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(7 articles matched your search)

Stylised Facts and the Contribution of Simulation to the Economic Analysis of Budgeting

Bernd-O. Heine, Matthias Meyer and Oliver Strangfeld
Journal of Artificial Societies and Social Simulation 8 (4) 4

Abstract: The application of computer simulation as a research method raises two important questions: (1) Does simulation really offer added value over established methods? (2) How can the danger of arbitrariness caused by the extended modelling possibilities be minimised? We present the concept of stylised facts as a methodological basis for approaching these questions systematically. In particular, stylised facts provide a point of reference for a comparative analysis of models intended to explain an observable phenomenon. This is shown with reference to a recent discussion in the "economic analysis of accounting" literature where established methods, i.e. game theory, as well as computer simulations are used: the susceptibility of the "Groves mechanism" to collusion. Initially, we identify six stylised facts on the stability of collusion in empirical studies. These facts serve as a basis for the subsequent comparison of four theoretical models with reference to the above questions: (1) We find that the simulation models of Krapp and Deliano offer added value in comparison to the game theoretical models. They can be related to more stylised facts, achieve a better reproduction and exhibit far greater potential for incorporating yet unaddressed stylised facts. (2) Considered in the light of the stylised facts to which the models can be related, Deliano's simulation model exhibits considerable arbitrariness in model design and lacks information on its robustness. In contrast, Krapp demonstrates that this problem is not inherent to the method. His simulation model methodically extends its game theoretical predecessors, leaving little room for arbitrary model design or questionable parameter calibration. All in all, the stylisedfactsconcept proved to be very useful in dealing with the questions simulation researchers are confronted with. Moreover, a "research landscape" emerges from the derived stylised facts pinpointing issues yet to be addressed.

A Generic Approach to an Object-Oriented Learning Classifier System Library

Matthias Meyer and Klaus Hufschlag
Journal of Artificial Societies and Social Simulation 9 (3) 9

Abstract: Learning Classifier Systems (LCS) have gained popularity in the realm of social science simulation. However, when it comes to actually constructing a LCS for a particular modelling purpose, it seems that every researcher must currently "reinvent the wheel". Taking this situation as a starting point, the objective of this paper is to present the basic ideas behind a LCS library, which can relieve simulation researchers of some of the technical work and can provide a generic structure for modelling LCS. The library is based on a strictly object-oriented approach. This provides flexibility in the process of constructing a LCS for a specific modelling purpose and encourages experimentation with various different assumptions. The paper is supported with examples based on experience in using the library.

The Development of Social Simulation as Reflected in the First Ten Years of JASSS: a Citation and Co-Citation Analysis

Matthias Meyer, Iris Lorscheid and Klaus G. Troitzsch
Journal of Artificial Societies and Social Simulation 12 (4) 12

Abstract: Social simulation is often described as a multidisciplinary and fast-moving field. This can make it difficult to obtain an overview of the field both for contributing researchers and for outsiders who are interested in social simulation. The Journal for Artificial Societies and Social Simulation (JASSS) completing its tenth year provides a good opportunity to take stock of what happened over this time period. First, we use citation analysis to identify the most influential publications and to verify characteristics of social simulation such as its multidisciplinary nature. Then, we perform a co-citation analysis to visualize the intellectual structure of social simulation and its development. Overall, the analysis shows social simulation both in its early stage and during its first steps towards becoming a more differentiated discipline.

Bibliometrics, Stylized Facts and the Way Ahead: How to Build Good Social Simulation Models of Science?

Matthias Meyer
Journal of Artificial Societies and Social Simulation 14 (4) 4

Abstract: This paper discusses how stylized facts derived from bibliometric studies can be used to build social simulation models of science. Based on a list of six stylized facts of science it illustrates how they can be brought into play to consolidate and direct research. Moreover, it discusses challenges such a stylized facts based approach of modeling science has to solve.

Recent Development of Social Simulation as Reflected in JASSS Between 2008 and 2014: A Citation and Co-Citation Analysis

Jonas Hauke, Iris Lorscheid and Matthias Meyer
Journal of Artificial Societies and Social Simulation 20 (1) 5

Abstract: The research field of social simulation comprises many topics and research directions. A previous study about the early years indicated that the community has evolved into a differentiated discipline. This paper investigates the recent development of social simulation as reflected in Journal of Artificial Societies and Social Simulation (JASSS) publications from 2008 to 2014. By using citation analysis, we identify the most influential publications and study the characteristics of citations. Additionally, we analyze the development of the field with respect to research topics and their structure in a co-citation analysis. The citation characteristics support the continuing highly multidisciplinary character of JASSS. Prominently cited are methodological papers and books, standards, and NetLogo as the main simulation tool. With respect to the focus of this research, we observe continuity in topics such as opinion dynamics and the evolution of cooperation. While some topics disappeared such as learning, new subjects emerged such as marriage formation models and tools and platforms. Overall, one can observe a maturing inter- and multidisciplinary scientific community in which both methodological issues and specific social science topics are discussed and standards have emerged.

Comparing Prediction Market Mechanisms: An Experiment-Based and Micro Validated Multi-Agent Simulation

Frank M. A. Klingert and Matthias Meyer
Journal of Artificial Societies and Social Simulation 21 (1) 7

Abstract: Prediction markets are a promising instrument for drawing on the “wisdom of the crowds”. For instance, in a corporate context they have been used successfully to forecast sales or project risks by tapping into the heterogeneous information of decentralized actors in and outside of companies. Among the main market mechanisms implemented so far in prediction markets are (1) the continuous double auction and (2) the logarithmic market scoring rule. However, it is not fully understood how this choice affects crucial variables like prediction market accuracy or price variation. Our paper uses an experiment-based and micro validated simulation model to improve the understanding of the mechanism-related effects and to inform further laboratory experiments. The results underline the impact of mechanism selection. Due to the higher number of trades and the lower standard deviation of the price, the logarithmic market scoring rule seems to have a clear advantage at a first glance. This changes when the accuracy level, which is the most important criterion from a practical perspective, is used as an independent variable; the effects become less straightforward and depend on the environment and actors. Besides these contributions, this work provides an example of how experimental data can be used to validate agent strategies on the micro level using statistical methods.

Theory Development Via Replicated Simulations and the Added Value of Standards

Jonas Hauke, Sebastian Achter and Matthias Meyer
Journal of Artificial Societies and Social Simulation 23 (1) 12

Abstract: Using the agent-based model of Miller et al. (2012), which depicts how different types of individuals’ memory affect the formation and performance of organizational routines, we show how a replicated simulation model can be used to develop theory. We also assess how standards, such as the ODD (Overview, Design concepts, and Details) protocol and DOE (design of experiments) principles, support the replication, evaluation, and further analysis of this model. Using the verified model, we conduct several simulation experiments as examples of different types of theory development. First, we show how previous theoretical insights can be generalized by investigating additional scenarios, such as mergers. Second, we show the potential of replicated simulation models for theory refinement, such as analyzing in-depth the relationship between memory functions and routine performance or routine adaptation.