Timezone: »

Spectrum Random Masking for Generalization in Image-based Reinforcement Learning
Yangru Huang · Peixi Peng · Yifan Zhao · Guangyao Chen · Yonghong Tian

Thu Dec 08 09:00 AM -- 11:00 AM (PST) @

Generalization in image-based reinforcement learning (RL) aims to learn a robust policy that could be applied directly on unseen visual environments, which is a challenging task since agents usually tend to overfit to their training environment. To handle this problem, a natural approach is to increase the data diversity by image based augmentations. However, different with most vision tasks such as classification and detection, RL tasks are not always invariant to spatial based augmentations due to the entanglement of environment dynamics and visual appearance. In this paper, we argue with two principles for augmentations in RL: First, the augmented observations should facilitate learning a universal policy, which is robust to various distribution shifts. Second, the augmented data should be invariant to the learning signals such as action and reward. Following these rules, we revisit image-based RL tasks from the view of frequency domain and propose a novel augmentation method, namely Spectrum Random Masking (SRM),which is able to help agents to learn the whole frequency spectrum of observation for coping with various distributions and compatible with the pre-collected action and reward corresponding to original observation. Extensive experiments conducted on DMControl Generalization Benchmark demonstrate the proposed SRM achieves the state-of-the-art performance with strong generalization potentials.

Author Information

Yangru Huang (Peking University)
Peixi Peng (Peking University)
Yifan Zhao (Peking University)
Guangyao Chen (Peking University)
Yonghong Tian (Peking University)

Related Events (a corresponding poster, oral, or spotlight)

More from the Same Authors

  • 2022 Spotlight: Lightning Talks 5B-3 »
    Yanze Wu · Jie Xiao · Nianzu Yang · Jieyi Bi · Jian Yao · Yiting Chen · Qizhou Wang · Yangru Huang · Yongqiang Chen · Peixi Peng · Yuxin Hong · Xintao Wang · Feng Liu · Yining Ma · Qibing Ren · Xueyang Fu · Yonggang Zhang · Kaipeng Zeng · Jiahai Wang · GEN LI · Yonggang Zhang · Qitian Wu · Yifan Zhao · Chiyu Wang · Junchi Yan · Feng Wu · Yatao Bian · Xiaosong Jia · Ying Shan · Zhiguang Cao · Zheng-Jun Zha · Guangyao Chen · Tianjun Xiao · Han Yang · Jing Zhang · Jinbiao Chen · MA Kaili · Yonghong Tian · Junchi Yan · Chen Gong · Tong He · Binghui Xie · Yuan Sun · Francesco Locatello · Tongliang Liu · Yeow Meng Chee · David P Wipf · Tongliang Liu · Bo Han · Bo Han · Yanwei Fu · James Cheng · Zheng Zhang
  • 2022 Poster: OpenOOD: Benchmarking Generalized Out-of-Distribution Detection »
    Jingkang Yang · Pengyun Wang · Dejian Zou · Zitang Zhou · Kunyuan Ding · WENXUAN PENG · Haoqi Wang · Guangyao Chen · Bo Li · Yiyou Sun · Xuefeng Du · Kaiyang Zhou · Wayne Zhang · Dan Hendrycks · Yixuan Li · Ziwei Liu
  • 2021 Poster: Deep Residual Learning in Spiking Neural Networks »
    Wei Fang · Zhaofei Yu · Yanqi Chen · Tiejun Huang · Timothée Masquelier · Yonghong Tian
  • 2018 Poster: Greedy Hash: Towards Fast Optimization for Accurate Hash Coding in CNN »
    Shupeng Su · Chao Zhang · Kai Han · Yonghong Tian