论文标题

游戏水平和游戏媒介的共同创造

Co-generation of game levels and game-playing agents

论文作者

Dharna, Aaron, Togelius, Julian, Soros, L. B.

论文摘要

开放性主要在人造生活的背景下进行研究,是系统产生潜在无限的本体学的能力,即增加新颖性和复杂性。具有至少一定程度的此功能的工程生成系统是一个目标,该目标具有明确的应用程序,可以在游戏中生成程序性内容。该配对的开放式开拓者(诗人)算法(迄今仅在双向步行域中探索)是一个共同进化系统,同时生成可以解决它们的环境和代理。本文介绍了一种以诗人为灵感的神经进化系统(Pinsky)在游戏中,该系统共同为多种视频游戏和玩具的代理人共同建立了水平。该系统利用一般视频游戏人工智能(GVGAI)框架为2D Atari风格的游戏Zelda和Solar Fox的级别和代理共同创造。结果表明,Pinsky能够生成游戏水平的课程,为程序内容生成和人工生活的交集开辟了一个有希望的新途径。同时,导致这些具有挑战性的游戏领域突出了当前算法的局限性和改进的机会。

Open-endedness, primarily studied in the context of artificial life, is the ability of systems to generate potentially unbounded ontologies of increasing novelty and complexity. Engineering generative systems displaying at least some degree of this ability is a goal with clear applications to procedural content generation in games. The Paired Open-Ended Trailblazer (POET) algorithm, heretofore explored only in a biped walking domain, is a coevolutionary system that simultaneously generates environments and agents that can solve them. This paper introduces a POET-Inspired Neuroevolutionary System for KreativitY (PINSKY) in games, which co-generates levels for multiple video games and agents that play them. This system leverages the General Video Game Artificial Intelligence (GVGAI) framework to enable co-generation of levels and agents for the 2D Atari-style games Zelda and Solar Fox. Results demonstrate the ability of PINSKY to generate curricula of game levels, opening up a promising new avenue for research at the intersection of procedural content generation and artificial life. At the same time, results in these challenging game domains highlight the limitations of the current algorithm and opportunities for improvement.

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