A Broad Research Program in the Sciences of Complexity

圣菲研究所（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专注于跨尺度的基础科学问题，可以通过定量思维、数学建模和经验数据分析来解决。该奖项支持了圣菲研究所（SFI）在复杂性科学领域的多学科综合核心研究项目的五年持续支持。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。支助的工作包括以下广泛领域：复杂系统物理学：SFI的基础物理学涵盖了量子和统计力学、信息论、非线性动力学和混沌以及离散系统的原理。这些领域提供了解决问题的技术和方法，这些技术和方法在各个科学领域都很有用，并作为认识新原则的出发点。当前SFI在物理学方面的研究包括：以自组织态和非常规统计为重点的统计物理学；量子力学基础与量子信息与控制；网络结构和动态具有广泛的应用；以及对社会和生物系统的定量预测理论的研究。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方面的开创性贡献，在理解物理与计算之间的关系方面，在分布式和基于集体代理的计算模型方面，以及在生物洞察力在工程计算系统中的应用方面。目前的工作将扩展SFI在物理和计算、生物系统计算以及计算问题的生物学启发解决方案等领域的贡献。进化系统中的创新：进化创新是一种手段，通过这种手段，进化克服了人口增长与支持人口增长所需资源增长之间的差异。因此，创新具有重要的理论和实践意义。SFI关于创新的研究主要涉及两个问题：解释生物和技术系统中形式的多样性和复杂性；并发展了一种形式转换理论。生命系统的出现、组织和动力学：SFI对生命系统的研究包括：早期地球化学代谢的起源；人工生物体中能量捕获、繁殖和突变的整合；创造最小形式的生命；生态系统建设、稳定性和测度的核心原则；在社会一级提供稳定的机制；以及系统发育方法在HIV.5疫苗开发中的应用。人类行为和制度的动力学：SFI的一个持续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（如利他合作、群体外敌意和适应性学习）的共同进化，这些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.