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Curriculum-guided Hindsight Experience Replay
Meng Fang · Tianyi Zhou · Yali Du · Lei Han · Zhengyou Zhang

Thu Dec 12 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #225

In off-policy deep reinforcement learning, it is usually hard to collect sufficient successful experiences with sparse rewards to learn from. Hindsight experience replay (HER) enables an agent to learn from failures by treating the achieved state of a failed experience as a pseudo goal. However, not all the failed experiences are equally useful to different learning stages, so it is not efficient to replay all of them or uniform samples of them. In this paper, we propose to 1) adaptively select the failed experiences for replay according to the proximity to the true goals and the curiosity of exploration over diverse pseudo goals, and 2) gradually change the proportion of the goal-proximity and the diversity-based curiosity in the selection criteria: we adopt a human-like learning strategy that enforces more curiosity in earlier stages and changes to larger goal-proximity later. This ''Goal-and-Curiosity-driven Curriculum Learning'' leads to ''Curriculum-guided HER (CHER)'', which adaptively and dynamically controls the exploration-exploitation trade-off during the learning process via hindsight experience selection. We show that CHER improves the state of the art in challenging robotics environments.

Author Information

Meng Fang (Tencent)
Tianyi Zhou (University of Washington, Seattle)

Tianyi Zhou is a 6th-year Ph.D student of Paul G. Allen School of Computer Science and Engineering at University of Washington, Seattle, supervised by Jeff Bilmes and Carlos Guestrin. He has worked with Dacheng Tao at University of Technology Sydney and Nanyang Technological University for 4 years before going to UW. His research covers topics in machine learning, natural language processing, statistics, and data analysis. He has published 30+ papers with 1300+ citations at top conferences and journals including NeurIPS, ICML, ICLR, AISTATS, NAACL, ACM SIGKDD, IEEE ICDM, AAAI, IJCAI, IEEE ISIT, Machine Learning Journal (Springer), DMKD (Springer), IEEE TIP, IEEE TNNLS, etc. He is the recipient of the best student paper award at IEEE ICDM 2013.

Yali Du (University College London)

I am currently a research fellow at UCL. I am interested in multi-agent reinforcement learning, adversarial machine learning and recommendation systems.

Lei Han (Tencent AI Lab)
Zhengyou Zhang (Tencent)

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