A Broad Research Program in the Sciences of Complexity

圣达菲研究所(SFI)是一家私人独立研究机构，致力于物理、计算、生物和社会科学领域的长期、创造性、跨学科研究。SFI专注于跨尺度的基本科学问题，可以通过量化思维、数学建模和经验数据分析来解决这些问题。该奖项支持圣达菲研究所(SFI)在复杂性科学领域的多学科综合核心研究计划的五年持续支持。该奖项将为SFI的访问科学家计划、研讨会计划、博士后和研究生研究员以及教育活动提供部分支持。支持的工作涵盖以下广泛领域：1.复杂系统物理学：SFI的基础物理学跨越了量子力学和统计力学、信息论、非线性动力学和混沌以及离散系统的原理。这些领域提供了在整个科学领域都有用的解决问题的技术和方法，并作为认识新原则的出发点。目前SFI在物理学方面的研究包括：侧重于自组织状态和非传统统计的统计物理学；量子力学和量子信息与控制的基础；具有广泛应用的网络结构和动力学；以及社会和生物系统的定标和寻找定量的预测理论。复杂系统中的计算：SFI在计算方面的研究包括在进化和自适应计算、理解物理和计算之间的关系、分布式和基于集体代理的计算模型以及将生物学见解应用于工程计算系统方面做出的开创性贡献。目前的工作将扩大SFI在物理和计算、生物系统计算以及生物启发的计算问题解决方案领域的贡献。进化系统中的创新：进化创新是进化克服了人口增长和支持人口所需资源增长之间的差异的手段。因此，创新具有重大的理论和实践意义。SFI关于创新的研究广泛涉及两个问题：解释生物和技术系统中形式的多样性和复杂性；以及发展形式之间的过渡理论。生命系统的出现、组织和动态：SFI对生命系统的研究包括：早期地球地球化学的新陈代谢起源；人工有机体中能量捕获、繁殖和突变的整合；最小生命形式的创造；指导生态系统建设、稳定性和测量的核心原则；在社会层面提供稳定性的机制；以及系统发育方法在艾滋病毒疫苗开发中的应用。人类行为和制度的动态：SFI持续的研究重点是社会制度的出现、持续和消亡，以及它们与独特的人类行为的共同进化，例如利他主义合作、群体外敌意和适应性学习，这些行为在标准经济学和其他行为科学模型中通常被忽视。

The Santa Fe Institute (SFI) is a private, independent research institute dedicated to long-term, creative, trans-disciplinary research across the physical, computational, biological and social sciences. SFI focuses on fundamental scientific problems that cross scales and can be addressed by quantitative thinking, mathematical modeling and empirical data analyses. This award supports five years of continued support for the Sante Fe Institute's (SFI) multi-disciplinary Integrative Core research program in the sciences of complexity. The award will provide partial support for SFI's visiting scientist program, workshop program, postdoctoral and graduate fellows, and educational activities. The supported work covers the following broad areas:1. Physics of Complex Systems: Fundamental physics at SFI has spanned the principles of quantum and statistical mechanics, information theory, nonlinear dynamics and chaos, and discrete systems. These fields have provided techniques and approaches to problem solving that are useful across the sciences, and served as points of departure for the recognition of new principles. Current SFI research in physics includes: statistical physics with emphasis on self-organized states and non-conventional statistics; foundations of quantum mechanics and quantum information and control; network structure and dynamics with a wide variety of applications; and scaling and the search for quantitative, predictive theories of social and biological systems.2. Computation in Complex Systems: SFI's research in computation has included seminal contributions in evolutionary and adaptive computation, in understanding relationships between physics and computation, in models of distributed and collective agent-based computation, and in applications of biological insights to engineered computational systems. The current work will extend SFI's contributions in the areas of physics and computation, computation in biological systems, and biologically inspired solutions to computational problems.3. Innovation in Evolutionary Systems: Evolutionary innovations are the means by which evolution has overcome the differential between the growth of populations and the growth of the resources needed to support them. Innovation is consequently of substantial theoretical and practical concern. Research at SFI on innovation is broadly concerned with two issues: accounting for the diversity and complexity of forms in biological and technological systems; and developing a theory of transitions among forms.4. Emergence, Organization, and Dynamics of Living Systems: Research on living systems at SFI includes: the origin of metabolism from early-earth geochemistry; the integration of energy capture, reproduction, and mutation in artificial organisms; the creation of minimal forms of life; the core principles governing ecosystem construction, stability, and measurement; the mechanisms providing stability at the social level; and applications of phylogenetic methods to vaccine development for HIV.5. Dynamics of Human Behavior and Institutions: A continuing SFI research focus is the emergence, persistence, and demise of social institutions and their co-evolution with distinctive human behaviors, such as altruistic cooperation, out-group hostility and adaptive learning, that are typically overlooked in standard economics and other behavioral science models.