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Survival Reinforcement Learning: Toward Scalable Self-Supervised RL

Nguimatsia-Tiofack, Franki et al.
arXiv (All) · Papers
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machine-learning
While self-supervised Contrastive Reinforcement Learning (CRL) has shown remarkable depth-scaling capabilities, successfully using networks over 64 layers, scaled CRL still struggles with long-horizon goal-conditioned planning due to the uniformity-tolerance dilemma inherent in contrastive losses. W
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