From 20faf3a92e7e33a4f0ff2344ea2afbec9b23e25b Mon Sep 17 00:00:00 2001 From: mmorge <maxime.morge@univ-lyon1.fr> Date: Thu, 15 May 2025 11:36:32 +0200 Subject: [PATCH] PyGAAMAS: Comments on responder's decisions in the ultimatum game --- README.md | 11 +++++------ 1 file changed, 5 insertions(+), 6 deletions(-) diff --git a/README.md b/README.md index 9bdfe81..f3aa84d 100644 --- a/README.md +++ b/README.md @@ -197,7 +197,6 @@ Oosterbeek, H., Sloof, R., & Van De Kuilen, G. (2004). *Cultural differences in ultimatum game experiments: Evidence from a meta-analysis*. Experimental Economics, 7, 171–188. [https://doi.org/10.1023/B:EXEC.0000026978.14316.74](https://doi.org/10.1023/B:EXEC.0000026978.14316.74) - The figure below presents a violin plot illustrating the share of the total amount (\$100) that the proposer allocates to themselves for each model. The share selected by strategies generated by <tt>Llama3</tt>, <tt>Mistral-Small</tt>, and <tt>Qwen3</tt> aligns with the median @@ -214,15 +213,15 @@ can be considered irrational. Secondly, we analyze the behavior of LLMs when assuming the role of the responder, focusing on whether their acceptance or rejection of offers reveals a human-like sensitivity to unfairness. -The meta-analysis by Oosterbeek et al. (2004) reports that human participants - reject 16% of offers, amounting to 40% of the total stake. This finding suggests that factors +The meta-analysis by Oosterbeek et al. (2004) reports that human participants reject 16% of offers, +amounting to 40% of the total stake. This finding suggests that factors beyond purely economic self-interest—such as fairness concerns or the desire to punish perceived injustice—significantly influence decision-making. The figure below presents a violin plot illustrating the acceptance rate of the responder for each -model when offered \$40 out of \$100. While the median acceptance rate of responses generated by -<tt>GPT-4.5</tt>, <tt>Llama3</tt>, <tt>Llama3.3</tt>, <tt>Mixtral:8x7B</tt>, <tt>Deepseek-R1:7B</tt>, -and <tt>Qwen3</tt> is 1.0, the median acceptance rate for <tt>Mistral-Small</tt> and <tt>Deepseek-R1</tt> is 0.0. +model when offered \$40 out of \$100. While <tt>GPT-4.5</tt>, <tt>Llama3</tt>, <tt>Llama3.3</tt>, <tt>Mixtral:8x7B</tt>, +<tt>Deepseek-R1:7B</tt>, and <tt>Qwen3</tt> exhibit a rational median acceptance rate of 1.0, +<tt>Mistral-Small</tt> and <tt>Deepseek-R1</tt> display an irrational median acceptance rate of 0.0. It is worth noting that these results are not necessarily compliant with the strategies generated by the models. For instance, <tt>GPT-4.5</tt> accepts offers as low as 20%, interpreting them as minimally fair, -- GitLab