def onCycleEnd(self, agt):
if agt.name != self.root:
return
ccg = self.ccg
vertex_cover = [u for u in ccg.nodes() if self.values[u] >= 0.5]
for var in self.variables:
set_var_value(var, vertex_cover, self.var_ccg_nodes[var.name],
self.prng)
def onCycleEnd(self, agt):
if agt.name != self.root:
return
ccg = self.ccg
weights = nx.get_node_attributes(ccg, 'weight')
vertex_cover = []
for u in ccg.nodes():
sum_msgs = np.sum(self.msgs[t][u] for t in ccg.neighbors(u))
if sum_msgs[0] > sum_msgs[1] + weights[u]:
vertex_cover.append(u)
for var in self.variables:
set_var_value(var, vertex_cover, self.var_ccg_nodes[var.name], self.prng)
def onStart(self, agt):
#agt.setRandomAssignment()
self.msgs = {u: {v: self.prng.randint(10, size=2)
for v in self.ccg.neighbors(u)} for u in self.ccg.nodes()}
if agt.name is self.root:
for var in self.variables:
v_val = var.value
# Set associated node to 0 and all others to 1
vc = []
for (u, r) in self.var_ccg_nodes[var.name]:
if v_val == 0 or v_val != 0 and r != v_val:
vc.append(u)
set_var_value(var, vc, self.var_ccg_nodes[var.name], self.prng)
def onStart(self, agt):
#agt.setRandomAssignment()
ccg = self.agt_ccg[agt.name]
self.agt_ccg_nodes[agt.name] = [
u for u, data in ccg.nodes(data=True)
if 'owner' in data and data['owner'] == agt.name
]
for var in agt.variables:
v_val = var.value
vc = []
# Set associated node to 0 and all others to 1
for (u, r) in self.var_ccg_nodes[var.name]:
if v_val == 0 or v_val != 0 and r != v_val:
vc.append(u)
set_var_value(var, vc, self.var_ccg_nodes[var.name], self.prng)
def onCycleEnd(self, agt):
ccg = self.agt_ccg[agt.name]
weights = nx.get_node_attributes(ccg, 'weight')
type = nx.get_node_attributes(ccg, 'type')
vertex_cover = []
for u in ccg.nodes():
sum_msgs = np.sum(self.msgs[t][u] for t in ccg.neighbors(u))
if sum_msgs[0] > sum_msgs[1] + weights[u]:
vertex_cover.append(u)
# if weights[u] < sum_msgs:
# vertex_cover.append(u)
for var in agt.variables:
set_var_value(var, vertex_cover, self.var_ccg_nodes[var.name],
self.prng)