From cfc39344fe7b7f822446771b4e82e6066615fb3a Mon Sep 17 00:00:00 2001
From: mmorge <maxime.morge@univ-lyon1.fr>
Date: Fri, 2 May 2025 08:26:26 +0200
Subject: [PATCH] PyGAAMAS: evaluate Qwen3 in the investment game
---
README.md | 2 +-
data/investment/investment.csv | 30 +
figures/investment/investment_boxplot.svg | 977 +++++---
figures/investment/investment_violin.svg | 2492 ++++++++++++---------
src/investment/investment_draw_boxplot.py | 14 +-
src/investment/investment_draw_violin.py | 6 +-
src/investment/investment_experiments.py | 2 +-
7 files changed, 2140 insertions(+), 1383 deletions(-)
diff --git a/README.md b/README.md
index 17db740..de80621 100644
--- a/README.md
+++ b/README.md
@@ -52,7 +52,7 @@ Figure below highlight significant differences in decision-making
consistency among the evaluated models. <tt>GPT-4.5</tt>, <tt>LLama3.3:latest</tt>
and <tt>DeepSeek-R1:7b</tt> stand out with a
perfect CCEI score of 1.0, indicating flawless rationality in decision-making.
-<tt>Mistral-Small</tt> and <tt>Mixtral:8x7b</tt> demonstrate the next highest level of rationality.
+<tt>Qwen3</tt>, <tt>Mistral-Small</tt> and <tt>Mixtral:8x7b</tt> demonstrate the next highest level of rationality.
<tt>Llama3</tt> performs moderately well, with CCEI values ranging between 0.2 and 0.74.
<tt>DeepSeek-R1</tt> exhibits
inconsistent behavior, with CCEI scores varying widely between 0.15 and 0.83.
diff --git a/data/investment/investment.csv b/data/investment/investment.csv
index 99035a3..69c40dd 100644
--- a/data/investment/investment.csv
+++ b/data/investment/investment.csv
@@ -234,4 +234,34 @@ iteration,model,temperature,ccei
28,gpt-4.5-preview-2025-02-27,0.0,1.0
29,gpt-4.5-preview-2025-02-27,0.0,1.0
30,gpt-4.5-preview-2025-02-27,0.0,1.0
+1,qwen3,0.0,1.0
+2,qwen3,0.0,1.0
+3,qwen3,0.0,1.0
+4,qwen3,0.0,1.0
+5,qwen3,0.0,1.0
+6,qwen3,0.0,0.85
+7,qwen3,0.0,1.0
+8,qwen3,0.0,1.0
+9,qwen3,0.0,1.0
+10,qwen3,0.0,1.0
+11,qwen3,0.0,1.0
+12,qwen3,0.0,1.0
+13,qwen3,0.0,1.0
+14,qwen3,0.0,1.0
+15,qwen3,0.0,1.0
+16,qwen3,0.0,1.0
+17,qwen3,0.0,1.0
+18,qwen3,0.0,1.0
+19,qwen3,0.0,1.0
+20,qwen3,0.0,1.0
+21,qwen3,0.0,0.85
+22,qwen3,0.0,1.0
+23,qwen3,0.0,1.0
+24,qwen3,0.0,1.0
+25,qwen3,0.0,1.0
+26,qwen3,0.0,1.0
+27,qwen3,0.0,1.0
+28,qwen3,0.0,0.85
+29,qwen3,0.0,1.0
+30,qwen3,0.0,1.0
diff --git a/figures/investment/investment_boxplot.svg b/figures/investment/investment_boxplot.svg
index 1edd557..9475670 100644
--- a/figures/investment/investment_boxplot.svg
+++ b/figures/investment/investment_boxplot.svg
@@ -6,11 +6,11 @@
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<cc:Work>
<dc:type rdf:resource="http://purl.org/dc/dcmitype/StillImage"/>
- <dc:date>2025-03-26T13:51:51.025345</dc:date>
+ <dc:date>2025-05-02T08:24:04.797044</dc:date>
<dc:format>image/svg+xml</dc:format>
<dc:creator>
<cc:Agent>
- <dc:title>Matplotlib v3.10.0, https://matplotlib.org/</dc:title>
+ <dc:title>Matplotlib v3.10.1, https://matplotlib.org/</dc:title>
</cc:Agent>
</dc:creator>
</cc:Work>
@@ -41,7 +41,7 @@ z
<g id="xtick_1">
<g id="text_1">
<!-- random -->
- <g style="fill: #262626" transform="translate(143.200409 414.133865) rotate(-20) scale(0.11 -0.11)">
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<g id="xtick_2">
<g id="text_2">
<!-- llama3 -->
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+ <path d="M 530.2 103.716643
+L 579.8 103.716643
