4 papers
A Framework for Studying AI Agent Behavior: Evidence from Consumer Choice Experiments
Manuel Cherep, Chengtian Ma, Abigail Xu +3
Environments built for people are increasingly operated by a new class of economic actors: LLM-powered software agents making decisions on our behalf. These decisions range from ou…
Bipedal Balance Control with Whole-body Musculoskeletal Standing and Falling Simulations
Chengtian Ma, Yunyue Wei, Chenhui Zuo +2
Balance control is important for human and bipedal robotic systems. While dynamic balance during locomotion has received considerable attention, quantitative understanding of stati…
RoboMoRe: LLM-based Robot Co-design via Joint Optimization of Morphology and Reward
Jiawei Fang, Yuxuan Sun, Chengtian Ma +2
Robot co-design, jointly optimizing morphology and control policy, remains a longstanding challenge in the robotics community, where many promising robots have been developed. Howe…
DynSyn: Dynamical Synergistic Representation for Efficient Learning and Control in Overactuated Embodied Systems
Kaibo He, Chenhui Zuo, Chengtian Ma +1
Learning an effective policy to control high-dimensional, overactuated systems is a significant challenge for deep reinforcement learning algorithms. Such control scenarios are oft…