Collaborative Research: Computational Sustainability: Computational Methods for a Sustainable Environment, Economy, and Society

合作研究：计算可持续性：可持续环境、经济和社会的计算方法

• 批准号: 0832804
• 负责人: Thomas Dietterich
• 金额: $ 185.82万
• 依托单位: Oregon State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-08-15 至 2015-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0832804&HistoricalAwards=false
• 关键词: Collaborative; Research; Computational; Sustainability; Methods

Balancing environmental, economic, and societal needs for a sustainable future encompasses problems of unprecedented size and complexity. With naturally occuring settings, global scale, dynamic and uncertain behavior, mixture of discrete and continuous effects, and highly interactive components, problems associated with sustaining the earth's resources can greatly benefit from computational methods and thinking. There is a key role to be played by computing and information sciences in increasing the efficiency and effectiveness in the way humanity manages and allocates natural resources. Toward that objective, this Expedition aims to establish and nurture a new field of study--Computational Sustainability--driven by a wide range of hard computational problems and critical challenges in the area of sustainability. This applied theoretical Expedition will pursue interdisciplinary research across three computational sustainability themes: conservation and biodiversity; balancing socio-economic demands and the environment; and renewable energy. With the view that natural problems may have a special structure discoverable by machine learning techniques that allows them to be solved even though they are NP-hard, this research attempts to stimulating new research synergies that cross boundaries and merge ideas from combinatorial optimization, dynamical systems, machine learning and constraint reasoning. An "Institute for Computational Sustainability" will be based at Cornell to serve as the nexus of foundational science advancements and practical applications in sustainability. Part of its mission and outreach is to establish a vibrant and diverse research community in the area of computational sustainability, drawing new students into the field from all backgrounds including students from underrepresented groups via summer research experiences and other such proactive activities.

平衡环境、经济和社会需求以实现可持续的未来面临着前所未有的规模和复杂性问题。 由于自然发生的环境、全球规模、动态和不确定的行为、离散和连续效应的混合以及高度交互的成分，与维持地球资源相关的问题可以极大地受益于计算方法和思维。 计算和信息科学在提高人类管理和分配自然资源的效率和有效性方面发挥着关键作用。 为了实现这一目标，本次探险旨在建立和培育一个新的研究领域——计算可持续性——由可持续性领域的一系列硬计算问题和关键挑战驱动。 这次应用理论考察将在三个计算可持续性主题上进行跨学科研究：保护和生物多样性；平衡社会经济需求和环境；和可再生能源。 鉴于自然问题可能具有可通过机器学习技术发现的特殊结构，即使它们是 NP 困难的，也可以解决它们，本研究试图激发新的研究协同作用，跨越边界并融合来自组合优化、动力系统的想法、机器学习和约束推理。 康奈尔大学将设立一个“计算可持续性研究所”，作为可持续性基础科学进步和实际应用的纽带。 其使命和外展活动的一部分是在计算可持续性领域建立一个充满活力和多元化的研究社区，通过暑期研究经验和其他此类主动活动吸引来自各种背景的新学生进入该领域，包括来自代表性不足群体的学生。