利用Concordia進行基於生成式代理模型的建模，其中行動基於物理、社會或數位空間。

摘要

基於代理的建模已有數十年的歷史，並被廣泛應用於社會科學和自然科學領域。這種研究方法的範疇正準備隨著大型語言模型（LLM）提供的新功能而大幅擴展。生成式基於代理的模型（GABM）不僅僅是傳統的基於代理的模型（ABM），其中代理彼此交談。相反，GABM是利用LLM構建的，以將常識應用於情境中，表現“合理”，回憶起常見的語義知識，生成API調用以控制諸如應用程式之類的數字技術，並在模擬內部和對外部查看的研究人員之間進行溝通。在這裡，我們介紹了Concordia，這是一個用於構建和操作GABM的庫。Concordia使得構建語言中介模擬物理或數字環境變得容易。Concordia代理通過一個靈活的組件系統來生成其行為，這個系統在LLM調用和聯想記憶檢索之間進行調解。一個名為遊戲主持人（GM）的特殊代理，靈感來自桌上角色扮演遊戲，負責模擬代理互動的環境。代理通過用自然語言描述他們想要做的事情來採取行動。然後，GM將他們的行動轉換為適當的實現。在模擬的物理世界中，GM檢查代理行動的物理合理性並描述其影響。在模擬諸如應用程式和服務等技術的數字環境中，GM可能處理API調用以與外部工具集成，例如通用AI助手（例如Bard、ChatGPT）和數字應用程式（例如日曆、電子郵件、搜索等）。Concordia旨在支持廣泛的應用，無論是在科學研究中還是通過模擬用戶和/或生成合成數據來評估真實數字服務的性能。

English

Agent-based modeling has been around for decades, and applied widely across the social and natural sciences. The scope of this research method is now poised to grow dramatically as it absorbs the new affordances provided by Large Language Models (LLM)s. Generative Agent-Based Models (GABM) are not just classic Agent-Based Models (ABM)s where the agents talk to one another. Rather, GABMs are constructed using an LLM to apply common sense to situations, act "reasonably", recall common semantic knowledge, produce API calls to control digital technologies like apps, and communicate both within the simulation and to researchers viewing it from the outside. Here we present Concordia, a library to facilitate constructing and working with GABMs. Concordia makes it easy to construct language-mediated simulations of physically- or digitally-grounded environments. Concordia agents produce their behavior using a flexible component system which mediates between two fundamental operations: LLM calls and associative memory retrieval. A special agent called the Game Master (GM), which was inspired by tabletop role-playing games, is responsible for simulating the environment where the agents interact. Agents take actions by describing what they want to do in natural language. The GM then translates their actions into appropriate implementations. In a simulated physical world, the GM checks the physical plausibility of agent actions and describes their effects. In digital environments simulating technologies such as apps and services, the GM may handle API calls to integrate with external tools such as general AI assistants (e.g., Bard, ChatGPT), and digital apps (e.g., Calendar, Email, Search, etc.). Concordia was designed to support a wide array of applications both in scientific research and for evaluating performance of real digital services by simulating users and/or generating synthetic data.

利用Concordia進行基於生成式代理模型的建模，其中行動基於物理、社會或數位空間。

Generative agent-based modeling with actions grounded in physical, social, or digital space using Concordia

摘要

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