CDI Type II: Cyber-Enabled Understanding of Complexity in Socio-Ecological Systems via Computational Thinking

该项目将通过应用集成了进化计算算法的网络多智能体系统模型，促进对气候-社会动态复杂性的理解。该研究将开发、验证和分析新的基于计算主体的模型，作为模拟人类社会的变革性工具，这些社会在空间上位于具有不同生态系统和明确气候动力学的地区。这套新模型将重点关注气候变化对人类和生态系统产生重大影响的两个地理区域：撒哈拉以南非洲（超过10亿人面临流离失所、疾病和饥饿的高风险）和北极圈地区（这里的生态变化速度最快，变化模式与早期的重大气候事件相当）。该项目在人类学家、政治学家、地球科学家和计算机科学家之间建立了跨学科的合作，以推进复杂适应系统的科学。该项目的核心智力价值在于，通过创建一个用于建模、模拟和探索情景的网络集成计算框架，有助于对气候-社会动力学多尺度复杂性的基本理解。将创建空间多主体系统，其中包括气候动态以及其他自然灾害和压力因素，对家庭和治理机构组成的社会动态产生直接和间接影响。该项目的更广泛影响将包括(1)对气候-社会动力学的新的跨学科理解；(2)新的计算工具；(3)利用这些工具进行情景分析，获得与政策相关的新见解；(4)混合计算建模新高级形式的创新，实现跨学科的新合作；(5)通过复杂社会生态系统的计算建模，为创新的教学、培训和学习形式提供新的支持；(6)通过课堂参观和博物馆展览，为弱势群体的学生提供多所学校的机会。所有电子材料（代码和数据）的永久存档将通过史密森尼数据存档计划实施。

This project will advance understanding of complexity in climate-societal dynamics by applying cyber-enabled multiagent systems models integrated with evolutionary computation algorithms. The research will develop, validate, and analyze new computational agent-based models as transformative tools for simulating human societies spatially situated in regions with diverse ecosystems and explicit climate dynamics. The new suite of models will focus on two geographic regions where climate change has significant consequences for humans and ecosystems: Sub-Saharan Africa (over a billion people at high risk of displacement, disease, starvation) and the Arctic Circumboreal region (where the fastest ecological changes are now occurring with shifting patterns comparable to earlier major climate events). The project forges interdisciplinary collaboration among anthropologists, political scientists, earth scientists, and computer scientists to advance the science of complex adaptive systems. The core intellectual merit of the project is its contribution to basic understanding of multiscale complexity in climate-society dynamics, by creating a cyber-enabled integrated computational framework for modeling, simulating, and exploring scenarios. Spatial multiagent systems will be created that include climate dynamics as well as other natural hazards and stressors with direct and indirect effects on social dynamics composed of households and governance institutions. Broader impacts from this project will include (1) new cross-disciplinary understanding of climate-society dynamics, (2) new computational tools; (3) new policy-relevant insights derived via scenario analysis with such tools; (4) innovations in new advanced forms of hybrid computational modeling, enabling new collaborations across disciplines; (5) new support for innovative forms of teaching, training, and learning through computational modeling of complex socio-ecological systems; (6) and multi-institutional opportunities for students from underrepresented groups via classroom visits and museum exhibits. Perpetual archiving of all electronic materials (code and data) will be implemented through the Smithsonian data archiving initiative.