def start_auction(self):
allocations = self.solver.solve()
optimal_with_agent = self.calculate_social_welfare(allocations)
for agent in self.agents:
other_agents = [a for a in self.agents if a != agent]
solver = BendersSolver(self.supply, other_agents,
LaviSwamyGreedyApproximator(
self.supply,
other_agents,
BlackHoleLogger()),
BlackHoleLogger())
allocations_without_agent = solver.solve()
optimal_without_agent = -solver.z.x # = self.calculate_social_welfare(allocations_without_agent)
other_agents_valuations = sum([allocation.get_expected_social_welfare_without_agent(agent.id)
for allocation in allocations.itervalues()])
vcg_payoff = optimal_with_agent - optimal_without_agent
vcg_price = optimal_without_agent - other_agents_valuations
self.expected_price[agent.id] = vcg_price
print 'Marginal Economy - Sum V-1 = %s - %s = %s' % (
optimal_without_agent, other_agents_valuations, self.expected_price[agent.id])
for price in self.expected_price.iteritems():
self.log.log('Agent %s has expected VCG price %s' % (price[0], price[1]))
def __init__(self, supply, agents, log=ConsoleLogger()):
"""
:param supply: Number of copies of identical item.
:param agents: List of agents to participate. Need to implement query_demand(.) and query_value(.).
"""
self.supply = supply
self.agents = agents
self.solver = BendersSolver(self.supply,
self.agents,
LaviSwamyGreedyApproximator(self.supply, self.agents, log),
log)
self.expected_price = dict()
self.log = log
class Auction:
def __init__(self, supply, agents, log=ConsoleLogger()):
"""
:param supply: Number of copies of identical item.
:param agents: List of agents to participate. Need to implement query_demand(.) and query_value(.).
"""
self.supply = supply
self.agents = agents
self.solver = BendersSolver(self.supply,
self.agents,
LaviSwamyGreedyApproximator(self.supply, self.agents, log),
log)
self.expected_price = dict()
self.log = log
def start_auction(self):
allocations = self.solver.solve()
optimal_with_agent = self.calculate_social_welfare(allocations)
for agent in self.agents:
other_agents = [a for a in self.agents if a != agent]
solver = BendersSolver(self.supply, other_agents,
LaviSwamyGreedyApproximator(
self.supply,
other_agents,
BlackHoleLogger()),
BlackHoleLogger())
allocations_without_agent = solver.solve()
optimal_without_agent = -solver.z.x # = self.calculate_social_welfare(allocations_without_agent)
other_agents_valuations = sum([allocation.get_expected_social_welfare_without_agent(agent.id)
for allocation in allocations.itervalues()])
vcg_payoff = optimal_with_agent - optimal_without_agent
vcg_price = optimal_without_agent - other_agents_valuations
self.expected_price[agent.id] = vcg_price
print 'Marginal Economy - Sum V-1 = %s - %s = %s' % (
optimal_without_agent, other_agents_valuations, self.expected_price[agent.id])
for price in self.expected_price.iteritems():
self.log.log('Agent %s has expected VCG price %s' % (price[0], price[1]))
def calculate_social_welfare(self, allocations):
return sum([allocation.expected_social_welfare for allocation in allocations.itervalues()])
