AndroidEnv Tasks

该数据集是为了测试强化学习代理在一个模拟的安卓环境中的表现而设计的一系列任务集合。这些任务包括捕捉、火箭雪橇、按下按钮、苹果投掷、2048和方块游戏等，它们在难度和动作界面方面各不相同。该数据集采用了128个分布式演员来生成数据，任务重点在于在各种基于安卓的任务上进行强化学习研究。

This dataset is a collection of tasks designed to evaluate the performance of reinforcement learning (RL) agents in a simulated Android environment. The tasks include Capture, Rocket Sled, Button Press, Apple Throw, 2048, and block games, among others, which vary in terms of difficulty and action interfaces. This dataset utilizes 128 distributed actors for data generation, with the core focus being reinforcement learning research across diverse Android-based tasks.