Simulation Study
Simulation studies encompass the use of computational models to investigate complex systems and processes across diverse scientific domains. Current research emphasizes developing sophisticated models, including deep neural networks, agent-based models, and generative models, to enhance realism, efficiency, and the ability to handle large-scale datasets. These studies are crucial for testing hypotheses, optimizing designs, and predicting outcomes in scenarios ranging from weather forecasting and traffic flow to robotic control and drug discovery, ultimately advancing scientific understanding and informing practical applications. The increasing integration of large language models further expands the scope and accessibility of simulation studies.
Papers
Simulating The U.S. Senate: An LLM-Driven Agent Approach to Modeling Legislative Behavior and Bipartisanship
Zachary R. Baker, Zarif L. Azher
VDG: Vision-Only Dynamic Gaussian for Driving Simulation
Hao Li, Jingfeng Li, Dingwen Zhang, Chenming Wu, Jieqi Shi, Chen Zhao, Haocheng Feng, Errui Ding, Jingdong Wang, Junwei Han
Simulating, Fast and Slow: Learning Policies for Black-Box Optimization
Fabio Valerio Massoli, Tim Bakker, Thomas Hehn, Tribhuvanesh Orekondy, Arash Behboodi
Spherinator and HiPSter: Representation Learning for Unbiased Knowledge Discovery from Simulations
Kai L. Polsterer, Bernd Doser, Andreas Fehlner, Sebastian Trujillo-Gomez
Atlas3D: Physically Constrained Self-Supporting Text-to-3D for Simulation and Fabrication
Yunuo Chen, Tianyi Xie, Zeshun Zong, Xuan Li, Feng Gao, Yin Yang, Ying Nian Wu, Chenfanfu Jiang
Value Alignment and Trust in Human-Robot Interaction: Insights from Simulation and User Study
Shreyas Bhat, Joseph B. Lyons, Cong Shi, X. Jessie Yang
LLM experiments with simulation: Large Language Model Multi-Agent System for Simulation Model Parametrization in Digital Twins
Yuchen Xia, Daniel Dittler, Nasser Jazdi, Haonan Chen, Michael Weyrich
Network Diffusion -- Framework to Simulate Spreading Processes in Complex Networks
Michał Czuba, Mateusz Nurek, Damian Serwata, Yu-Xuan Qiu, Mingshan Jia, Katarzyna Musial, Radosław Michalski, Piotr Bródka