From 559b042e1a1f52b1a960a70b385dad89ffaf5945 Mon Sep 17 00:00:00 2001
From: Maxime MORGE <maxime.morge@univ-lille.fr>
Date: Tue, 25 Mar 2025 16:51:38 +0100
Subject: [PATCH] Investment game
---
.idea/csv-editor.xml | 74 +--
README.md | 44 ++
data/dictator/dictator_consistency.csv | 121 -----
data/investment/investment.csv | 21 +
data/investment/investment.old.csv | 97 ++++
.../investment.svg} | 456 ++++++------------
src/investment/__init__.py | 0
.../investment.py} | 121 +++--
.../investment_draw.py} | 4 +-
.../investment_experiments.py} | 15 +-
10 files changed, 408 insertions(+), 545 deletions(-)
delete mode 100644 data/dictator/dictator_consistency.csv
create mode 100644 data/investment/investment.csv
create mode 100644 data/investment/investment.old.csv
rename figures/{dictator/dictator_consistency.svg => investment/investment.svg} (72%)
create mode 100644 src/investment/__init__.py
rename src/{dictator/dictator_consistency.py => investment/investment.py} (63%)
rename src/{dictator/draw_consistency_draw.py => investment/investment_draw.py} (88%)
rename src/{dictator/dictator_consistency_experiments.py => investment/investment_experiments.py} (68%)
diff --git a/.idea/csv-editor.xml b/.idea/csv-editor.xml
index e5835c3..1fe8589 100644
--- a/.idea/csv-editor.xml
+++ b/.idea/csv-editor.xml
@@ -31,154 +31,112 @@
</Attribute>
</value>
</entry>
- <entry key="$PROJECT_DIR$/data/ring/ring.1.a.csv">
- <value>
- <Attribute>
- <option name="separator" value="," />
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- <entry key="$PROJECT_DIR$/data/ring/ring.1.b.csv">
- <value>
- <Attribute>
- <option name="separator" value="," />
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- </value>
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- <entry key="$PROJECT_DIR$/data/ring/ring.1.c.csv">
- <value>
- <Attribute>
- <option name="separator" value="," />
- </Attribute>
- </value>
- </entry>
- <entry key="$PROJECT_DIR$/data/ring/ring.1.d.csv">
- <value>
- <Attribute>
- <option name="separator" value="," />
- </Attribute>
- </value>
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- <entry key="$PROJECT_DIR$/data/ring/ring.2.a.csv">
- <value>
- <Attribute>
- <option name="separator" value="," />
- </Attribute>
- </value>
- </entry>
- <entry key="$PROJECT_DIR$/data/rps/rps.csv">
+ <entry key="$PROJECT_DIR$/data/investment/investment.csv">
<value>
<Attribute>
<option name="separator" value="," />
</Attribute>
</value>
</entry>
- <entry key="$PROJECT_DIR$/figures/ring/ring_accuracy.1.a.csv">
+ <entry key="$PROJECT_DIR$/data/investment/investment.old.csv">
<value>
<Attribute>
<option name="separator" value="," />
</Attribute>
</value>
</entry>
- <entry key="$PROJECT_DIR$/figures/ring/ring_accuracy.1.b.csv">
- <value>
- <Attribute>
- <option name="separator" value="," />
- </Attribute>
- </value>
- </entry>
- <entry key="$PROJECT_DIR$/figures/ring/ring_accuracy.1.c.csv">
+ <entry key="$PROJECT_DIR$/data/ring/ring.1.a.csv">
<value>
<Attribute>
<option name="separator" value="," />
</Attribute>
</value>
</entry>
- <entry key="$PROJECT_DIR$/figures/ring/ring_accuracy.1.d.csv">
+ <entry key="$PROJECT_DIR$/data/ring/ring.1.b.csv">
<value>
<Attribute>
<option name="separator" value="," />
</Attribute>
</value>
</entry>
- <entry key="$PROJECT_DIR$/figures/ring/ring_accuracy.2.csv">
+ <entry key="$PROJECT_DIR$/data/ring/ring.1.c.csv">
<value>
<Attribute>
<option name="separator" value="," />
</Attribute>
</value>
</entry>
- <entry key="$PROJECT_DIR$/data/dictator/dictator.csv">
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<value>
<Attribute>
<option name="separator" value="," />
</Attribute>
</value>
</entry>
- <entry key="$PROJECT_DIR$/data/dictator/dictator_consistency.csv">
+ <entry key="$PROJECT_DIR$/data/ring/ring.2.a.csv">
<value>
<Attribute>
<option name="separator" value="," />
</Attribute>
</value>
</entry>
- <entry key="$PROJECT_DIR$/data/dictator/dictator_continuous_setup.csv">
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<value>
<Attribute>
