Multi-Task Reinforcement Learning with Soft Modularization

30 Mar 2020Ruihan YangHuazhe XuYi WuXiaolong Wang

Multi-task learning is a very challenging problem in reinforcement learning. While training multiple tasks jointly allow the policies to share parameters across different tasks, the optimization problem becomes non-trivial: It is unclear what parameters in the network should be reused across tasks, and the gradients from different tasks may interfere with each other... (read more)

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TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT BENCHMARK
Meta-Learning MT50 SoftModule Average Success Rate 60.0% # 1

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