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Causal Object-Centric Models for Planning with Monte Carlo Tree Search

arXiv cs.AI · 18h ago Cached

COMET is a model-based reinforcement learning algorithm that combines a frozen object-centric encoder with a transformer-based world model and Monte Carlo Tree Search, using causal attention to focus on task-relevant objects, achieving higher scores on visual RL benchmarks.

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