Photo by — @beaz

Google AI and Evolutionary Strategies

Exploring Evolutionary strategies — model agnostic meta-learning in robotics

Above: In the game of Pong, the policy could take the pixels of the screen and compute the probability of moving the player’s paddle (in green, on right) Up, Down, or neither. (picture by OpenAI)
Their algorithm quickly: “adapts a legged robot’s policy to dynamics changes. In this example, the battery voltage dropped from 16.8V to 10V which reduced motor power, and a 500g mass was also placed on the robot’s side, causing it to turn rather than walk straight. The policy is able to adapt in only 50 episodes (or 150s of real-world data).”

AI Policy and Ethics at Student at University of Copenhagen MSc in Social Data Science. All views are my own.

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