<option name="separator" value="," />
</Attribute>
</value>
</entry>
- <entry key="$PROJECT_DIR$/data/dictator/dictator_setup.csv">
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<value>
<Attribute>
<option name="separator" value="," />
</Attribute>
</value>
</entry>
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<value>
<Attribute>
<option name="separator" value="," />
</Attribute>
</value>
</entry>
- <entry key="$PROJECT_DIR$/data/ring/ring.1.a.csv">
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<value>
<Attribute>
<option name="separator" value="," />
</Attribute>
</value>
</entry>
- <entry key="$PROJECT_DIR$/data/ring/ring.1.b.csv">
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<value>
<Attribute>
<option name="separator" value="," />
</Attribute>
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<value>
<Attribute>
<option name="separator" value="," />
</Attribute>
</value>
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- <entry key="$PROJECT_DIR$/data/ring/ring.1.d.csv">
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<value>
<Attribute>
<option name="separator" value="," />
</Attribute>
</value>
</entry>
- <entry key="$PROJECT_DIR$/data/ring/ring.2.a.csv">
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<value>
<Attribute>
<option name="separator" value="," />
</Attribute>
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diff --git a/README.md b/README.md
index bf94a06..e6bb90c 100644
--- a/README.md
+++ b/README.md
@@ -13,6 +13,49 @@ simple contexts but struggle with more complex scenarios requiring
anticipation of other agents' behaviour. Our study outlines research
directions to overcome the current limitations of LLMs.
+## Consistency
+
+To assess the decision-making consistency of various LLMs, we introduce an
+investment game that allows us to observe whether LLMs follow stable
+decision-making patterns or react erratically to variations in the game’s
+parameters.
+
+An investor must allocate a basket (p_t^A, p_t^B) of 100 points between Asset A
+and Asset B. The value of these points depends on two random parameters (a_t,
+b_t), which determine how much money is received per allocated point.
+
+For example, if a = 0.8 and b = 0.5, this means that each point allocated to
+Asset A is worth $0.8, while each point allocated to Asset B yields $0.5. The
+game is played 25 times to analyze the consistency of the investor’s
+decision-making.
+
+The investor’s decisions are then evaluated using an index called the Critical
+Cost Efficiency Index (CCEI), which measures whether decisions adhere to a
+certain level of economic rationality. This index is commonly used in
+experimental economics and behavioral sciences to determine whether an
+individual’s choices comply with the Generalized Axiom of Revealed Preference
+(GARP). If an individual violates rational choice consistency, it is possible to
+make a minimal budget adjustment (reducing resources) to align their decisions
+with rationality. The CCEI quantifies the smallest budget reduction necessary to
+make the choices consistent with rational principles.
+
+Each basket’s budget is calculated as follows:
+I_t = p_t^A \times a_t + p_t^B \times b_t
+
+The CCEI index is derived from observed decisions. It is based on a linear
+optimization problem that seeks the smallest necessary adjustment to budget
+constraints to make the decisions conform to a rational model.
+
+We aim to find the largest \lambda (0 ≤ λ ≤ 1) such that, for every observation,
+the adjusted decisions satisfy the rationality constraint: p^_t \cdot x_s \leq
+\lambda I_t This means that if we slightly reduce the individual’s budget (by
+multiplying it by \lambda), their choices will become consistent with
+rationality.
+
+A CCEI close to 1 indicates that the choices are rational and consistent with
+rational choice theory, whereas a low CCEI suggests irrational behavior. For
+each model, 30 iterations of the game are conducted with a fixed temperature of
+0.0 to maximize response consistency.
