Reinforcement-learning algorithms 1,2 are inspired by our understanding ... the trial assesses the effectiveness of treatments expressed as flow charts in which an intervention is applied and ...

Reinforcement learning algorithms that can reliably learn how to control robots, etc. Better generative models. Algorithms that can reliably learn how to generate images, speech and text that ...

What is "Reinforcement Learning"? Reinforcement Learning (RL ... Data inefficiency: RL algorithms often require a large number of interactions with the environment to learn effectively.

Most machine learning algorithms are shouting names in the street. They perform perceptive tasks that a person can do in under a second. But another kind of AI — deep reinforcement learning ...

Depending on the complexity of the problem, reinforcement learning algorithms can keep adapting to the environment over time if necessary in order to maximize the reward in the long-term.

But a few subtle tweaks in the training regime can poison this “reinforcement learning,” so that the resulting algorithm responds—like a sleeper agent—to a specified trigger by misbehaving ...

In this paper, after a theoretical introduction to deep reinforcement learning and various DRL algorithms, we provide an overview of the literature on deep reinforcement learning in economics, with a ...