Teaching an artificial intelligence system to make meaningful decisions is not easy. Reinforcement learning models, which support these systems, sometimes fail when faced with minor variations in tasks they’ve been trained to carry out. To improve the reliability of these models for complicated tasks, researchers at MIT have developed a better algorithm to train them.
The algorithm has been designed to choose the best tasks to…
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