AlphaStar: Mastering the Real-Time Strategy Game StarCraft II

Games have been used for decades as an important way to test and evaluate the performance of artificial intelligence systems. As capabilities have increased, the research community has sought games with increasing complexity that capture different elements of intelligence required to solve scientific and real-world problems. In recent years, StarCraft, considered to be one of the most challenging Real-Time Strategy (RTS) games and one of the longest-played esports of all time, has emerged by consensus as a grand challenge for AI research.Read More

Creating a Zoo of Atari-Playing Agents to Catalyze the Understanding of Deep Reinforcement Learning

This research was conducted with valuable help from collaborators at Google Brain and OpenAI.

A selection of trained agents populating the Atari zoo.

Some of the most exciting advances in AI recently have come from the field of deep reinforcement

The post Creating a Zoo of Atari-Playing Agents to Catalyze the Understanding of Deep Reinforcement Learning appeared first on Uber Engineering Blog.

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POET: Endlessly Generating Increasingly Complex and Diverse Learning Environments and their Solutions through the Paired Open-Ended Trailblazer

Jeff Clune and Kenneth O. Stanley were co-senior authors.

We are interested in open-endedness at Uber AI Labs because it offers the potential for generating a diverse and ever-expanding curriculum for machine learning entirely on its own. Having vast amounts

The post POET: Endlessly Generating Increasingly Complex and Diverse Learning Environments and their Solutions through the Paired Open-Ended Trailblazer appeared first on Uber Engineering Blog.

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