Year: 2024
Type: conference-paper
Abstract: Non-player Characters (NPCs) in video games have been ubiquitous for many years. However, the interactions players have with these NPCs have typically been limited to pre-defined dialogue options, limiting the player’s immersion within the game world. Recent advances in AI and Natural Language Processing (NLP) have opened up new possibilities for creating NPCs that are capable of engaging in more naturalistic conversational interactions with players. We explore the use of GPT-powered NPCs in video games in the context of virtual reality and develop NPCs that possess long-term memory, autonomous behaviour, and believable interactions. We pro pose a novel GPT-NPC framework that utilises GPT models, in a modularised approach, to generate coherent and engaging dialogue for NPCs, while also incorporating thought and emotion modelling to create more immersive characters. To assess the effectiveness of our framework, human participants are involved, to rate the human likeness of NPCs. We demonstrate a mixed level of general believability, showing a rating score of 60%. From this, we further discuss ways to better improve and utilise the framework. This paper aims to contribute to the growing field of AI-powered game development and create more engaging gaming experiences for players.
Authors: D Ogunlesi (21970520), X Wang (1378959)
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6982100336
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