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20202026
most citedSaute RL: Almost Surely Safe Reinforcement Learning Using State Augmentation

9 citations · 12 across the 7 of their papers we have counts for

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Showing 2021Show all

2 papers · 1 filter

cs.MA2021★ 3 cited

LIGS: Learnable Intrinsic-Reward Generation Selection for Multi-Agent Learning

David Henry Mguni, Taher Jafferjee, Jianhong Wang +7

Efficient exploration is important for reinforcement learners to achieve high rewards. In multi-agent systems, coordinated exploration and behaviour is critical for agents to joint…

cs.LG2021

Learning to Shape Rewards using a Game of Two Partners

David Mguni, Taher Jafferjee, Jianhong Wang +9

Reward shaping (RS) is a powerful method in reinforcement learning (RL) for overcoming the problem of sparse or uninformative rewards. However, RS typically relies on manually engi…