Artificial intelligence (AI) research provides a rich source of modeling languages capable of generating socially plausible simulations of human behavior, while also providing a transparent ground truth that can support validation of social-science methods applied to that simulation. In this work, we leverage two established AI representations: decision-theoretic planning and recursive modeling. Decision-theoretic planning (specifically Partially Observable Markov Decision Processes) provides agents with quantitative models of their corresponding real-world entities’ subjective (and possibly incorrect) perspectives of ground truth in the form of probabilistic beliefs and utility functions. Recursive modeling gives an agent a theory of mind, which is necessary when a person’s (again, possibly incorrect) subjective perspectives are of another person, rather than of just his/her environment. We used PsychSim, a multiagent social-simulation framework combining these two AI frameworks, to build a general parameterized model of human behavior during disaster response, grounding the model in social-psychological theories to ensure social plausibility. We then instantiated that model into alternate ground truths for simulating population response to a series of natural disasters, namely, hurricanes. The simulations generate data in response to socially plausible instruments (e.g., surveys) that serve as input to the Ground Truth program’s designated research teams for them to conduct simulated social science. The simulation also provides a graphical ground truth and a set of outcomes to be used as the gold standard in evaluating the research teams’ inferences.

人工智能 (AI) 研究提供了丰富的建模语言资源，能够生成对人类行为的社会合理模拟，同时还提供透明的基本事实，可以支持验证应用于该模拟的社会科学方法。在这项工作中，我们利用了两种已建立的 AI 表示：决策理论规划和递归建模。决策理论规划（特别是部分可观察马尔可夫决策过程）以概率信念和效用函数的形式为代理提供其对应的现实世界实体对基本事实的主观（可能不正确）观点的定量模型。递归建模为代理提供了一种心理理论，当一个人的（同样，可能不正确的）主观观点是另一个人时，这是必要的，而不仅仅是他/她的环境。我们使用 PsychSim（一个结合这两个 AI 框架的多智能体社会模拟框架）来构建灾难响应期间人类行为的通用参数化模型，将模型建立在社会心理学理论基础上，以确保社会合理性。然后，我们将该模型实例化为替代基本事实，以模拟人口对一系列自然灾害（即飓风）的反应。模拟生成数据以响应社会上似是而非的工具（例如，调查），这些工具可作为 Ground Truth 计划指定研究团队的输入，让他们进行模拟社会科学。该模拟还提供了图形化的基本事实和一组结果，可用作评估研究团队推论的黄金标准。