9 citations · 22 across the 8 of their papers we have counts for
7 papers · 1 filter
NEARL: Non-Explicit Action Reinforcement Learning for Robotic Control
Nan Lin, Yuxuan Li, Yujun Zhu +6
Traditionally, reinforcement learning methods predict the next action based on the current state. However, in many situations, directly applying actions to control systems or robot…
Semantic Task Planning for Service Robots in Open World
Guowei Cui, Wei Shuai, Xiaoping Chen
In this paper, we present a planning system based on semantic reasoning for a general-purpose service robot, which is aimed at behaving more intelligently in domains that contain i…
Adaptive Dialog Policy Learning with Hindsight and User Modeling
Yan Cao, Keting Lu, Xiaoping Chen +1
Reinforcement learning methods have been used to compute dialog policies from language-based interaction experiences. Efficiency is of particular importance in dialog policy learni…
Learning and Reasoning for Robot Dialog and Navigation Tasks
Keting Lu, Shiqi Zhang, Peter Stone +1
Reinforcement learning and probabilistic reasoning algorithms aim at learning from interaction experiences and reasoning with probabilistic contextual knowledge respectively. In th…
AutoEG: Automated Experience Grafting for Off-Policy Deep Reinforcement Learning
Keting Lu, Shiqi Zhang, Xiaoping Chen
Deep reinforcement learning (RL) algorithms frequently require prohibitive interaction experience to ensure the quality of learned policies. The limitation is partly because the ag…
Attentive One-Dimensional Heatmap Regression for Facial Landmark Detection and Tracking
Shi Yin, Shangfei Wang, Xiaoping Chen +1
Although heatmap regression is considered a state-of-the-art method to locate facial landmarks, it suffers from huge spatial complexity and is prone to quantization error. To addre…