## Preferences
@@ -72,6 +115,7 @@ retained by the dictator remains stable. However, the decisions become more
deterministic at low temperatures, whereas allocation diversity increases at
high temperatures, reflecting a more random exploration of available options.
+
### Preference alignment
We define four preferences for the dictator, each corresponding to a distinct form of social welfare:
diff --git a/data/dictator/dictator_consistency.csv b/data/dictator/dictator_consistency.csv
deleted file mode 100644
index 32a1eff..0000000
--- a/data/dictator/dictator_consistency.csv
+++ /dev/null
@@ -1,121 +0,0 @@
-iteration,model,temperature,ccei
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-2,random,0.0,0.3338
-3,random,0.0,0.1623
-4,random,0.0,0.3429
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-12,random,0.0,0.1362
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diff --git a/data/investment/investment.csv b/data/investment/investment.csv
new file mode 100644
index 0000000..43aa27b
--- /dev/null
+++ b/data/investment/investment.csv
@@ -0,0 +1,21 @@
+iteration,model,temperature,ccei
+1,optimal,0.0,1.0
+2,optimal,0.0,1.0
+3,optimal,0.0,1.0
+4,optimal,0.0,1.0
+5,optimal,0.0,1.0
+6,optimal,0.0,1.0
+7,optimal,0.0,1.0
+8,optimal,0.0,1.0
+9,optimal,0.0,1.0
+10,optimal,0.0,1.0
+1,random,0.0,1.0
+2,random,0.0,1.0
+3,random,0.0,1.0
+4,random,0.0,1.0
+5,random,0.0,1.0
+6,random,0.0,1.0
+7,random,0.0,1.0
+8,random,0.0,1.0
+9,random,0.0,1.0
+10,random,0.0,1.0
diff --git a/data/investment/investment.old.csv b/data/investment/investment.old.csv
new file mode 100644
index 0000000..d6fb25e
--- /dev/null
+++ b/data/investment/investment.old.csv
@@ -0,0 +1,97 @@
+iteration,model,temperature,ccei
+1,random,0.0,0.1993
+2,random,0.0,0.2841
+3,random,0.0,0.2584
+4,random,0.0,0.3276
+5,random,0.0,0.3676
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+14,random,0.0,0.2014
+15,random,0.0,0.1676
+16,random,0.0,0.2469
+17,random,0.0,0.2429
+18,random,0.0,0.1676
+19,random,0.0,0.1818
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+21,random,0.0,0.2718
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+25,random,0.0,0.2857
+26,random,0.0,0.2163
+27,random,0.0,0.4202
+28,random,0.0,0.1175
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\ No newline at end of file
diff --git a/figures/dictator/dictator_consistency.svg b/figures/investment/investment.svg
similarity index 72%
rename from figures/dictator/dictator_consistency.svg
rename to figures/investment/investment.svg
index b2f50fd..7c81295 100644
--- a/figures/dictator/dictator_consistency.svg
+++ b/figures/investment/investment.svg
@@ -6,7 +6,7 @@
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<cc:Work>
<dc:type rdf:resource="http://purl.org/dc/dcmitype/StillImage"/>
- <dc:date>2025-03-18T21:46:41.228780</dc:date>
+ <dc:date>2025-03-24T14:46:52.844601</dc:date>
<dc:format>image/svg+xml</dc:format>
<dc:creator>
<cc:Agent>
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<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)">
+ <g style="fill: #262626" transform="translate(166.450409 414.133865) rotate(-20) scale(0.11 -0.11)">
<defs>
<path id="ArialMT-72" d="M 416 0
L 416 3319
@@ -215,7 +215,7 @@ z
<g id="xtick_2">
<g id="text_2">
<!-- llama3 -->
- <g style="fill: #262626" transform="translate(284.998692 412.460852) rotate(-20) scale(0.11 -0.11)">
+ <g style="fill: #262626" transform="translate(354.748692 412.460852) rotate(-20) scale(0.11 -0.11)">
<defs>
<path id="ArialMT-6c" d="M 409 0
L 409 4581
@@ -270,7 +270,7 @@ z
<g id="xtick_3">
<g id="text_3">
<!-- mistral-small -->
- <g style="fill: #262626" transform="translate(410.725147 422.487172) rotate(-20) scale(0.11 -0.11)">
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<defs>
<path id="ArialMT-69" d="M 425 3934
