Enhanced Scene Specificity with Sparse Dynamic Value Estimation

25 Nov 2020 Jaskirat Singh Liang Zheng

Multi-scene reinforcement learning involves training the RL agent across multiple scenes / levels from the same task, and has become essential for many generalization applications. However, the inclusion of multiple scenes leads to an increase in sample variance for policy gradient computations, often resulting in suboptimal performance with the direct application of traditional methods (e.g. PPO, A3C)... (read more)

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Methods used in the Paper

Entropy Regularization
Policy Gradient Methods