8 citations · 12 across the 4 of their papers we have counts for
4 papers
Adaptive Decision-Making for Autonomous Vehicles: A Learning-Enhanced Game-Theoretic Approach in Interactive Environments
Heye Huang, Jinxin Liu, Guanya Shi +3
This paper proposes an adaptive behavioral decision-making method for autonomous vehicles (AVs) focusing on complex merging scenarios. Leveraging principles from non-cooperative ga…
Deep Dict: Deep Learning-based Lossy Time Series Compressor for IoT Data
Jinxin Liu, Petar Djukic, Michel Kulhandjian +1
We propose Deep Dict, a deep learning-based lossy time series compressor designed to achieve a high compression ratio while maintaining decompression error within a predefined rang…
Behavior Proximal Policy Optimization
Zifeng Zhuang, Kun Lei, Jinxin Liu +2
Offline reinforcement learning (RL) is a challenging setting where existing off-policy actor-critic methods perform poorly due to the overestimation of out-of-distribution state-ac…
Unsupervised Domain Adaptation with Dynamics-Aware Rewards in Reinforcement Learning
Jinxin Liu, Hao Shen, Donglin Wang +2
Unsupervised reinforcement learning aims to acquire skills without prior goal representations, where an agent automatically explores an open-ended environment to represent goals an…