内在动机一般同伴npc通过耦合授权最大化

C. Guckelsberger, Christoph Salge, S. Colton
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引用次数: 23

摘要

游戏中的非玩家角色(npc)通常是硬编码的,或者依赖于预先设定的目标,因此他们很难在不断变化和不可预测的游戏世界中做出明智的行为。为了让它们适应程序内容生成的新发展,我们引入了耦合授权最大化原则作为游戏npc的内在动机。我们专注于开发一个通用的游戏伴侣,旨在帮助玩家实现他们的目标。我们根据三个直观和抽象的同伴职责来评估我们的方法。我们在地下城爬行游戏测试平台中为每个任务开发专门的场景,并提供定性证据,证明突发NPC行为履行了这些任务。我们认为这种通用方法可以加速NPC AI的开发,改善自动游戏进化,并将NPC引入完整的游戏生成系统。
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Intrinsically motivated general companion NPCs via Coupled Empowerment Maximisation
Non-player characters (NPCs) in games are traditionally hard-coded or dependent on pre-specified goals, and consequently struggle to behave sensibly in ever-changing and possibly unpredictable game worlds. To make them fit for new developments in procedural content generation, we introduce the principle of Coupled Empowerment Maximisation as an intrinsic motivation for game NPCs. We focus on the development of a general game companion, designed to support the player in achieving their goals. We evaluate our approach against three intuitive and abstract companion duties. We develop dedicated scenarios for each duty in a dungeon-crawler game testbed, and provide qualitative evidence that the emergent NPC behaviour fulfils these duties. We argue that this generic approach can speed up NPC AI development, improve automatic game evolution and introduce NPCs to full game-generation systems.
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