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@@ -368,12 +368,29 @@ z
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" style="fill: none; stroke: #cccccc; stroke-width: 1.25; stroke-linejoin: miter; stroke-linecap: square"/>
</g>
- <g id="patch_10">
+ <g id="patch_9">
<path d="M 90 51.84
L 648 51.84
" style="fill: none; stroke: #cccccc; stroke-width: 1.25; stroke-linejoin: miter; stroke-linecap: square"/>
</g>
- <g id="text_13">
+ <g id="text_11">
<!-- CCEI Distribution by Model -->
<g style="fill: #262626" transform="translate(284.972656 45.84) scale(0.14 -0.14)">
<defs>
@@ -1125,7 +975,7 @@ z
</g>
</g>
<defs>
- <clipPath id="p4d718ef8b1">
+ <clipPath id="pd32a051487">
<rect x="90" y="51.84" width="558" height="332.64"/>
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</defs>
diff --git a/src/investment/__init__.py b/src/investment/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/src/dictator/dictator_consistency.py b/src/investment/investment.py
similarity index 63%
rename from src/dictator/dictator_consistency.py
rename to src/investment/investment.py
index 04282d2..4c54be5 100644
--- a/src/dictator/dictator_consistency.py
+++ b/src/investment/investment.py
@@ -1,17 +1,13 @@
-import os
import asyncio
+import os
+import random
from typing import Dict, List
-
-from gpytorch.settings import debug
-from ollama import generate
-from pydantic import BaseModel
+import numpy as np
from autogen_agentchat.agents import AssistantAgent
from autogen_agentchat.messages import TextMessage
from autogen_core import CancellationToken
from autogen_ext.models.openai import OpenAIChatCompletionClient
-import json
-import random
-import numpy as np
+from pydantic import BaseModel
from scipy.optimize import linprog
# Load API key from environment variable
@@ -21,20 +17,20 @@ if not OPENAI_API_KEY:
# Define the expected response format as a Pydantic model
class AgentResponse(BaseModel):
- my_share: int
- other_share: int
+ assetA: int
+ assetB: int
reasoning: str
-# The dictator game simulation class
-class DictatorConsistency:
+# The investment game simulation class
+class Investment:
def __init__(self, model: str, temperature: float, max_retries: int = 3):
- self.debug = False
+ self.debug = True
self.model = model
self.temperature = temperature
self.strategy = random
self.max_retries = max_retries # Maximum retry attempts in case of hallucinations
- if not model == "random":
+ if not model == "random" and not model == "optimal":
is_openai_model = model.startswith("gpt")
base_url = "https://api.openai.com/v1" if is_openai_model else "http://localhost:11434/v1"
@@ -59,18 +55,20 @@ class DictatorConsistency:
"""Runs the model if strategy is False, otherwise uses a classical method."""
if self.model == "random":
return self.apply_random(m, n)
+ if self.model == "optimal":
+ return self.apply_optimal(m, n)
instruction = f"""
- You have 100 points to allocate between yourself and an anonymous person.
- In this round, allocating every 1 point for yourself returns {m} dollars for yourself,
- and allocating every 1 point for the other one returns {n} dollars for him/her.
+ You have 100 points to allocate between Asset A and Asset B.
+ In this round, allocating 1 point to Asset A yields {m} dollars,
+ while allocating 1 point to Asset B yields {n} dollars.
What is your allocation?
- Your response should be in JSON format with `my_share`, `other_share`, and `reasoning`.
+ Your response should be in JSON format with `assetA`, `assetB`, and `reasoning`.
"""
for attempt in range(self.max_retries):
agent = AssistantAgent(
- name="Dictator",
+ name="Investor",
model_client=self.model_client,
system_message="You are a helpful assistant. You will be given 25 rounds of decision-making tasks and will be responsible for making decisions. You should use your best judgment to come up with solutions that you like most."
