def replan(self, temporary_task_):
new_run = improve_plan_given_history(self.product, self.trace,
self.run, self.index)
if new_run:
self.run = new_run
self.index = 0
self.segment = 'line'
self.trace = []
self.run_history = []
if (len(temporary_task_.combinations)) > 0:
current_state = list(
initial_state_given_history(self.product, self.run_history,
self.run, self.index))
current_state = current_state[0]
run_temp = temporary_task_.find_temporary_run(
current_state, self.product)
end_temporary = set()
end_temporary.add(run_temp.prefix[-1])
new_run, time = dijkstra_plan_optimal(self.product, 10,
end_temporary)
prefix = run_temp.prefix[0:-1] + new_run.prefix
precost = run_temp.precost + new_run.precost
suffix = run_temp.suffix + new_run.suffix
sufcost = new_run.sufcost
totalcost = precost + self.beta * sufcost
self.run = ProdAut_Run(self.product, prefix, precost, suffix,
sufcost, totalcost)
def replan(self): new_run = improve_plan_given_history(self.product, self.trace) if (new_run) and (new_run.pre_plan !=self.run.pre_plan[self.index:-1]): self.run = new_run self.index = 1 self.segment = 'line' self.next_move = self.run.pre_plan[self.index] print 'Plan adapted!'
def replan(self): new_run = improve_plan_given_history(self.product, self.trace) if (new_run) and (new_run.pre_plan !=self.run.pre_plan[self.index:-1]): self.run = new_run self.index = 1 self.segment = 'line' self.next_move = self.run.pre_plan[self.index] print 'Plan adapted!'
def replan(self):
self.run = improve_plan_given_history(self.product, self.trace)
self.index = 0
self.segment = 'line'
self.next_move = self.run.pre_plan[self.index]