chain of thought condition implemented for dictator game

llm_cooperation/experiments/__init__.py

@@ -242,3 +242,18 @@ def get_participants(
 
 
 SEED_VALUE = 101  # Ensure same participants are used across all experiments
+
+
+def round_instructions(participant: Participant, choice_template: str) -> str:
+    if participant[CONDITION_CHAIN_OF_THOUGHT]:
+        return f"""
+For each round, give your answer in the format below on two separate lines:
+Explanation: [why I made my choice]
+{choice_template}"""
+    else:
+        return f"""
+For each round, state your choice without explanation in the format below:
+{choice_template}"""
+
+
+CONDITION_CHAIN_OF_THOUGHT = "chain_of_thought"

llm_cooperation/experiments/dictator.py

@@ -32,6 +32,7 @@
 from llm_cooperation import Grid, ModelSetup, Participant, amount_as_str
 from llm_cooperation.experiments import (
     CONDITION_CASE,
+    CONDITION_CHAIN_OF_THOUGHT,
     CONDITION_PRONOUN,
     Case,
     Pronoun,
@@ -40,6 +41,7 @@
     get_participants,
     get_pronoun_phrasing,
     get_role_prompt,
+    round_instructions,
     run_and_record_experiment,
 )
 from llm_cooperation.gametypes.oneshot import OneShotResults, run_experiment
@@ -107,7 +109,7 @@ def payoff_allo(self) -> float:
 
 
 DICTATOR_ATTRIBUTES: Grid = {
-    # CONDITION_CHAIN_OF_THOUGHT: [True, False],
+    CONDITION_CHAIN_OF_THOUGHT: [True, False],
     # CONDITION_LABEL: all_values(Label),
     CONDITION_CASE: all_values(Case),
     CONDITION_PRONOUN: all_values(Pronoun),
@@ -143,6 +145,7 @@ def get_prompt_dictator(participant: Participant) -> str:
 def get_prompt_base(participant: Participant) -> str:
     role_prompt = get_role_prompt(participant)
     pronoun_phrase = get_pronoun_phrasing(participant)
+    choice_template = f"Choice: [{choice_menu()}]"
     return f"""
 {role_prompt}
 This is a study of investment choices in different situations.
@@ -161,11 +164,8 @@ def get_prompt_base(participant: Participant) -> str:
 but you are not allowed to communicate with your partner apart from informing
 them of your choice. Your decision will be
 final and cannot be changed after you have made it. Here is your investment
-partner. Take care to specify your choice on a separate line after
-your explanation, in the format below.
-
-Explanation: [why you picked your choice]
-Choice: [{choice_menu()}]
+partner.
+{round_instructions(participant, choice_template)}
 """
 
 

llm_cooperation/experiments/dilemma.py

@@ -34,6 +34,7 @@
 from llm_cooperation import Grid, ModelSetup, Participant, Payoffs
 from llm_cooperation.experiments import (
     CONDITION_CASE,
+    CONDITION_CHAIN_OF_THOUGHT,
     CONDITION_PRONOUN,
     Case,
     Pronoun,
@@ -42,6 +43,7 @@
     get_participants,
     get_pronoun_phrasing,
     get_role_prompt,
+    round_instructions,
     run_and_record_experiment,
 )
 from llm_cooperation.gametypes import simultaneous
@@ -68,7 +70,6 @@
 
 CONDITION_LABEL = "label"
 CONDITION_LABELS_REVERSED = "labels_reversed"
-CONDITION_CHAIN_OF_THOUGHT = "chain_of_thought"
 CONDITION_DEFECT_FIRST = "defect_first"
 CONDITION_ROLE = "role"
 CONDITION_GROUP = "group"
@@ -162,17 +163,6 @@ def get_prompt_base(participant: Participant) -> str:
     def payout(amount: int) -> str:
         return f"${amount}.00"
 
-    def round_instructions() -> str:
-        if participant[CONDITION_CHAIN_OF_THOUGHT]:
-            return f"""
-For each round, give your answer in the format below on two separate lines:
-Explanation: [why I made my choice]
-{choice_template}"""
-        else:
-            return f"""
-    For each round, state your choice without explanation in the format below:
-    {choice_template}"""
-
     return f"""{role_prompt}
 This is a study of investment choices in different situations.
 You will be making your choices with an investment partner
@@ -192,7 +182,7 @@ def round_instructions() -> str:
 You will make decisions that are consistent with the role outlined earlier,
 but you are not allowed to communicate with your partner apart from informing
 of them of your choice.
-{round_instructions()}
+{round_instructions(participant, choice_template)}
 Here is your investment partner. What is your choice in the first round?
 """
 

tests/conftest.py

@@ -29,14 +29,14 @@
 from llm_cooperation import ConfigValue, Group, Participant
 from llm_cooperation.experiments import (
     CONDITION_CASE,
+    CONDITION_CHAIN_OF_THOUGHT,
     CONDITION_GROUP,
     CONDITION_PROMPT_INDEX,
     CONDITION_PRONOUN,
     Case,
     Pronoun,
 )
 from llm_cooperation.experiments.dilemma import (
-    CONDITION_CHAIN_OF_THOUGHT,
     CONDITION_DEFECT_FIRST,
     CONDITION_LABEL,
     CONDITION_LABELS_REVERSED,

tests/test_dictator.py

@@ -29,6 +29,7 @@
 from llm_cooperation.experiments import (
     AI_PARTICIPANTS,
     CONDITION_CASE,
+    CONDITION_CHAIN_OF_THOUGHT,
     CONDITION_PRONOUN,
     Case,
 )
@@ -134,6 +135,7 @@ def test_compute_freq_dictator(test_choice: DictatorChoice):
         lazy_fixture("base_condition"),
         lazy_fixture("with_gender_neutral_pronoun"),
         lazy_fixture("with_upper_case"),
+        lazy_fixture("with_chain_of_thought"),
     ],
 )
 def test_get_prompt_dictator(condition: Participant):
@@ -142,6 +144,7 @@ def test_get_prompt_dictator(condition: Participant):
     def contains(text: ConfigValue) -> bool:
         return str(text).lower() in prompt.lower()
 
+    assert contains("explanation:") == condition[CONDITION_CHAIN_OF_THOUGHT]
     assert contains(condition[CONDITION_PRONOUN])
     assert contains(AI_PARTICIPANTS[Group.Control][0])
     for choice in all_dictator_choices:

tests/test_dilemma.py

@@ -32,11 +32,11 @@
 from llm_cooperation import DEFAULT_MODEL_SETUP, Group, Participant, Payoffs, exhaustive
 from llm_cooperation.experiments import (
     AI_PARTICIPANTS,
+    CONDITION_CHAIN_OF_THOUGHT,
     CONDITION_PRONOUN,
     GROUP_PROMPT_CONDITIONS,
 )
 from llm_cooperation.experiments.dilemma import (
-    CONDITION_CHAIN_OF_THOUGHT,
     CONDITION_LABELS_REVERSED,
     PD_ATTRIBUTES,
     Cooperate,