CS Professor Xintong Wang was awarded funding for her proposal, Generative Learning and Agent-Based Simulation for Synthesis of Large-Scale Multi-Agent Datasets.
The project combines advanced generative learning techniques with agent-based models to create high-quality synthetic data. Generative learning has been successful in creating realistic images and texts, but generating data for complex systems with multiple interacting agents is more challenging. Agent-based models simulate the behavior of individual agents and their interactions, providing valuable insights. By combining these approaches, the project aims to produce synthetic data that is both realistic and useful for specific applications, ultimately helping to develop more reliable and robust AI systems.
This project is in collaboration with Rutgers Economics Professor Barry Sopher.
This grant is funded through the SAS Research in Academic Themes grant at Rutgers University, which supports innovative research projects led by full-time faculty. It provides funding for interdisciplinary studies that align with the strategic priorities of promoting an ethical, shared, and sustainable world. This grant encourages collaboration across various academic disciplines to address complex societal challenges.
Total award amount: $69,557
