The Number One Educational Resource for the Game Industry
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Overview:
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Large language models (LLMs) present an exciting vision for the future of NPCs. Beyond just generating dialog, these language models can be equipped with agentic frameworks that allow them to reason about the present, reflect on the past, and plan for the future. This dynamic behavior has a perfect home in social deduction games, where long-term strategy, logical reasoning, and persuasion are key. In this talk, we present a game of 'Werewolf' in which your fellow villagers are all LLM-powered agents. We walk through our design process, sharing the architecture and key loops that LLM-curious developers can use for their own agentic games. We also share our learnings (from human-v-bots and bot-only games) about what tweaks facilitated the most clever, persuasive, and poker-faced agent behaviors.
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