{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:RTDRFYLHSNTOLLMU5W44FVBNQY","short_pith_number":"pith:RTDRFYLH","schema_version":"1.0","canonical_sha256":"8cc712e1679366e5ad94edb9c2d42d863b102f5e967ba439dc0c3d309b60cfb5","source":{"kind":"arxiv","id":"2506.04699","version":1},"attestation_state":"computed","paper":{"title":"Empowering Economic Simulation for Massively Multiplayer Online Games through Generative Agent-Based Modeling","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Bihan Xu, Changjie Fan, Haoyu Liu, Jiangze Han, Jiawei Wang, Kai Wang, Le Li, Runze Wu, Shiwei Zhao, Tangjie Lv, Xin Tong, Zhenya Huang, Zhipeng Hu","submitted_at":"2025-06-05T07:21:13Z","abstract_excerpt":"Within the domain of Massively Multiplayer Online (MMO) economy research, Agent-Based Modeling (ABM) has emerged as a robust tool for analyzing game economics, evolving from rule-based agents to decision-making agents enhanced by reinforcement learning. Nevertheless, existing works encounter significant challenges when attempting to emulate human-like economic activities among agents, particularly regarding agent reliability, sociability, and interpretability. In this study, we take a preliminary step in introducing a novel approach using Large Language Models (LLMs) in MMO economy simulation."},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2506.04699","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2025-06-05T07:21:13Z","cross_cats_sorted":[],"title_canon_sha256":"397eb9ac2a205c0cf8871d90eed771360997c367ab1ea8875930b05a303003a7","abstract_canon_sha256":"a0390353a0b0871c3e08cbc260ecd261689655f59d328b2261db549aa4d06a61"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:16:19.118775Z","signature_b64":"d6mA2R/rdNROj72nnRtcGJjb3M7nK3sWiAaed/TXnMun2M3OGDzaDidgWcqp3Az/vrCZUqvuQMlIY67BFrMTAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8cc712e1679366e5ad94edb9c2d42d863b102f5e967ba439dc0c3d309b60cfb5","last_reissued_at":"2026-07-05T11:16:19.118309Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:16:19.118309Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Empowering Economic Simulation for Massively Multiplayer Online Games through Generative Agent-Based Modeling","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Bihan Xu, Changjie Fan, Haoyu Liu, Jiangze Han, Jiawei Wang, Kai Wang, Le Li, Runze Wu, Shiwei Zhao, Tangjie Lv, Xin Tong, Zhenya Huang, Zhipeng Hu","submitted_at":"2025-06-05T07:21:13Z","abstract_excerpt":"Within the domain of Massively Multiplayer Online (MMO) economy research, Agent-Based Modeling (ABM) has emerged as a robust tool for analyzing game economics, evolving from rule-based agents to decision-making agents enhanced by reinforcement learning. Nevertheless, existing works encounter significant challenges when attempting to emulate human-like economic activities among agents, particularly regarding agent reliability, sociability, and interpretability. In this study, we take a preliminary step in introducing a novel approach using Large Language Models (LLMs) in MMO economy simulation."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.04699","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2506.04699/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2506.04699","created_at":"2026-07-05T11:16:19.118375+00:00"},{"alias_kind":"arxiv_version","alias_value":"2506.04699v1","created_at":"2026-07-05T11:16:19.118375+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.04699","created_at":"2026-07-05T11:16:19.118375+00:00"},{"alias_kind":"pith_short_12","alias_value":"RTDRFYLHSNTO","created_at":"2026-07-05T11:16:19.118375+00:00"},{"alias_kind":"pith_short_16","alias_value":"RTDRFYLHSNTOLLMU","created_at":"2026-07-05T11:16:19.118375+00:00"},{"alias_kind":"pith_short_8","alias_value":"RTDRFYLH","created_at":"2026-07-05T11:16:19.118375+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/RTDRFYLHSNTOLLMU5W44FVBNQY","json":"https://pith.science/pith/RTDRFYLHSNTOLLMU5W44FVBNQY.json","graph_json":"https://pith.science/api/pith-number/RTDRFYLHSNTOLLMU5W44FVBNQY/graph.json","events_json":"https://pith.science/api/pith-number/RTDRFYLHSNTOLLMU5W44FVBNQY/events.json","paper":"https://pith.science/paper/RTDRFYLH"},"agent_actions":{"view_html":"https://pith.science/pith/RTDRFYLHSNTOLLMU5W44FVBNQY","download_json":"https://pith.science/pith/RTDRFYLHSNTOLLMU5W44FVBNQY.json","view_paper":"https://pith.science/paper/RTDRFYLH","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2506.04699&json=true","fetch_graph":"https://pith.science/api/pith-number/RTDRFYLHSNTOLLMU5W44FVBNQY/graph.json","fetch_events":"https://pith.science/api/pith-number/RTDRFYLHSNTOLLMU5W44FVBNQY/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/RTDRFYLHSNTOLLMU5W44FVBNQY/action/timestamp_anchor","attest_storage":"https://pith.science/pith/RTDRFYLHSNTOLLMU5W44FVBNQY/action/storage_attestation","attest_author":"https://pith.science/pith/RTDRFYLHSNTOLLMU5W44FVBNQY/action/author_attestation","sign_citation":"https://pith.science/pith/RTDRFYLHSNTOLLMU5W44FVBNQY/action/citation_signature","submit_replication":"https://pith.science/pith/RTDRFYLHSNTOLLMU5W44FVBNQY/action/replication_record"}},"created_at":"2026-07-05T11:16:19.118375+00:00","updated_at":"2026-07-05T11:16:19.118375+00:00"}