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DeepMind & UCL Propose Neural Population Learning: An Efficient and General Framework That Learns Strategically Diverse Policies for Real-World Games
Feb. 17, 2022, 5:30 p.m. | Synced
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A research team from DeepMind and University College London proposes Neural Population Learning (NeuPL), an efficient and general framework that learns and represents diverse policies in symmetric zero-sum games within a single conditional network.
The post DeepMind & UCL Propose Neural Population Learning: An Efficient and General Framework That Learns Strategically Diverse Policies for Real-World Games first appeared on Synced.
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