{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/digital-player-evaluating-large-language","title":"Digital Player: Evaluating Large Language Models based Human-like Agent in Games","arxiv_id":"2502.20807","date":"2025-02-28","proceeding":null,"authors":["Jiawei Wang","Kai Wang","Shaojie Lin","Runze Wu","Bihan Xu","Lingeng Jiang","Shiwei Zhao","Renyu Zhu","Haoyu Liu","Zhipeng Hu","Zhong Fan","Le Li","Tangjie Lyu","Changjie Fan"],"abstract":"With the rapid advancement of Large Language Models (LLMs), LLM-based autonomous agents have shown the potential to function as digital employees, such as digital analysts, teachers, and programmers. In this paper, we develop an application-level testbed based on the open-source strategy game \"Unciv\", which has millions of active players, to enable researchers to build a \"data flywheel\" for studying human-like agents in the \"digital players\" task. This \"Civilization\"-like game features expansive decision-making spaces along with rich linguistic interactions such as diplomatic negotiations and acts of deception, posing significant challenges for LLM-based agents in terms of numerical reasoning and long-term planning. Another challenge for \"digital players\" is to generate human-like responses for social interaction, collaboration, and negotiation with human players. The open-source project can be found at https:/github.com/fuxiAIlab/CivAgent.","url_abs":"https://arxiv.org/abs/2502.20807v1","url_pdf":"https://arxiv.org/pdf/2502.20807v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"digital-player-evaluating-large-language","repo_url":"https://github.com/fuxiailab/civagent","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"decision-making","task_name":"Decision Making"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2502.20807","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2502.20807"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. 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