def predict_outcome(self, task_state, params):
outcomes = []
success_prob = self.predict_success(task_state, params)
# success
outcome = Outcome()
outcome.success = 1
outcome.probability = success_prob
# cost
outcome.cost = self.predict_cost(task_state, params)
outcome.task_state_update = CTaskStateUpdate(
task_state,
True, # is_pos_update
task_state.get_subpath_xy()[-1],
task_state.get_subpath_ij()[-1],
"NUDGE",
"S",
)
outcomes.append(outcome)
# failure
outcome = Outcome()
outcome.success = 0
outcome.probability = 1 - success_prob
# cost
outcome.cost = self.predict_cost(task_state, params)
outcome.task_state_update = CTaskStateUpdate(
task_state,
False, # is_pos_update
None,
None,
"NUDGE",
"F",
)
outcomes.append(outcome)
return outcomes
def predict_outcome(self, task_state, params):
""" if crawling failed, the likelihood of a non-permissive agent is high """
outcomes = []
success_prob = self.predict_success(task_state, params)
# success
outcome = Outcome()
outcome.success = 1
outcome.probability = success_prob
# cost
outcome.cost = self.predict_cost(task_state, params)
outcome.task_state_update = CTaskStateUpdate(
task_state,
True, # is_pos_update
task_state.get_subpath_xy()[-1],
task_state.get_subpath_ij()[-1],
"CRAWL",
"S",
)
outcomes.append(outcome)
# failure
outcome = Outcome()
outcome.success = 0
outcome.probability = 1 - success_prob
# cost
outcome.cost = self.predict_cost(task_state, params)
outcome.task_state_update = CTaskStateUpdate(
task_state,
False, # is_pos_update
None,
None,
"CRAWL",
"F",
)
outcomes.append(outcome)
return outcomes