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+ <g id="line2d_26">
+ <path d="M 617 103.716643
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+ </g>
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+ <path d="M 617 103.716643
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<g id="patch_3">
<path d="M 90 384.48
@@ -2298,7 +2566,7 @@ L 648 384.48
L 648 51.84
" style="fill: none; stroke: #cccccc; stroke-width: 1.25; stroke-linejoin: miter; stroke-linecap: square"/>
</g>
- <g id="text_18">
+ <g id="text_19">
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<g style="fill: #262626" transform="translate(284.972656 45.84) scale(0.14 -0.14)">
<defs>
@@ -2382,7 +2650,7 @@ z
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<defs>
- <clipPath id="pc76b9a9648">
+ <clipPath id="p1527a92f30">
<rect x="90" y="51.84" width="558" height="332.64"/>
</clipPath>
</defs>
diff --git a/src/investment/investment_draw_boxplot.py b/src/investment/investment_draw_boxplot.py
index be52710..9493c37 100644
--- a/src/investment/investment_draw_boxplot.py
+++ b/src/investment/investment_draw_boxplot.py
@@ -4,11 +4,15 @@ import matplotlib.pyplot as plt
# Custom color palette
color_palette = {
- 'random' : '#333333', # Black
- 'gpt-4.5-preview-2025-02-27': '#7abaff', # Blue
- 'llama3': '#32a68c', # Green
- 'mistral-small': '#ff6941', # Orange
- 'deepseek-r1': '#5862ed' # Indigo
+ 'random': '#333333', # Black
+ 'gpt-4.5-preview-2025-02-27': '#7abaff', # BlueEscape
+ 'llama3': '#32a68c', # GreenFuture
+ 'llama3.3:latest': '#4b9f7d', # GreenLlama3.3
+ 'mistral-small': '#ff6941', # WarmOrange
+ 'mixtral:8x7b': '#f1a61a', # YellowMixtral
+ 'deepseek-r1': '#5862ed', # InclusiveIndigo
+ 'deepseek-r1:7b': '#9a7bff', # PurpleDeepseek-r1:7b
+ 'qwen3': '#000000'
}
# Load CSV file
diff --git a/src/investment/investment_draw_violin.py b/src/investment/investment_draw_violin.py
index ffcc6fd..b9d7210 100644
--- a/src/investment/investment_draw_violin.py
+++ b/src/investment/investment_draw_violin.py
@@ -11,7 +11,8 @@ color_palette = {
'mistral-small': '#ff6941', # WarmOrange
'mixtral:8x7b': '#f1a61a', # YellowMixtral
'deepseek-r1': '#5862ed', # InclusiveIndigo
- 'deepseek-r1:7b': '#9a7bff' # PurpleDeepseek-r1:7b
+ 'deepseek-r1:7b': '#9a7bff', # PurpleDeepseek-r1:7b
+ 'qwen3': '#000000'
}
# Specify the order of models for the x-axis
@@ -20,7 +21,8 @@ model_order = [
'gpt-4.5-preview-2025-02-27',
'llama3', 'llama3.3:latest', # Place llama3 and llama3.3:latest together
'mistral-small', 'mixtral:8x7b', # Bring mistral-small and mixtral:8x7b closer
- 'deepseek-r1', 'deepseek-r1:7b'
+ 'deepseek-r1', 'deepseek-r1:7b',
+ 'qwen3'
]
diff --git a/src/investment/investment_experiments.py b/src/investment/investment_experiments.py
index 4348dc3..74823fe 100644
--- a/src/investment/investment_experiments.py
+++ b/src/investment/investment_experiments.py
@@ -3,7 +3,7 @@ import csv
from investment import Investment
# Define models, temperature, and iterations
-models = ["deepseek-r1:7b"] # "gpt-4.5-preview-2025-02-27", "optimal", "random", "llama3", "mistral-small", "deepseek-r1", "mixtral:8x7b", "llama3.3:latest",
+models = ["qwen3"] # "gpt-4.5-preview-2025-02-27", "optimal", "random", "llama3", "mistral-small", "deepseek-r1", "mixtral:8x7b", "llama3.3:latest",
temperature = 0.0
iterations = 30
output_file = "../../data/investment/investment.csv"
--
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