def on_start(self):
"""
Start the algorithm and select an initial value for the variable when the
agent is started.
"""
if not self._neighbors:
# If a variable has no neighbors, we must select its final value immediately
# as it will never receive any message.
value, cost = optimal_cost_value(self._variable, self._mode)
self.value_selection(value, cost)
if self.logger.isEnabledFor(logging.INFO):
self.logger.info(
f"Select initial value {self.current_value} "
f"based on cost function for var {self._variable.name}")
self.finished()
else:
# The variable has neighbors: select a value, which might change
# once we receive messages.
if self.variable.initial_value is None:
self.value_selection(random.choice(self.variable.domain), None)
if self.logger.isEnabledFor(logging.INFO):
self.logger.info(
f"Select initial random value {self.current_value}")
else:
self.value_selection(self.variable.initial_value, None)
if self.logger.isEnabledFor(logging.INFO):
self.logger.info(
f"Select initial value {self.current_value}")
self._wait_for_values()
def on_start(self):
# Select an initial value.
if not self.neighbors:
# If a variable has no neighbors, we must select its final value immediately
# as it will never receive any message.
value, cost = optimal_cost_value(self._variable, self._mode)
self.value_selection(value, cost)
if self.logger.isEnabledFor(logging.INFO):
self.logger.info(
f"Select initial value {self.current_value} "
f"based on cost function for var {self._variable.name}")
self.finished()
else:
if self.variable.initial_value is None:
self.value_selection(random.choice(self.variable.domain),
self.current_cost)
self.logger.info(
"%s gdba starts: randomly select value %s and "
"send to neighbors",
self.variable.name,
self.current_value,
)
else:
self.value_selection(self.variable.initial_value,
self.current_cost)
self.logger.info(
"%s gdba starts: select initial value %s and send to neighbors",
self.variable.name,
self.current_value,
)
self._send_current_value()
self._go_to_wait_ok_mode()
def delayed_start(self):
self.remove_periodic_action(self._start_handle)
if self.logger.isEnabledFor(logging.DEBUG):
self.logger.debug("Remove start delayed action %s ",
self._start_handle)
self._start_handle = None
if not self.neighbors:
# If a variable has no neighbors, we must select its final value immediately.
# We also do not need to setup a periodic action.
if hasattr(self._variable, "cost_for_val"):
current_cost, value = optimal_cost_value(
self._variable, self.mode)
self.value_selection(value, current_cost)
if self.logger.isEnabledFor(logging.INFO):
self.logger.info(
f"ADSA starts: initial value {self.current_value} "
f"based on cost function for var {self._variable.name}"
)
else:
self.value_selection(random.choice(self.variable.domain), None)
if self.logger.isEnabledFor(logging.INFO):
self.logger.info(
f"ADSA starts: initial random value {self.current_value} "
f"for unconstrained variable {self._variable.name}")
self.finished()
self.stop()
else:
self._tick_handle = self.add_periodic_action(
self.period, self.tick)
self.random_value_selection()
if self.logger.isEnabledFor(logging.INFO):
self.logger.info("ADSA starts: randomly select value %s",
self.current_value)
self.post_to_all_neighbors(ADsaMessage(self.current_value))
def on_start(self):
if not self.neighbors:
# If a variable has no neighbors, we must select its final value immediately
# as it will never receive any message.
value, cost = optimal_cost_value(self._variable, self.mode)
self.value_selection(value, cost)
if self.logger.isEnabledFor(logging.INFO):
self.logger.info(
f"Select initial value {self.current_value} "
f"based on cost function for var {self._variable.name}")
self.finished()
self.stop()
else:
self.random_value_selection()
self.logger.debug("DSA starts: randomly select value %s",
self.current_value)
self.post_to_all_neighbors(DsaMessage(self.current_value))
# As everything is asynchronous, we might have received our
# neighbors values even before starting this algorithm.
self.evaluate_cycle()