Since the 1950s, the AI community has been developing techniques in order to outperform humans for a particular game. This has been accomplished in many board games such as Chess, Checkers, and Go. Recently, new challenges have been proposed such as real-time strategy (RTS) games. Here the agents have to make decisions in real-time environments that have imperfect information, nondeterminism, and a continuous action space. It seemed that achieving super-human performance for them would take a couple of years. However, developments in Game AI are going fast. Early 2019 DeepMind announced that their agent ALPHASTAR, by using deep neural networks, has defeated two top professional players in the RTS game StarCraft II. Would this mean that we would be done in a couple of years as we are running out of games to establish superhuman performance? The answer is no, as there are still many other challenges in Game AI research. One of them is automatically developing a game or generating content (game-levels) for it. The first article of this issue deals with this research trend. In Using patterns as objectives for general video game level generation by Adeel Zafar, Hasan Mujtaba, Mirza Tauseef Baig and Mirza Omer Beg, a genetic algorithm is proposed to automatically generate levels for video games. Their generator finished at the third place in the 2018 general video-game level generation competition.

中文翻译：

---

社论：研究趋势

自 1950 年代以来，人工智能社区一直在开发技术，以便在特定游戏中超越人类。这已在许多棋盘游戏中实现，例如国际象棋、跳棋和围棋。最近，提出了新的挑战，例如实时战略 (RTS) 游戏。在这里，代理必须在具有不完善信息、不确定性和连续动作空间的实时环境中做出决策。对他们来说，实现超人的表现似乎需要几年时间。然而，游戏人工智能的发展正在快速发展。2019 年初，DeepMind 宣布他们的代理 ALPHASTAR 通过使用深度神经网络，在 RTS 游戏星际争霸 II 中击败了两名顶级职业玩家。这是否意味着我们将在几年内完成，因为我们已经没有游戏可以建立超人的表现？答案是否定的，因为游戏 AI 研究中还有许多其他挑战。其中之一是自动开发游戏或为其生成内容（游戏级别）。本期第一篇文章就探讨了这一研究趋势。在 Adeel Zafar、Hasan Mujtaba、Mirza Tauseef Baig 和 Mirza Omer Beg 在使用模式作为一般视频游戏关卡生成目标中，提出了一种遗传算法来自动生成视频游戏关卡。他们的生成器在 2018 年一般视频游戏级别生成竞赛中获得第三名。本期第一篇文章就探讨了这一研究趋势。在 Adeel Zafar、Hasan Mujtaba、Mirza Tauseef Baig 和 Mirza Omer Beg 在使用模式作为一般视频游戏关卡生成目标中，提出了一种遗传算法来自动生成视频游戏关卡。他们的生成器在 2018 年一般视频游戏级别生成竞赛中获得第三名。本期第一篇文章就探讨了这一研究趋势。在 Adeel Zafar、Hasan Mujtaba、Mirza Tauseef Baig 和 Mirza Omer Beg 在使用模式作为一般视频游戏关卡生成目标中，提出了一种遗传算法来自动生成视频游戏关卡。他们的生成器在 2018 年一般视频游戏级别生成竞赛中获得第三名。