# sellers = removeSeconds(sellers, reduce_number)
# mediators = removeSeconds(mediators, reduce_number)
# mediatorsB = removeSeconds(mediatorsB, reduce_number)
#
# random.shuffle(buyers)
# random.shuffle(sellers)
# random.shuffle(mediators)
# random.shuffle(mediatorsB)
market = Market([
AgentCategory("buyer", buyers),
AgentCategory("seller", sellers),
AgentCategory("mediator", mediators),
AgentCategory("mediatorB", mediatorsB),
])
without_gft0 = budget_balanced_trade_reduction(market, recipe, False)
with_gft0 = budget_balanced_trade_reduction(market, recipe, True)
print(without_gft0)
print(with_gft0)
without_count = without_gft0.num_of_deals()
with_count = with_gft0.num_of_deals()
without_gft = without_gft0.gain_from_trade()
with_gft = with_gft0.gain_from_trade()
print('Compare: Without:', without_gft, "With:", with_gft)
print('Compare: Without:', without_count, "With:", with_count)
break
# print(" buyers =", buyers)
# print(" sellers =", sellers)
# print(" mediators =", mediators)
def experiment(results_csv_file: str, recipes: tuple, value_ranges: list,
nums_of_agents: list, num_of_iterations: int):
"""
Run an experiment similar to McAfee (1992) experiment on the given auction.
:param recipes: list of recipes.
:param nums_of_agents: a list of the numbers of agents with which to run the experiment.
:param value_ranges: for each category, a pair (min_value,max_value). The value for each agent in this category is selected uniformly at random between min_value and max_value.
:param num_of_iterations: how many times to repeat the experiment for each num of agents.
"""
results_table = TeeTable(TABLE_COLUMNS, results_csv_file)
for recipe in recipes:
recipe_str = ":".join(map(str, recipe))
num_of_categories = len(recipe)
external_wins_gft = tie_gft = ascending_wins_gft = 0
external_wins_k = tie_k = ascending_wins_k = 0
for num_of_agents_per_category in nums_of_agents:
external_sum_auction_count = ascending_sum_auction_count = 0 # count the number of deals done the ascending auction.
external_sum_auction_gft = ascending_sum_auction_gft = 0
agents_recipe_values = [sum(recipe) - recipe[0]] + [
recipe[0] for _ in range(1, len(recipe))
]
for _ in range(num_of_iterations):
market = Market([
AgentCategory.uniformly_random(
"agent", num_of_agents_per_category * recipe[category],
value_ranges[category][0] *
agents_recipe_values[category],
value_ranges[category][1] *
agents_recipe_values[category])
for category in range(num_of_categories)
])
(optimal_trade, _) = market.optimal_trade(recipe)
external_auction_trade = budget_balanced_trade_reduction(
market, recipe)
ascending_auction_trade = budget_balanced_ascending_auction(
market, recipe)
external_sum_auction_count += external_auction_trade.num_of_deals(
)
ascending_sum_auction_count += ascending_auction_trade.num_of_deals(
)
external_sum_auction_gft += external_auction_trade.gain_from_trade(
)
ascending_sum_auction_gft += ascending_auction_trade.gain_from_trade(
)
if external_sum_auction_count > ascending_sum_auction_count:
external_wins_k += 1
elif external_sum_auction_count == ascending_sum_auction_count:
tie_k += 1
else:
ascending_wins_k += 1
if external_sum_auction_gft > ascending_sum_auction_gft:
external_wins_gft += 1
elif external_sum_auction_gft == ascending_sum_auction_gft:
tie_gft += 1
else:
ascending_wins_gft += 1
num_agents = len(nums_of_agents)
results_table.add(
OrderedDict((
("recipe", recipe),
("external_wins_gft",
int(external_wins_gft * 100 / num_agents)),
("tie_gft", int(tie_gft * 100 / num_agents)),
("ascending_wins_gft",
int(ascending_wins_gft * 100 / num_agents)),
("external_wins_k", int(external_wins_k * 100 / num_agents)),
("tie_k", int(tie_k * 100 / num_agents)),
("ascending_wins_k", int(ascending_wins_k * 100 / num_agents)),
("external_wins", external_wins_gft),
("tie", tie_gft),
("ascending_wins", ascending_wins_gft),
)))
results_table.done()
print(
"\n\n###### RUNNING EXAMPLE FROM THE PAPER FOR TYPE (1,1,1): buyers-sellers-mediators"
)
buyers = [17, 14, 13, 9, 6]
sellers = [-1, -4, -5, -8, -11]
mediators = [-1, -3, -4, -7, -10]
recipe = [1, 1, 1]
market = Market([
AgentCategory("buyer", buyers),
AgentCategory("seller", sellers),
AgentCategory("mediator", mediators),
])
print(budget_balanced_trade_reduction(market, recipe))
print("\n\n###### SAME EXAMPLE WITH DIFFERENT ORDER: buyers-mediators-sellers")
market = Market([
AgentCategory("buyer", buyers),
AgentCategory("mediator", mediators),
AgentCategory("seller", sellers),
])
print(budget_balanced_trade_reduction(market, recipe))
print("\n\n###### SAME EXAMPLE WITH DIFFERENT ORDER: sellers-buyers-mediators")
market = Market([
AgentCategory("seller", sellers),
AgentCategory("buyer", buyers),
AgentCategory("mediator", mediators),
])
print("\n\n###### RUNNING mcafee_trade_reduction")
market = Market([
AgentCategory("buyer", [1, 1, 1]),
AgentCategory("seller", [-1, -1, -0.5]),
])
print(mcafee_trade_reduction(market, [1, 1]))
print("\n\n###### RUNNING budget_balanced_trade_reduction")
market = Market([
AgentCategory("buyer", [1, 1, 1]),
AgentCategory("seller", [-1, -1, -0.5]),
])
print(budget_balanced_trade_reduction(market, [1, 1], True))
print("\n\n###### RUNNING EXPERIMENT FOR DEMO OF TYPE (1,1)")
ascending_auction_protocol.logger.setLevel(logging.ERROR)
prices.logger.setLevel(logging.ERROR)
results_file = "results/ascending_auction_demo_11.csv"
SBB_ASCENDING_STOCKS = "SBB Ascending Prices"
experiment(results_file,
mcafee_trade_reduction,
"McAfee Stock", (1, 1),
value_ranges=[(1, 2), (-1, -2)],
nums_of_agents=(50, 50),
num_of_iterations=1)