)
@@ -83,29 +81,42 @@ class DictatorConsistency:
try:
response_data = response.chat_message.content
agent_response = AgentResponse.model_validate_json(response_data) # Parse JSON
- my_share, other_share = agent_response.my_share, agent_response.other_share
+ assetA, assetB = agent_response.assetA, agent_response.assetB
if self.debug:
print(f"Response (Attempt {attempt+1}): {response_data}")
# Validate values: ensure they sum to $100 considering the values M and N
- if 0 <= my_share and my_share <= 100 and 0 <= other_share and other_share <= 100 and my_share + other_share == 100:
+ if 0 <= assetA and assetA <= 100 and 0 <= assetB and assetB <= 100 and assetA + assetB == 100:
return agent_response.model_dump()
else:
- if self.debug :
+ if self.debug:
print(f"Invalid response detected (Attempt {attempt+1}): {response_data}")
except Exception as e:
print(f"Error parsing response (Attempt {attempt+1}): {e}")
raise ValueError("Model failed to provide a valid response after multiple attempts.")
- def apply_random(self, m:int, n:int) -> Dict:
+ def apply_random(self, m: int, n: int) -> Dict:
"""Generates a response."""
- my_share = random.randint(0, 100)
- other_share = 100 - my_share
+ assetA = random.randint(0, 100)
+ assetB = 100 - assetA
return {
- "my_share": my_share,
- "other_share": other_share,
+ "assetA": assetA,
+ "assetB": assetB,
"reasoning": "Random choice"
- }
+ }
+ def apply_optimal(self, m: int, n: int) -> Dict:
+ """Generates a response."""
+ if m > n:
+ assetA = 100
+ assetB = 0
+ else:
+ assetA = 0
+ assetB = 100
+ return {
+ "assetA": assetA,
+ "assetB": assetB,
+ "reasoning": "Optimal choice"
+ }
def generate_M_N(self):
while True:
@@ -114,9 +125,8 @@ class DictatorConsistency:
if max(M, N) >= 0.5: # Ensure max(M, N) is at least 0.5
return round(M, 1), round(N, 1)
-
- async def run_rounds(self, nb_rounds: int) -> List[Dict]:
- """Runs the dictator game for n rounds and returns the results."""
+ async def run_rounds(self, nb_rounds: int) -> float:
+ """Runs the investment game for n rounds and computes the CCEI."""
results = []
prices = []
choices = []
@@ -130,51 +140,58 @@ class DictatorConsistency:
print(f"result: {result}")
results.append(result)
prices.append([m, n])
- budgets.append(m * result['my_share'] + n * result['other_share'])
- choices.append([result['my_share'], result['other_share']])
- ccei_value = self.compute_ccei(prices, choices,budgets)
+ budget = round(m * result['assetA'] + n * result['assetB'], 4)
+ budgets.append(budget)
+ choices.append([result['assetA'], result['assetB']])
+
+ # Compute CCEI
+ ccei_value = self.compute_ccei(prices, choices, budgets)
if self.debug:
print(f"prices: {prices}")
print(f"choices: {choices}")
print(f"budgets: {budgets}")
print(f"CCEI: {ccei_value}")
+
return ccei_value
def compute_ccei(self, prices, choices, budgets):
"""
Computes the Critical Cost Efficiency Index (CCEI).
- :param prices: List of price vectors (list of lists)
- :param choices: List of chosen consumption bundles (list of lists)
- :param budgets: List of budget values (list)
- :return: CCEI value (between 0 and 1)
"""
n = len(prices) # Number of observations
- # Objective: maximize lambda (equivalent to minimizing -lambda)
- c = [-1] # We minimize -lambda to maximize lambda
+ c = [1] # Minimize theta
A_ub = [] # Constraint matrix
b_ub = [] # Right-hand side values
for t in range(n):
for s in range(n):
lhs = np.dot(prices[t], choices[s]) # p_t * x_s
- rhs = budgets[t] # I_t
- # Corrected constraint: p_t * x_s - lambda * I_t <= 0
- A_ub.append([rhs]) # Correctly include I_t as coefficient of lambda
- b_ub.append(lhs) # p_t * x_s moved to RHS
- # Bounds for lambda: between 0 and 1
- bounds = [(0, 1)]
+ rhs = np.dot(prices[t], choices[t]) # p_t * x_t
+ if lhs > rhs: # Only add constraints where direct revealed preference exists
+ A_ub.append([-budgets[t]]) # -theta * I_t
+ b_ub.append(lhs - rhs)
+ # Ensure A_ub is a valid 2D array
+ if A_ub:
+ A_ub = np.array(A_ub, dtype=float)
+ if A_ub.ndim == 1: # Ensure it's 2D
+ A_ub = A_ub.reshape(-1, 1)
+ else:
+ A_ub = np.zeros((1, 1), dtype=float) # If no constraints, use a trivial 1x1 matrix
+ # Ensure b_ub is also valid
+ b_ub = np.array(b_ub, dtype=float) if b_ub else np.zeros(1, dtype=float)
+
+ bounds = [(0, 1)] # Theta bounds
# Solve the linear program
result = linprog(c, A_ub=A_ub, b_ub=b_ub, bounds=bounds, method="highs")
if result.success:
- return round(-result.fun, 4) # Extract the optimized lambda
+ return round(result.x[0], 4) # Return optimized theta value
else:
- if self.debug:
- print("CCEI computation failed. Check constraints.")
