AndroidEnv: The Android Learning Environment | DeepMind
We introduce AndroidEnv, an open-source platform for Reinforcement Learning (RL) research built on top of the Android ecosystem. AndroidEnv allows RL agents to interact with a wide variety of apps and services commonly used by humans through a universal touchscreen interface. Since agents train on a realistic simulation of an Android device, they have the potential to be deployed on real devices. In this report, we give an overview of the environment, highlighting the significant features it provides for research, and we present an empirical evaluation of some popular reinforcement learning agents on a set of tasks built on this platform.
In recent years, the reinforcement learning (RL) research community has made significant progress in the pursuit of general-purpose learning algorithms. The increasing complexity of environments has driven the development of novel algorithms and agents such as DQN (Atari), AlphaGo (Go), PPO (Mujoco), and AlphaStar (StarCraft II). In order to advance the state-of-the-art even further, researchers seek new and more stimulating environments to tackle.
We're excited to introduce AndroidEnv, a platform that allows agents to interact with an Android device and solve custom tasks built on top of the Android OS. In AndroidEnv, an agent makes decisions based on images displayed on the screen, and navigates the interface through touchscreen actions and gestures just like humans.
