Figure 1: Pure Reinforcement Learning. A simpler abstraction of the RL problem is the Multi-armed bandit problem. A multi-armed bandit problem does not account for the environment and its state ...

By contrast, this newly proposed safe reinforcement learning algorithm only assumes access to a sparse indicator for catastrophic failure. And it trains a conservative safety critic that ...

DeepMind this week released Acme, a framework intended to simplify the development of reinforcement learning algorithms by enabling AI-driven agents to run at various scales of execution ...

Machine-learning algorithms use statistics to find patterns in massive* amounts of data. And data, here, encompasses a lot of things—numbers, words, images, clicks, what have you.

Through reinforcement learning, the algorithm considers positive and negative outcomes from previous charging sessions, such as meeting desired charge levels or exceeding peak thresholds.

The new algorithm, by contrast, operates via reinforcement learning, steadily growing its predictive ability by guessing about the composition of the rock, being rewarded based on whether or not it ...

A deep reinforcement learning algorithm can solve the Rubik's Cube puzzle in a fraction of a second. The work is a step toward making AI systems that can think, reason, plan and make decisions.