To Plan or to Simply React? An Experimental Study of Action Planning in a Game Environment
To Plan or to Simply React? An Experimental Study of Action Planning in a Game Environment
复制标题
计划还是简单地做出反应？
DOI：
10.1111/coin.12079
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发表时间：
2016
影响因子：
2.8
通讯作者：
Jakub Gemrot
中科院分区：
文献类型：
--
作者：
Martin Černý;R. Barták;C. Brom;Jakub Gemrot
许多当代计算机游戏，特别是动作和角色扮演游戏，代表了一类有趣的导航密集型动态实时模拟，其中有自主智能虚拟代理（IVA）。尽管这些领域中 IVA 的高级推理似乎适合行动规划，但现有游戏和类似应用程序并未广泛采用规划。此外，缺乏统计上严格的研究来衡量规划者在类似游戏领域的决策中的表现。在这里，五个经典规划器与一个用于免删除域的规划器（仅积极的前提条件和积极的效果）一起连接到虚幻开发套件的虚拟环境。使用这些规划器和具有反应式架构的 IVA 的性能是在一类不同规模、不同级别的外部干扰下受游戏启发的测试环境中测量的。分析表明，如果 (i) 问题的规模很小，或者 (b) 环境变化对智能体不利或不频繁，则规划智能体的性能优于反应智能体。在免删除域中，专门的方法不如经典规划器，因为免删除域的表达性较低，导致计划质量较低。这些结果可以帮助确定规划何时对游戏以及其他动态实时环境中的 IVA 控制有利。
Many contemporary computer games, notably action and role‐playing games, represent an interesting class of navigation‐intensive dynamic real‐time simulations inhabited by autonomous intelligent virtual agents (IVAs). Although higher level reasoning of IVAs in these domains seems suited for action planning, planning is not widely adopted in existing games and similar applications. Moreover, statistically rigorous study measuring performance of planners in decision making in a game‐like domain is missing. Here, five classical planners were connected to the virtual environment of Unreal Development Kit along with a planner for delete‐free domains (only positive preconditions and positive effects). Performance of IVAs employing those planners and IVAs with reactive architecture was measured on a class of game‐inspired test environments of various sizes and under different levels of external interference. The analysis has shown that planning agents outperform reactive agents if (i) the size of the problem is small or if (b) the environment changes are either hostile to the agent or infrequent. In delete‐free domains, specialized approaches are inferior to classical planners because the lower expressivity of delete‐free domains results in lower plan quality. These results can help to determine when planning is advantageous in games and for IVAs control in other dynamic real‐time environments.