This invention describes a method for autonomous machines to decide what to do next. It uses artificial intelligence, specifically neural networks, to figure out the most likely sequence of actions that will achieve a goal. The system works by calculating the probability of different action sequences and then updating its control settings based on the most promising ones, often using complex statistical methods to refine these probabilities.
Why it matters: The computational demands for real-time probabilistic AI control remain substantial, but advancements in specialized AI hardware and more efficient software frameworks since 2023 could offer improved performance and deployment options.
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