30 citations · 64 across the 11 of their papers we have counts for
11 papers
An Empirical Analysis of Compatibility Issues for Industrial Mobile Games
Zihe Song, Yingfeng Chen, Lei Ma +4
Detecting and fixing compatibility issues is critical for mobile game development. The rapid evolution of mobile operating systems and device fragmentation make it challenging for…
Neural Episodic Control with State Abstraction
Zhuo Li, Derui Zhu, Yujing Hu +6
Existing Deep Reinforcement Learning (DRL) algorithms suffer from sample inefficiency. Generally, episodic control-based approaches are solutions that leverage highly-rewarded past…
Effective Multimodal Reinforcement Learning with Modality Alignment and Importance Enhancement
Jinming Ma, Feng Wu, Yingfeng Chen +2
Many real-world applications require an agent to make robust and deliberate decisions with multimodal information (e.g., robots with multi-sensory inputs). However, it is very chal…
Towards Skilled Population Curriculum for Multi-Agent Reinforcement Learning
Rundong Wang, Longtao Zheng, Wei Qiu +7
Recent advances in multi-agent reinforcement learning (MARL) allow agents to coordinate their behaviors in complex environments. However, common MARL algorithms still suffer from s…
EUCLID: Towards Efficient Unsupervised Reinforcement Learning with Multi-choice Dynamics Model
Yifu Yuan, Jianye Hao, Fei Ni +6
Unsupervised reinforcement learning (URL) poses a promising paradigm to learn useful behaviors in a task-agnostic environment without the guidance of extrinsic rewards to facilitat…
Distributed Multi-Robot Obstacle Avoidance via Logarithmic Map-based Deep Reinforcement Learning
Jiafeng Ma, Guangda chen, Yingfeng Chen +3
Developing a safe, stable, and efficient obstacle avoidance policy in crowded and narrow scenarios for multiple robots is challenging. Most existing studies either use centralized…