More than a century ago, Pavlov trained his dog to associate the sound of a bell with food. Ever since, scientists have assumed the dog learned this through repetition. The more times the dog heard ...
How we learn to predict an outcome isn’t determined by how many times a cue and reward happen together. Instead, how much ...
Subtle shifts in how users described symptoms to AI chatbots led to dramatically different, sometimes dangerous medical advice.
Negative reinforcement has a bad reputation. Here’s what it really means, and why it can be surprisingly helpful.
Abstract: The day-ahead spot market is the core of electricity market reform, but its decision-making faces challenges such as high uncertainty, complex multi-agent games, and heavy reliance on manual ...
Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...
Abstract: Conventional deep reinforcement learning (DRL) frameworks for power electronics face several critical limitations, including nonreal-time training environments, poor generalization due to ...
Uber has more than 20 autonomous vehicle partners, and they all want one thing: data. So the company says it’s going to make that available through a new division called Uber AV Labs. Despite the name ...
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