taking into account the argumentative context and adopting a family-of-models perspective. We draw up such an account and show how it makes it easier to see the value and limits of the use of models in social epistemology. To illustrate our points, we document and explicate the argumentative role of epistemic landscape models in social epistemology and highlight their limitations. We also claim that our account could be fruitfully used in appraising other models in philosophy and science

Domain-specific reasoning for method engineering based on Toulmin's argumentation theory

Methods describe and embody a broad range of relevant knowledge of enterprises. Usually they have to account for requirements stated by a multitude of various stakeholders. These are typically those that are in charge of business related actions and those that are in charge to support such actions with an IT-Infrastructure. The statement of requirements as well as the validation of methods and in particular process models with respect to those requirements relies drastically on natural language. Natural language seems to be a substantial component to explain and to give an understanding about process models or certain aspects of it. This fact requires closing the gap between the natural language and the respective modelling language. This paper proposes argumentative method engineering for purposefully depicting design decisions and convictions for method engineering through arguments. The approach is derived from Toulmin’s Argumentation Model and explicates the process of negotiating with various stakeholders. So, a model, depicting a method, specified by means of argumentative method engineering, not just includes the claims about a certain domain, it further justifies these claims by referring to already established knowledge. While it can’t be ensured that certain requirements are considered in future project, if the reasons for design decisions of method engineering are transcribed in natural language text, but the semi- formalising of arguments regarding these methods allows such an assurance. So the argumentative approach enables the sophisticated management and reuse of knowledge during the development and extension of methods. The approach is evaluated using a case study, in which a software development method was outsourced to contractors

Argumentative Landscapes: The Functions of Models in Social Epistemology

We argue that the appraisal of models in social epistemology requires conceiving of them as argumentative devices, taking into account the argumentative context and adopting a family-of-models perspective. We draw up such an account and show how it makes it easier to see the value and limits of the use of models in social epistemology. To illustrate our points, we document and explicate the argumentative role of epistemic landscape models in social epistemology and highlight their limitations. We also claim that our account could be fruitfully used in appraising other models in philosophy and science

Exploring Scientific Inquiry via Agent-Based Modeling

In this paper I examine the epistemic function of agent-based models (ABMs) of scientific inquiry, proposed in the recent philosophical literature. In view of Boero and Squazzoni's (2005) classification of ABMs into case-based models, typifications and theoretical abstractions, I argue that proposed ABMs of scientific inquiry largely belong to the third category. While this means that their function is primarily exploratory, I suggest that they are epistemically valuable not only as a temporary stage in the development of ABMs of science, but by providing insights into theoretical aspects of scientific rationality. I illustrate my point with two examples of highly idealized ABMs of science, which perform two exploratory functions: Zollman's (2010) ABM which provides a proof-of-possibility in the realm of theoretical discussions on scientific rationality, and ArgABM (Borg et al., 2017b, 2018a,b), which provides insights into potential mechanisms underlying the efficiency of scientific inquiry