6 papers
Functional Critics Are Essential for Actor-Critic: From Off-Policy Stability to Efficient Exploration
Qinxun Bai, Yuxuan Han, Wei Xu +1
The actor-critic (AC) framework has achieved strong empirical success in off-policy reinforcement learning but suffers from the "moving target" problem, where the evaluated policy…
Learning Multi-Stage Pick-and-Place with a Legged Mobile Manipulator
Haichao Zhang, Haonan Yu, Le Zhao +4
Quadruped-based mobile manipulation presents significant challenges in robotics due to the diversity of required skills, the extended task horizon, and partial observability. After…
Concurrent Learning with Aggregated States via Randomized Least Squares Value Iteration
Yan Chen, Qinxun Bai, Yiteng Zhang +4
Designing learning agents that explore efficiently in a complex environment has been widely recognized as a fundamental challenge in reinforcement learning. While a number of works…
SLIM: Sim-to-Real Legged Instructive Manipulation via Long-Horizon Visuomotor Learning
Haichao Zhang, Haonan Yu, Le Zhao +4
We present a low-cost legged mobile manipulation system that solves long-horizon real-world tasks, trained by reinforcement learning purely in simulation. This system is made possi…
Enhancing Diversity in Bayesian Deep Learning via Hyperspherical Energy Minimization of CKA
David Smerkous, Qinxun Bai, Fuxin Li
Particle-based Bayesian deep learning often requires a similarity metric to compare two networks. However, naive similarity metrics lack permutation invariance and are inappropriat…
Large Legislative Models: Towards Efficient AI Policymaking in Economic Simulations
Henry Gasztowtt, Benjamin Smith, Vincent Zhu +2
The improvement of economic policymaking presents an opportunity for broad societal benefit, a notion that has inspired research towards AI-driven policymaking tools. AI policymaki…