Pluralistic Modeling of Complex Systems
Total Page：16
File Type：pdf, Size：1020Kb
PERSPECTIVES PLURALISTIC MODELING OF COMPLEX SYSTEMS DIRK HELBING*† The modeling of complex systems such as ecological or socio-economic systems can be very challenging. Although various modeling approaches exist, they are generally not compatible and mutually consistent, and empirical data often do not allow one to decide what model is the right one, the best one, or most appropriate one. Moreover, as the recent financial and economic crisis shows, relying on a single, idealized model can be very costly. This contribution tries to shed new light on problems that arise when complex systems are modeled. While the arguments can be transferred to many different systems, the related scientific challenges are illustrated for social, economic, and traffic systems. The contribution discusses issues that are sometimes overlooked and tries to overcome some frequent misunderstandings and controversies of the past. At the same time, it is highlighted how some long-standing scientific puzzles may be solved by considering non-linear models of heterogeneous agents with spatio-temporal interactions. As a result of the analysis, it is concluded that a paradigm shift towards a pluralistic or possibilistic modeling approach, which integrates multiple world views, is overdue. In this connection, it is argued that it can be useful to combine many different approaches to obtain a good picture of reality, even though they may be inconsistent. Finally, it is identified what would be profitable areas of collaboration between the socio-economic, natural, and engineering sciences. Introduction complexity or network scientists. Researchers from the hen the “father of sociology”, August Comte, social sciences, physics, computer science, biology, came up with the idea of a “social physics”, he mathematics, and artificial intelligence research are Whoped that the puzzles of social systems could addressing the challenges of social and economic systems be revealed with a natural science approach1 . However, with mathematical or computational models and lab or web progress along these lines was very difficult and slow. experiments. Will they end up with resignation in view of Today, most sociologists do not believe in his positivistic the complexity of social and economic systems, or will they approach anymore. The question is whether this proves the manage to push our knowledge of social systems failure of the positivistic approach or whether it just shows considerably beyond what was imaginable even a decade that social scientists did not use the right methods so far. ago? Will August Comte’s vision of sociology as “the 2 After all, social scientists rarely have a background in the queen of the sciences” finally become true? natural sciences, while the positivistic approach has been My own judgement is that it is less hopeless to develop most successful in fields like physics, chemistry, or biology. mathematical models for social systems than most social In fact, recently new scientific communities are scientists usually think, but more difficult than most natural developing, and they are growing quickly. They call scientists imagine. The crucial question is, how substantial themselves socio-physicists, mathematical sociologists, progress in a field as complicated and multi-faceted as the computational social scientists, agent-based modelers, social sciences can be made, and how the current obstacles can be overcome? Moreover, what are these obstacles, after * ETH Zurich, CLU, Clausiusstr. 50, 8092 Zurich, Switzerland all? The current contribution tries to make the controversial † Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501, USA, E-mail: [email protected] issues better understandable to scientific communities with VOL. 76, NOS. 9–10 315 different approaches and backgrounds. While each of the molecules, which may form solid bodies, fluids or gases, points may be well-known to some scientists, they are which together make up our planet, which belongs to a probably not so obvious for others. Putting it differently, solar system, and a galaxy. In biology, cells are composed this contribution tries to build bridges between different of organelles, they form tissues and organs, which are the disciplines interested in similar subjects, and make thoughts constituting parts of living creatures, and these make up understandable to scientific communities with different ecosystems. points of views. Such analogies are certainly interesting and have been A dialogue between social, natural and economic discussed, for example, by Herbert Spencer5 and later on in sciences seems to be desirable not only for the sake of an systems theory6 . It is not so obvious, however, how much intellectual exchange on fundamental scientific problems. It one can learn from them. While physical systems are often also appears that science is lacking behind the pace of well understood by mathematical models, biological and upcoming socio-economic problems, and that we need to socio-economic systems are usually not. This often inspires become more efficient in addressing practical problems3 . physicists to transfer their models to biological and socio- President Lee C. Bollinger of New York’s prestigious economic problems (see the discussion in the section “The Columbia University formulated the challenge as follows: Model Captures Some Features...”), while biologists, social “The forces affecting societies around the world ... are scientists, and economists often find such attempts powerful and novel. The spread of global market systems ... “physicalistic” and inadequate. In fact, social and economic are ... reshaping our world ..., raising profound questions. systems possess a number of properties, which distinguish These questions call for the kinds of analyses and them from most physical ones: understandings that academic institutions are uniquely 1. the number of variables involved is typically capable of providing. Too many policy failures are (much) larger (considering that each human brain 4 fundamentally failures of knowledge.” contains about 1000 billion neurons), The fundamental and practical scientific challenges 2. the relevant variables and parameters are often require from us that we do everything we can to find unknown and hard to measure (the existence of solutions, and that we do not give up before the limits or “unknown unknowns” is typical), failure of a scientific approach have become obvious. As will be argued in the Discussion and Outlook, different 3. the time scales on which the variables evolve are methods should be seen complementary to each other and, often not well separated from each other, even when inconsistent, may allow one to get a better 4. the statistical variation of measurements is picture than any single method can do, no matter how considerable and masks laws of social behavior, powerful it may seem. where they exist (if they exist at all), 5. frequently there is no ensemble of equivalent Particular Difficulties of Modeling Socio- systems, but just one realization (one human Economic Systems history), When speaking about socio-economic systems in the 6. empirical studies are limited by technical, following, it could be anything from families over social financial, and ethical issues, groups or companies up to countries, markets, or the world 7. it is difficult or impossible to subdivide the system economy including the financial system and the labor into simple, non-interacting subsystems that can be market. The constituting system elements or system separately studied, components would be individuals, groups, or companies, for example, depending on the system under consideration 8. the observer participates in the system and and the level of description one is interested in. modifies social reality, On the macroscopic (systemic) level, social and 9. the non-linear and/or network dependence of many economic systems have some features that seem to be variables leads to complex dynamics and similar to properties of certain physical or biological structures, and sometimes paradoxical effects, systems. One example is the hierarchical organization. In 10. interaction effects are often strong, and emergent social systems, individuals form groups, which establish phenomena are ubiquitous (hence, not organizations, companies, parties, etc., which make up understandable by the measurement and states, and these build communities of states (like the quantification of the individual system elements), United States or the European Union, for example). In 11. factors such as a large degree of randomness and physics, elementary particles form atoms, which create heterogeneity, memory, anticipation, decision- 316 SCIENCE AND CULTURE, SEPTEMBER-OCTOBER, 2010 making, communication, consciousness, and the of intellectual digestion, and the first and very essential one relevance of intentions and individual is to create a picture of the system one is interested in and interpretations complicate the analysis and to make sense of what is going on in it. This step is clearly modeling a lot, indispensible. Nevertheless, the approach is sometimes 12. the same applies to human features such as criticized for reasons such as the following: emotions, creativity, and innovation, l Observation, description, and interpretation are 13. the impact of information is often more decisive difficult to separate from each other, since they are for the behavior of a socio-economic system than typically performed by the same brain (of a single physical aspects (energy,