請用此 Handle URI 來引用此文件:
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/98894完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 黃貞穎 | zh_TW |
| dc.contributor.advisor | Chen-Ying Huang | en |
| dc.contributor.author | 張廷宇 | zh_TW |
| dc.contributor.author | Ting-Yu Chang | en |
| dc.date.accessioned | 2025-08-20T16:11:18Z | - |
| dc.date.available | 2025-08-21 | - |
| dc.date.copyright | 2025-08-20 | - |
| dc.date.issued | 2025 | - |
| dc.date.submitted | 2025-08-12 | - |
| dc.identifier.citation | Thomas C. Schelling. The Strategy of Conflict. Harvard University Press, Cambridge, MA, 1960.
Judith Mehta, Chris Starmer, and Robert Sugden. The nature of salience: An experimental investigation of pure coordination games. The American Economic Review, 84(3):658-673, 1994. Dale O. Stahl and Paul W. Wilson. On players' models of other players: Theory and experimental evidence. Games and Economic Behavior, 10(1):218-254, 1995. Colin F. Camerer, Teck-Hua Ho, and Juin-Kuan Chong. A cognitive hierarchy model of games. The Quarterly Journal of Economics, 119(3):861-898, 2004. Robert Sugden. Thinking as a team: Towards an explanation of nonselfish behavior. Social Philosophy and Policy, 10(1):69-89, 1993. Robert Sugden. A theory of focal points. The Economic Journal, 105(430):533-550, 1995. Nicholas Bardsley, Judith Mehta, Chris Starmer, and Robert Sugden. Explaining focal points: Cognitive hierarchy theory versus team reasoning. The Economic Journal, 120(543):40-79, 2010. Shaun P. Hargreaves Heap, David Rojo Arjona, and Robert Sugden. Coordination when there are restricted and unrestricted options. Theory and Decision, 83:107-129, 2017. Daniel Perez-Zapata and Ian Apperly. An international study of pure coordination games: Adaptable solutions when intuitions are presumed to vary. has not been peer reviewed, 2022. Fulin Guo. Gpt in game theory experiments. arXiv preprint arXiv:2305.05516, 2023. Jesse Roberts, Kyle Moore, and Doug Fisher. Do large language models learn human-like stratgic preferences? arXiv preprint arXiv:2404.08710, 2024. Caoyun Fan, Jindou Chen, Yauhui Jin, and Hao He. Can large language models serve as rational players in game theory? a systematic analysis. Proceedings of the AAAI Conference on Artificial Intelligence, 38(16):17960-17967, 2024. Elif Akata, Lion Schulz, Julian Coda-Forno, Seong Joon Oh, Matthias Bethge, and Eric Schulz. Playing repeated games with large language models. Nature Human Behaviour, 2025. Wen-Jui Kuo, Tomas Sjöström, Yu-Ping Chen, Yen-Hsiang Wang, and Chen-Ying Huang. Intuition and deliberation: Two systems for strategizing in the brain. Science, 324(5926):519-522, April 2009. | - |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/98894 | - |
| dc.description.abstract | 我們在Prolific上舉行了一場全球的純協調遊戲實驗,其中包含四組參與者:與人類協調的人類(HH組)、與ChatGPT協調的人類(HG組)、與人類協調的ChatGPT(GH組)、與ChatGPT協調的ChatGPT(GG組)。比較四組的回答相似度,我們驚訝地發現相對於HH組,HG組的回答反而比較不像GH組。我們事前請了另外一小批參與者為我們的純協調遊戲題目標記出「可用性」最高的選項(A選項)與最不一樣的選項(O選項)。我們發現ChatGPT極度傾向於選擇A選項。HH組與HG組也傾向於選擇A選項,但相較之下HG組選了較多O選項,這正是前述發現的主因。結合參與者在李克特量表自評的直覺/思考傾向、每題所花秒數、參與時當地時間,我們擬合了兩個logistic generalized linear mixed models。我們認為,對HH組而言直覺的選擇是A選項,對HG組而言直覺的選擇是O選項。我們還測試並整理了人類、ChatGPT、Claude、Llama三種模型在五種純協調遊戲中的決策。 | zh_TW |
