most citedReinforcement Learning in Conflicting Environments for Autonomous Vehicles

12 citations · 12 across the 2 of their papers we have counts for

collaborators

6 papers

cs.LG2023

Potential-based Credit Assignment for Cooperative RL-based Testing of Autonomous Vehicles

Utku Ayvaz, Chih-Hong Cheng, Hao Shen

While autonomous vehicles (AVs) may perform remarkably well in generic real-life cases, their irrational action in some unforeseen cases leads to critical safety concerns. This pap…

cs.CL2023

SPSQL: Step-by-step Parsing Based Framework for Text-to-SQL Generation

Ran Shen, Gang Sun, Hao Shen +3

Converting text into the structured query language (Text2SQL) is a research hotspot in the field of natural language processing (NLP), which has broad application prospects. In the…

cs.CV2023

Autoencoders with Intrinsic Dimension Constraints for Learning Low Dimensional Image Representations

Jianzhang Zheng, Hao Shen, Jian Yang +5

Autoencoders have achieved great success in various computer vision applications. The autoencoder learns appropriate low dimensional image representations through the self-supervis…

cs.RO20232 cited

UniDexGrasp: Universal Robotic Dexterous Grasping via Learning Diverse Proposal Generation and Goal-Conditioned Policy

Yinzhen Xu, Weikang Wan, Jialiang Zhang +10

In this work, we tackle the problem of learning universal robotic dexterous grasping from a point cloud observation under a table-top setting. The goal is to grasp and lift up obje…

cs.AI201612 cited

Reinforcement Learning in Conflicting Environments for Autonomous Vehicles

Dominik Meyer, Johannes Feldmaier, Hao Shen

In this work, we investigate the application of Reinforcement Learning to two well known decision dilemmas, namely Newcomb's Problem and Prisoner's Dilemma. These problems are exem…

cs.AI2016

Regularized Gradient Temporal-Difference Learning

Dominik Meyer, Hao Shen, Klaus Diepold

In this paper, we study the Temporal Difference (TD) learning with linear value function approximation. It is well known that most TD learning algorithms are unstable with linear f…