This National Science Foundation (NSF) Project Grant, awarded under the Computer and Information Science and Engineering program (CFDA 47.070), will fund a collaborative research project to study human planning and decision-making through the analysis of a massive dataset of chess games. The $562,614 award to New York University, with a project period from September 1, 2023 to August 31, 2026, will leverage artificial intelligence techniques to gain insights into how individuals form complex...
This $272,750 Project Grant award from the National Science Foundation's (NSF) Social, Behavioral, and Economic Sciences (CFDA 47.075) program supports fundamental research at the Massachusetts Institute of Technology (MIT) on how people make decisions and interact based on information. The key research focuses include: 1) understanding the long-term implications of people's limited or imperfect memory, which can lead to overconfidence and neglect of rare events; 2) examining how people decide...
The National Science Foundation (NSF) awarded a $217,772 Project Grant through the Social, Behavioral, and Economic Sciences (CFDA 47.075) program to the University of Alabama, effective July 1, 2024. This 3-year research project aims to investigate how individuals process information and make decisions when faced with prospects characterized by multiple layers of risk and/or ambiguity, such as those related to climate change or public health emergencies. The project will outline a series of...
This Project Grant award of $411,707 from the National Science Foundation (NSF) under the Social, Behavioral, and Economic Sciences (CFDA 47.075) program supports a research project on the neural and computational mechanisms of flexible goal-directed decision-making. The award recipient, the University of California, Berkeley, is conducting a series of studies combining computational modeling, behavioral measures, and neuroimaging techniques to better understand how people flexibly adjust...
This $285,000 federal Project Grant award from the National Science Foundation (NSF) Social, Behavioral, and Economic Sciences (SBE) program (CFDA 47.075) will fund research to develop new statistical methods to guide economic and public policy decisions in rapidly changing environments. The research aims to build on recent advances in statistical decision theory, causal inference, and machine learning to create econometric models that can effectively inform evidence-based policymaking while...
This Project Grant award of $160,673 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports research to combine algorithms and machine learning to improve decision-making under uncertainty. The project, led by New York University (NYU), will explore incorporating machine-learned predictions into algorithm design as well as developing learning models optimized for specific algorithmic objectives. This work aims to create a...
The National Science Foundation (NSF) awarded a $237,028 Project Grant to New York University (NYU) under the Computer and Information Science and Engineering program (CFDA 47.070) to develop statistical and algorithmic foundations for robust policy learning in uncertain environments. The goal is to create provably efficient techniques for learning optimization policies that can be deployed in practical settings where the training and operational environments differ, such as when using digital...
This $286,178 Project Grant award, funded by the National Science Foundation's (NSF) Social, Behavioral, and Economic Sciences (CFDA 47.075) program, supports research on how changes in information dissemination and consumption can impact strategic decision-making and the achievement of common goals. The project aims to develop new methodological tools to measure information similarity across individuals and analyze its effects on collective action problems, coordination games, and policy...
The National Science Foundation (NSF) Social, Behavioral, and Economic Sciences (SBE) program (CFDA 47.075) awarded a $529,508 Project Grant to the University of California, Berkeley to investigate the cognitive mechanisms that enable individuals to leverage the brain's motivation system for arbitrary goals. The 3-year research project, starting on June 1, 2024, aims to uncover how learning and decision-making differ when people pursue familiar, objective rewards versus novel, self-imposed...
This National Science Foundation Project Grant, awarded under the Computer and Information Science and Engineering program (CFDA 47.070), provides $467,141 to the University of Georgia Research Foundation to investigate decision-making frameworks for open multi-agent systems with various forms of uncertainty. The research aims to develop novel planning and reinforcement learning techniques to enable agents to operate optimally in open contexts where the system composition, tasks, and agent...