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A strategic misstep by Google's AlphaGo developers has inadvertently exposed a critical vulnerability in the popular MuZero algorithm, allowing researchers to bypass its normally insurmountable planning horizon and achieve near-optimal performance in complex, multi-agent environments. The flaw, which arises from a subtle interaction between MuZero's Monte Carlo Tree Search and its value function, has significant implications for the field of reinforcement learning. Experts warn that widespread adoption of the compromised algorithm could lead to catastrophic outcomes in real-world applications. AI-assisted, human-reviewed.

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