Modeling Caribou Migrations and Traditional Hunting Strategies in a Virtual World Simulation

在虚拟世界模拟中对驯鹿迁徙和传统狩猎策略进行建模

• 批准号: 1744367
• 负责人: John O'Shea
• 金额: $ 16.88万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1744367&HistoricalAwards=false
• 关键词: Modeling; Caribou; Migrations; Traditional; Hunting

Caribou are one of the most significant animals in the Arctic. They are intimately tied to the people, history, and ecology of the region. This project will bring together archaeologists, computer scientists, geographers, ecologists and Alaska Native rights holders to investigate caribou migrations prior to the dramatic reduction in caribou numbers during the 18th Century. A unique aspect of this project is the creation of a virtual world model of the past environment for a portion of ancient Alaska. The researchers will then ask experienced Alaska Native hunters to enter the virtual world to seek migrating caribou under different conditions. Using virtual reality googles and similar equipment, the hunters will be able to experience the model world as if they were actually there. By following their movements and listening to their descriptions the researchers will be able tell how well the model is simulating reality. By comparing the model with the hunting locations chosen by ancient hunters known from archaeology, the research team hopes to see how conditions of the environment and of caribou numbers have changed over time. In addition to informing us about the past, the model will provide a valuable new tool for ecologists to think about caribou migrations and how they might be altered in response to future oil and gas development within the region. Beyond the scientific value of the research, the inclusion of Alaska Native communities in the design process will provide an opportunity for them to inform the model. The gaming format developed from the model will provide a valuable (and easily accessible) educational tool for K-12 students in Alaska, encourage interest in science and technology (STEM) among Alaska Native students, and provide opportunities for the involvement citizen scientists more broadly.In consultation with Alaska Native communities and local experts the research team will adapt a virtual world model of caribou migration developed for the Early Holocene period in the Great Lakes region and apply it to a portion of modern Alaska. The present proposal has two main goals. To allow the research team to become acquainted with the Arctic context of the research and to establish the necessary collaborative contacts particularly among Alaska Native scholars, to ground the virtual world simulation in Alaska. Second, to recruit one or more Alaska Native hunters to experience the current virtual world simulation via an immersive augmented reality system. The placing of knowledgeable hunters within a virtual world simulation as a means of exploring the interactions of human actors in modeled environments is an emerging approach to behavioral research in many fields, and this will be among the first systematic applications of the approach to anthropology. Through these activities, the research team will verify the basic elements of the virtual world simulation and fine tune the augmented reality system for recording the movements and comments of the hunters as they traverse the model landscape. These results will also provide important data for better understanding the Early Holocene occupation of the Great Lakes region and will highlight differences in hunting strategies and tactics observed in recent and ancient times. The work will also lay the foundation for a systematic remote sensing survey of built hunting structures (both recent and ancient) in an archaeologically under-research portion of Alaska.

驯鹿是北极最重要的动物之一。它们与该地区的人民、历史和生态息息相关。该项目将汇集考古学家、计算机科学家、地理学家、生态学家和阿拉斯加原住民权利持有人，调查18世纪驯鹿数量急剧减少之前的驯鹿迁徙。这个项目的一个独特方面是为古阿拉斯加的一部分创建了一个过去环境的虚拟世界模型。然后，研究人员将让经验丰富的阿拉斯加原住民猎人进入虚拟世界，在不同的条件下寻找迁徙的驯鹿。使用虚拟现实谷歌和类似的设备，猎人将能够体验模型世界，就像他们真的在那里一样。通过跟踪他们的动作和听他们的描述，研究人员将能够看出该模型模拟现实的程度。通过将该模型与考古学中已知的古代猎人选择的狩猎地点进行比较，研究小组希望看到环境条件和驯鹿数量随着时间的推移发生了怎样的变化。除了告诉我们过去的情况外，该模型还将为生态学家提供一个有价值的新工具，让他们思考驯鹿的迁徙以及如何改变它们，以应对该地区未来的石油和天然气开发。除了研究的科学价值，将阿拉斯加原住民社区纳入设计过程将为他们提供一个向模型提供信息的机会。由该模型开发的游戏形式将为阿拉斯加的K-12学生提供一个有价值的(且易于获取的)教育工具，鼓励阿拉斯加土著学生对科学和技术(STEM)的兴趣，并为更广泛的公民科学家的参与提供机会。在与阿拉斯加土著社区和当地专家协商后，研究小组将修改为大湖区全新世早期开发的驯鹿迁徙的虚拟世界模型，并将其应用于现代阿拉斯加的一部分。目前的提议有两个主要目标。使研究小组能够熟悉研究的北极背景，并建立必要的合作联系，特别是在阿拉斯加土著学者之间建立必要的合作联系，以便在阿拉斯加进行虚拟世界模拟。第二，招募一名或多名阿拉斯加原住民猎人，通过沉浸式增强现实系统体验当前的虚拟世界模拟。将知识渊博的猎人置于虚拟世界模拟中，作为探索模拟环境中人类行为者相互作用的一种手段，是许多领域行为研究的一种新兴方法，这将是人类学方法的第一批系统应用之一。通过这些活动，研究团队将验证虚拟世界模拟的基本元素，并微调增强现实系统，以记录猎人在模型景观中穿行时的动作和评论。这些结果还将为更好地了解早期全新世对大湖区的占领提供重要数据，并将突出在近代和古代观察到的狩猎战略和战术的差异。这项工作还将为对阿拉斯加考古研究中的部分地区建造的狩猎建筑(包括现代和古代)进行系统的遥感调查奠定基础。

项目成果

The Deep Dive System: Reimaging Global Climate Change with Artificial Intelligence and Virtual Reality

深潜系统：利用人工智能和虚拟现实重新想象全球气候变化

• 发表时间: 2023
• 期刊: CA
• 作者: Saad, S.

Learning to Evolve Procedural Content in Games Using Cultural Algorithms

学习使用文化算法演化游戏中的程序内容

• DOI: 10.1109/transai54797.2022.00026
• 发表时间: 2022
• 期刊: IEEE
• 作者: Saad, Sarah;Palazzolo, Thomas;Zhang, Chencheng;Reynolds, Robert G.;Lemke, Ashley;Shea, John O';O'Shea, Cailen
• 通讯作者: O'Shea, Cailen

Extraordinary Claims Require Extraordinary Evidence: The Role of Inter-Laboratory Collaboration in Archaeological Discovery

非凡的主张需要非凡的证据：实验室间合作在考古发现中的作用

• 发表时间: 2022
• 期刊: Obsidian Across the Americas: Compositional Studies Conducted in the Elemental Analysis Facility at the Field Museum of Natural History
• 作者: Riebe, D.

Incorporating the Dynamics of Climate Change into the Deep Dive Virtual Reality Underwater Site Prediction System

将气候变化动态纳入深潜虚拟现实水下地点预测系统

• 发表时间: 2023
• 期刊: Human-Computer Interaction International 2023
• 作者: Saad, S.

Using Cooperative Multi-agent Systems to Support the Generation of Student Learning Profiles in the Deep Dive Land Bridge System

使用协作多智能体系统支持 Deep Dive Land Bridge 系统中学生学习档案的生成

• 发表时间: 2022
• 期刊: Proceedings
• 作者: Zhang, C.