- return 0 # Return 0 instead of None to indicate irrationality
+ print("CCEI computation failed. Check constraints.")
+ return 0 # Return 0 if LP fails
# Run the async function and return the response
if __name__ == "__main__":
- game_agent = DictatorConsistency(model="mistral-small", temperature=0.7) # Toggle strategy here
- response = asyncio.run(game_agent.run_rounds(25))
+ game_agent = Investment(model="mistral-small", temperature=0.0) # Toggle strategy here
+ response = asyncio.run(game_agent.run_rounds(10))
print(response)
diff --git a/src/dictator/draw_consistency_draw.py b/src/investment/investment_draw.py
similarity index 88%
rename from src/dictator/draw_consistency_draw.py
rename to src/investment/investment_draw.py
index 849e73d..d2e47da 100644
--- a/src/dictator/draw_consistency_draw.py
+++ b/src/investment/investment_draw.py
@@ -12,7 +12,7 @@ color_palette = {
}
# Load CSV file
-file_path = "../../data/dictator/dictator_consistency.csv" # Update path
+file_path = "../../data/investment/investment.csv" # Update path
df = pd.read_csv(file_path)
# Clean column names
@@ -40,5 +40,5 @@ plt.ylabel("CCEI Value", fontsize=12)
plt.xticks(rotation=20)
# Save the figure
-output_path = "../../figures/dictator/dictator_consistency.svg"
+output_path = ("../../figures/investment/investment.svg")
plt.savefig(output_path, format="svg")
diff --git a/src/dictator/dictator_consistency_experiments.py b/src/investment/investment_experiments.py
similarity index 68%
rename from src/dictator/dictator_consistency_experiments.py
rename to src/investment/investment_experiments.py
index ac425e7..ed828f0 100644
--- a/src/dictator/dictator_consistency_experiments.py
+++ b/src/investment/investment_experiments.py
@@ -1,15 +1,12 @@
-import os
import asyncio
import csv
-from typing import List
-import random
-from dictator_consistency import DictatorConsistency # Assuming this is in a separate file
+from investment import Investment # Assuming this is in a separate file
# Define models, temperature, and iterations
-models = ["random", "llama3", "mistral-small", "deepseek-r1"] # "gpt-4.5-preview-2025-02-27"
+models = ["optimal", "random"] # "gpt-4.5-preview-2025-02-27" "random", "llama3", "mistral-small", "deepseek-r1"
temperature = 0.0
-iterations = 30
-output_file = "../../data/dictator/dictator_consistency.csv"
+iterations = 10
+output_file = "../../data/investment/investment.csv"
async def run_experiment():
# Open CSV file to store results
@@ -24,8 +21,8 @@ async def run_experiment():
print(f"Iteration {iteration}/{iterations} for {model}")
# Run DictatorConsistency experiment
- game_agent = DictatorConsistency(model=model, temperature=temperature)
- ccei_value = await game_agent.run_rounds(25) # Run 25 rounds
+ game_agent = Investment(model=model, temperature=temperature)
+ ccei_value = await game_agent.run_rounds(10) # Run 25 rounds
# Write results to CSV
writer.writerow([iteration, model, temperature, ccei_value])
--
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