Stanislaw Raczynski - Interacting Complexities of Herds and Social Organizations: Agent Based Modeling

The Japanese Association for Evolutionary Economics (JAFEE) always has adhered to its original aim of taking an explicit integrated approach. This path has been followed steadfastly since the Associations establishment in 1997 and, as well, since the inauguration of our international journal in 2004. We have deployed an agenda encompassing a contemporary array of subjects including but not limited to: foundations of institutional and evolutionary economics, criticism of mainstream views in the social sciences, knowledge and learning in socio-economic life, development and innovation of technologies, transformation of industrial organizations and economic systems, experimental studies in economics, agent-based modeling of socio-economic systems, evolution of the governance structure of firms and other organizations, comparison of dynamically changing institutions of the world, and policy proposals in the transformational process of economic life. In short, our starting point is an "integrative science" of evolutionary and institutional views. Furthermore, we always endeavor to stay abreast of newly established methods such as agent-based modeling, socio/econo-physics, and network analysis as part of our integrative links.

More fundamentally, evolution in social science is interpreted as an essential key word, i.e., an integrative and /or communicative link to understand and re-domain various preceding dichotomies in the sciences: ontological or epistemological, subjective or objective, homogeneous or heterogeneous, natural or artificial, selfish or altruistic, individualistic or collective, rational or irrational, axiomatic or psychological-based, causal nexus or cyclic networked, optimal or adaptive, micro- or macroscopic, deterministic or stochastic, historical or theoretical, mathematical or computational, experimental or empirical, agent-based or socio/econo-physical, institutional or evolutionary, regional or global, and so on. The conventional meanings adhering to various traditional dichotomies may be more or less obsolete, to be replaced with more current ones vis--vis contemporary academic trends. Thus we are strongly encouraged to integrate some of the conventional dichotomies.

These attempts are not limited to the field of economic sciences, including management sciences, but also include social science in general. In that way, understanding the social profiles of complex science may then be within our reach. In the meantime, contemporary society appears to be evolving into a newly emerging phase, chiefly characterized by an information and communication technology (ICT) mode of production and a service network system replacing the earlier established factory system with a new one that is suited to actual observations. In the face of these changes we are urgently compelled to explore a set of new properties for a new socio/economic system by implementing new ideas. We thus are keen to look for integrated principles common to the above-mentioned dichotomies throughout our serial compilation of publications. We are also encouraged to create a new, broader spectrum for establishing a specific method positively integrated in our own original way.

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According to John von Neumann, by a model is meant a mathematical construct which, with the addition of certain verbal interpretations, describes observed phenomena. The justification of such a mathematical construct is solely and precisely that it is expected to work that is, correctly to describe phenomena from a reasonably wide area. Humans always (sometimes unconsciously) have used models created in their brains. When our technical skills have grown, the models acquired the form of physical, scale models, drawings, and finally sophisticated logical and mathematical constructions. The common concept of modeling is defined as a scientific activity, the aim of which is to make a particular part or feature of the world easier to understand.

The complexity of the real world can be modeled to some extent. There are many definitions of complexity, recently related to system of systems structures. Note that a system that contains a great number of sub-systems or items or a huge number of differential equations is not necessarily complex. The complexity lies in the way the components interact with each other and the diversity of system components. In such systems, the simulation results may provide information about the behavior of the whole system, which is not the sum of individual behavior patterns. This is also interpreted as nonlinearity. This book is focused on this kind of modeling and simulation experiments.

Analog and digital computers gave us a powerful tool for model building and analysis. At the very beginning of the computer era, the differential equations have been solved on analog machines, helping scientists and engineers to design mechanisms, circuits, and complex devices. The field of model applications has grown over the decades, including not only the works of engineering and exact sciences but also the models of animal and human societies.