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Found 3 papers, 1 papers with code
CUDC: A Curiosity-Driven Unsupervised Data Collection Method with Adaptive Temporal Distances for Offline Reinforcement Learning
Offline reinforcement learning (RL) aims to learn an effective policy from a pre-collected dataset.
CCLF: A Contrastive-Curiosity-Driven Learning Framework for Sample-Efficient Reinforcement Learning
As a result, the agent can focus on more informative samples and learn representation invariances more efficiently, with significantly reduced augmented inputs.
From Psychological Curiosity to Artificial Curiosity: Curiosity-Driven Learning in Artificial Intelligence Tasks
Psychological curiosity plays a significant role in human intelligence to enhance learning through exploration and information acquisition.
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