| dc.description.abstract | We conducted a global pure coordination game experiment on Prolific with four participant groups: humans coordinating with humans (HH), humans coordinating with ChatGPT (HG), ChatGPT coordinating with humans (GH), and ChatGPT coordinating with ChatGPT (GG). Surprisingly, we found that compared to the HH group, the responses of the HG group were actually less similar to those of the GH group. We asked a separate group of participants to label the option with the highest "availability" (A option) and the odd-one-out (O option) for each coordination item. We found that ChatGPT participants had a strong tendency to choose A options, but HG participants selected more O options than HH participants, which mainly explains the previous finding. Using participants' intuition-thinking tendency, response time per trial, and local time of participation, we fit two logistic generalized linear mixed models. Based on the results, we argue that for the HH group, A was the intuitive choice, while for the HG group, O was the intuitive choice. | en |
| dc.description.provenance | Submitted by admin ntu (admin@lib.ntu.edu.tw) on 2025-08-20T16:11:18Z No. of bitstreams: 0 | en |
| dc.description.provenance | Made available in DSpace on 2025-08-20T16:11:18Z (GMT). No. of bitstreams: 0 | en |
| dc.description.tableofcontents | Acknowledgements ii
摘要 iv Abstract v Contents vi List of Figures ix List of Tables xi Chapter 1 Introduction 1 1.1 Pure Coordination Games 1 1.2 Classical Theories 2 1.3 Recent Developments 3 1.4 Large Language Models in Game Experiments 4 1.5 Overview of This Study 5 Chapter 2 Experimental Design 7 2.1 Participants 7 2.2 Coordination Groups 8 2.3 Evaluation Group 10 2.4 Materials 11 Chapter 3 Results 12 3.1 Alignment Scores (within-group and between-group) 12 3.2 Visualization of A and O Choices by Group 17 3.3 Exploratory Regression Analyses of A/A+O Proportion 20 3.3.1 group 20 3.3.2 Intuition/Thinking Preference 21 3.3.3 Local Time of Participation 23 3.4 Logistic GLMMs of A and O Choices 25 Chapter 4 LLMs in Diverse Coordination Games 29 4.1 Claude and Llama in Our Word Game 29 4.2 ChatGPT, Claude, and Llama in the Number Game 31 4.3 ChatGPT, Claude, and Llama in the Box Game 34 4.4 ChatGPT, Claude, and Llama in the Left-or-Right Game 36 4.5 ChatGPT, Claude, and Llama in the Pie-Cutting Game 38 Chapter 5 Conclusion 39 5.1 Summary 39 5.2 Future Directions 40 5.3 Discussion 41 References 43 Appendix A -- Instructions and Questionnaires 45 A.1 Instructions 45 A.2 Questionnaires 47 Appendix B -- Supplementary Analyses 52 B.1 Analyses Using A and O Salience Ratings 52 B.2 Downweighting Participants with Extreme IntuiThink 60 Appendix C -- Informal Testing of Prompt Variations Across LLMs 62 | - |
| dc.language.iso | en | - |
| dc.subject | 直覺 | zh_TW |
| dc.subject | 協調賽局 | zh_TW |
| dc.subject | 大型語言模型 | zh_TW |
| dc.subject | Logistic GLMMs | zh_TW |
| dc.subject | Large Language Models | en |
| dc.subject | Intuition | en |
| dc.subject | Coordination Games | en |
| dc.subject | Logistic GLMMs | en |
| dc.title | 人類與GPT的純協調遊戲 | zh_TW |
| dc.title | A Pure Coordination Game between Humans and GPT | en |
| dc.type | Thesis | - |
| dc.date.schoolyear | 113-2 | - |
| dc.description.degree | 碩士 | - |
| dc.contributor.oralexamcommittee | 陳慶池;陳俊廷;賴建宇 | zh_TW |
| dc.contributor.oralexamcommittee | Jimmy Chan;Chun-Ting Chen;Chien-Yu Lai | en |
| dc.subject.keyword | 直覺,協調賽局,大型語言模型,Logistic GLMMs, | zh_TW |
| dc.subject.keyword | Intuition,Coordination Games,Large Language Models,Logistic GLMMs, | en |
| dc.relation.page | 64 | - |
| dc.identifier.doi | 10.6342/NTU202504234 | - |
| dc.rights.note | 同意授權(全球公開) | - |
| dc.date.accepted | 2025-08-14 | - |
| dc.contributor.author-college | 社會科學院 | - |
| dc.contributor.author-dept | 經濟學系 | - |
| dc.date.embargo-lift | 2025-08-21 | - |
| 顯示於系所單位: | 經濟學系 | |
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