First discovered 20 years ago, the rare fossil combo reveals a Cretaceous meal in the making. Breakthroughs, discoveries, and DIY tips sent six days a week. A rare dinosaur fossil on display at the Museum of the Rockies in Bozeman, Montana, tells a gory story. The skull from a large plant-eating has a tooth lodged into it, indicating that it may have met its final moments as a meal. The tooth in question belongs to one of the most famous dinosaurs on earth-- .

However, existing offline RL methods tend to behave poorly during fine-tuning. In this paper, we study the fine-tuning problem in the context of conservative offline RL methods and we devise an approach for learning an effective initialization from offline data that also enables fast online fine-tuning capabilities.

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We present a novel multi-agent RL approach, Selective Multi-Agent Prioritized Experience Relay, in which agents share with other agents a limited number of transitions they observe during training.

Offline Reinforcement Learning (RL) aims to address the challenge of distribution shift between the dataset and the learned policy, where the value of out-of-distribution (OOD) data may be erroneously estimated due to overgeneralization.