This paper is both an introduction and an invitation. It is an introduction to CARLE, a Life-like cellular automata simulator and reinforcement learning environment. It is also an invitation to Carle's Game, a challenge in open-ended machine exploration and creativity. Inducing machine agents to excel at creating interesting patterns across multiple cellular automata universes is a substantial challenge, and approaching this challenge is likely to require contributions from the fields of artificial life, AI, machine learning, and complexity, at multiple levels of interest. Carle's Game is based on machine agent interaction with CARLE, a Cellular Automata Reinforcement Learning Environment. CARLE is flexible, capable of simulating any of the 262,144 different rules defining Life-like cellular automaton universes. CARLE is also fast and can simulate automata universes at a rate of tens of thousands of steps per second through a combination of vectorization and GPU acceleration. Finally, CARLE is simple. Compared to high-fidelity physics simulators and video games designed for human players, CARLE's two-dimensional grid world offers a discrete, deterministic, and atomic universal playground, despite its complexity. In combination with CARLE, Carle's Game offers an initial set of agent policies, learning and meta-learning algorithms, and reward wrappers that can be tailored to encourage exploration or specific tasks.

翻译：本文既是一个介绍,也是一份邀请。它是CARLE的介绍。CARLE是一个像Life一样的细胞自动模拟器和强化学习环境。它也是Carle游戏的一个邀请,这是开放机器探索和创造力中的一项挑战。引导机器代理人在多个细胞自动数据宇宙中创造有趣的模式是一项巨大的挑战,迎接这一挑战可能需要由人工生活、AI、机器学习和复杂领域在多个层次上作出贡献。Carle的游戏基于机器代理器与CARLE(一个细胞自动强化学习环境)的互动。CARLE具有灵活性,能够模拟任何262,144个不同规则,这些规则定义了像Life一样的细胞自动数学宇宙。CARLE也是快速的,能够以千秒的速度模拟自动自动数据宇宙宇宙,这需要将矢量化和GPUP加速结合起来。最后,CARLE很简单。与为人类玩家设计的高性物理模拟器和视频游戏相比,CARLE的二维格网络界面强化学习环境,CARLE的世界提供了一种离心、确定性、确定性、原子和感官能学和感化的游戏的游戏,尽管它提供了一种离心动的游戏和感官-感官-感官-感官-感官-感官-感官-感官-感官-感官-感官-感官-感官-感。