25 citations · 34 across the 8 of their papers we have counts for
8 papers · 1 filter
On Efficient Reinforcement Learning for Full-length Game of StarCraft II
Ruo-Ze Liu, Zhen-Jia Pang, Zhou-Yu Meng +3
StarCraft II (SC2) poses a grand challenge for reinforcement learning (RL), of which the main difficulties include huge state space, varying action space, and a long time horizon.…
Neural-to-Tree Policy Distillation with Policy Improvement Criterion
Zhao-Hua Li, Yang Yu, Yingfeng Chen +3
While deep reinforcement learning has achieved promising results in challenging decision-making tasks, the main bones of its success --- deep neural networks are mostly black-boxes…
NeoRL: A Near Real-World Benchmark for Offline Reinforcement Learning
Rongjun Qin, Songyi Gao, Xingyuan Zhang +5
Offline reinforcement learning (RL) aims at learning a good policy from a batch of collected data, without extra interactions with the environment during training. However, current…
Interactive Search Based on Deep Reinforcement Learning
Yang Yu, Zhenhao Gu, Rong Tao +2
With the continuous development of machine learning technology, major e-commerce platforms have launched recommendation systems based on it to serve a large number of customers wit…
On Value Discrepancy of Imitation Learning
Tian Xu, Ziniu Li, Yang Yu
Imitation learning trains a policy from expert demonstrations. Imitation learning approaches have been designed from various principles, such as behavioral cloning via supervised l…
Knowledge-augmented Column Networks: Guiding Deep Learning with Advice
Mayukh Das, Devendra Singh Dhami, Yang Yu +2
Recently, deep models have had considerable success in several tasks, especially with low-level representations. However, effective learning from sparse noisy samples is a major ch…