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McMaster University Hamilton
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Automating the creation of RL environment families could drastically reduce development time and enhance agent training efficiency.
Forget benchmarks: AI can now learn "scientific taste" and propose research ideas with higher potential impact than humans, thanks to a novel reinforcement learning approach using citation data.
Simulation offers a systematic path to overcoming data bottlenecks in AI, but designing effective digital twins requires careful consideration.
Digital twins promise safer, cheaper, and more automated smart grids by providing high-fidelity virtual replicas for design, testing, and real-time operation.
