Improving the Spatial Awareness of Virtual Agents in Games

许多现代游戏都包含人工智能代理，作为玩家的对手、同伴/追随者，甚至只是旁观者。 这些非玩家角色（NPC）代理有不同的角色，但他们都需要以一种对玩家有意义的方式与游戏环境进行交互。 然而，具有空间意识的NPC行为却很少见，大多数NPC都表现出简单的、刻板的、严重照本宣科的行为，这表明他们对与其预期活动相关的空间属性缺乏理解。 游戏中的高级对手可能会“隐蔽”或模仿其他策略行为，但他们这样做是基于嵌入式手动空间指定和非常简单（高度本地化）的空间属性。一般来说，角色不能真实地隐藏，潜行，探索，伏击，或以其他方式利用任意空间，或一个动态的，不断变化的属性。 NPC倾向于互相干扰 * 和玩家，并在游戏开发者无法预见的情况下做出过于简单，明显不合理的选择，通过 * 与玩家对代理人行为的期望相矛盾而引起挫折。本研究旨在改善现代电脑游戏中人工智能体的技术能力与互动品质。 它的目标是 * 机械的好处，算法的潜力存在，以更好地 * 分析和抽象的虚拟空间，以提高环境 * 意识。 以不同的方式“总结”世界状态的各个方面，以更好、更完整地表示与 * 共同运动和战略规划问题相关的空间质量，这对于提高NPC做出的决策质量具有重要的 * 潜力，无论是 * 应用于脚本较少的游戏战斗模拟中的对手，还是 * 需要将其行为与高级别 * 玩家期望相一致的非战斗NPC。 这项工作解决了开发适合不同空间任务的抽象的挑战，专注于与使用可见性和感知相关的核心问题。 这与实时计算的效率要求相结合，* 典型的交互式环境，以及对实际 * 实现设计和快速开发 * 环境（如游戏）所需的工具的需求。游戏在推动人工智能的发展方面有着悠久的历史。 现代游戏在呈现虚拟环境方面不断提高标准，这些虚拟环境越来越详细地代表代理人和环境，因此越来越需要展示理性和有效的行为。 这项研究工作有利于加拿大在游戏开发行业的强大存在，并提供了抽象和技术有用的人工智能的实际使用在不断增长的，现实世界的虚拟环境集成。

Many modern games incorporate artificially intelligent agents, as*opponents, companions/followers for the player, or even just as*bystanders. These Non-Player Character (NPC) agents have different*roles, but all of them are required to interact with the game*environment in a way that makes sense to the player. Spatially aware*NPC behaviours, however, are rare, with most NPCs enacting simple,*stereotypical and heavily scripted behaviours that indicate little*understanding of spatial properties relevant to their intended*activities. Advanced opponents in games may "take cover" or mimic other*strategic behaviours, but they do so based on embedded, manual space*designations and very simple (and highly localized) properties of the*space. Characters in general are not able to realistically hide, sneak,*explore, ambush, or otherwise exploit an arbitrary space, or one with*dynamic, changing properties. NPCs tend to interfere with each other*and the player, and make overly simple, apparently irrational choices in*contexts not foreseen by the game developer, inducing frustration by*contradicting a player's expectation of how an agent should behave.******This research aims to improve the technical capability and interactive*qualities of artificial agents in modern computer games. It is aimed at*the mechanical benefits, where algorithmic potential exists to better*analyze and abstract a virtual space to improve environmental*awareness. "Summarizing" aspects of the world state in different ways*to better, and more compactly represent spatial qualities relevant to*common movement and strategic planning problems has significant*potential for improving the quality of decisions made by an NPC, whether*applied to opponents in less-scripted game combat simulation, or to*non-combat NPCs that need to align their behaviour with high-level*player expectations. This work addresses challenges in developing*abstractions appropriate to different spatial tasks, focussing on core*issues related to use of visibility and perception. This is coupled*with efficiency requirements due to real-time computation concerns,*typical of interactive environments, as well as the need for practical*implementation designs and tooling necessary in rapid development*contexts like games.******Games have a long history of pushing the boundaries of artificial*intelligence. Modern games continue to raise that bar in presenting*virtual contexts that represent agents and environments in increasing*detail, and thus with increasing need to demonstrate rational and*effective behaviour. This research work benefits Canada's strong*presence in the game development industry, and offers abstractions and*techniques useful for the practical use of artificial intelligence in*the growing, real-world integration of virtual environments.