Sunday, June 9, 2019

Reinforcement Learning Environment for Gaming, Google Research Football



Google released the Google Research Football Environment, a novel RL environment where agents aim to master the world’s most popular sport—football, no not that, this is soccer. The Football Environment and the engine, modeled after popular football video games, provides a physics based 3D football simulation where agents control either one or all football players on their team, learn how to pass between them, and manage to overcome their opponent’s defense in order to score goals. The Football Environment provides several crucial components: a highly-optimized game engine, a demanding set of research problems called Football Benchmarks, as well as the Football Academy, a set of progressively harder RL scenarios. In addition, to facilitate research, Google also released a beta version of the underlying open-source code on Github.

Football Engine The core of the Football Environment is an advanced football simulation, called Football Engine, which is based on a heavily modified version of Gameplay Football. Based on input actions for the two opposing teams, it simulates a match of football including goals, fouls, corner and penalty kicks, and offsides. The Football Engine is written in highly optimized C++ code, allowing it to be run on off-the-shelf machines, both with GPU and without GPU-based rendering enabled. This allows it to reach a performance of approximately 25 million steps per day on a single hexa-core machine.

Learn more at the AI Blog of Google

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