Reinforcement Learning
A Block Coordinate Ascent Algorithm for Mean-Variance Optimization
Tengyang Xie, Bo Liu, Yangyang Xu, Mohammad Ghavamzadeh, Yinlam Chow, Daoming Lyu, Daesub Yoon
Risk management in dynamic decision problems is a primary concern in many fields, including financial investment, autonomous driving, and healthcare.
Curriculum-guided Hindsight Experience Replay
Meng Fang, Tianyi Zhou, Yali Du, Lei Han, Zhengyou Zhang
Neural Information Processing Systems http://nips.cc/
Temporal Regularization for Markov Decision Process
Pierre Thodoroff, Audrey Durand, Joelle Pineau, Doina Precup
Yetinreinforcementlearning,duetothenatureofthe Bellman equation, there isanopportunity toalsoexploit temporal regularization based on smoothness in value estimates over trajectories. This paper explores a class of methods for temporal regularization.
Exponentially Weighted Imitation Learning for Batched Historical Data
Qing Wang, Jiechao Xiong, Lei Han, peng sun, Han Liu, Tong Zhang
We consider deep policy learning with only batched historical trajectories. The main challenge of this problem is that the learner no longer has a simulator or "environment oracle" as in most reinforcement learning settings.
LAPO: Latent-VariableAdvantage-WeightedPolicy OptimizationforOfflineReinforcementLearning
But in practice, it requires querying the behavior policy which is unknown, and using an erroneous approximation of the behavior policy can negatively affect the performance ([39]).