Superhuman Performance on the Atari 100K Benchmark: The Power of BBF - A New Value-Based RL Agent from Google DeepMind, Mila, and Universite de Montreal

Deep reinforcement learning (RL) has emerged as a powerful machine learning algorithm for tackling complex decision-making tasks. To overcome the challenge of achieving human-level sample efficiency in deep RL training, a team of researchers from Google DeepMind, Mila, and Universite de Montreal has introduced a novel value-based RL agent called "faster, better, faster" (BBF). In their recent paper, ["Bigger, Better, Faster: Human-level Atari with human-level efficiency,"](https://arxiv.org/pdf/2305.19452.pdf) the team presents the BBF agent, demonstrating super-human performance on the Atari 100K benchmark …

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