A Broad Research Program in the Sciences of Complexity

点击翻译按钮获取中文摘要

The Santa Fe Institute (SFI) will build significantly upon its successes to date in conducting transdisciplinary research toward understanding the complex behaviors arising in systems composed of relatively simple, highly interacting components. Specifically, SFI will study the emergent behaviors of real complex systems whose components are themselves complex-genetic regulatory networks, financial markets and social institutions for example-through mathematical investigation and simulation in concert with empirical studies and data analysis. Researchers involved in these activities will come from many disciplines, including biology, physics, mathematics, computation, and the social behavioral, and economic sciences.Integration and synthesis underlie this research, which is thus complementary to the more well-established methods of reduction and analysis that characterize disciplinary science. It is, of course, essential that complex systems such as the immune system or the global economy be decomposed into their constituent parts and that the behavior of these parts be elucidated as completely as possible for the subsequent understanding of the system as a whole. But in addition to understanding these constituents, understanding of their collective organization is required. It is necessary to refer separately to the parts and their organization to call attention to the fact that the properties of the parts alone do not uniquely determine their collective organization; there are many organizational structures possible with the same parts. Furthermore, the observed organization, or the emergent collective entity, is itself perpetuated independently of its parts. Thus, a market persists even as the individual traders turn over, an ecosystem persists even as the organisms die and are replaced, a cell persists, though its molecules degrade. SFI will further develop the fertile concept of emergence by strengthening the theoretical understanding of emergence through rigorous mathematical study direct and by intensive study of empirical data from specific real-world complex phenomena, including: Structure and Dynamics of Networks, Novelty in Evolution, Computation in Nature, Market Evolution, and Human Behavior and the Emergent Properties of Social Structures.