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edu.umass.cs.automan.core.policy.aggregation

AggregationPolicy

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abstract class AggregationPolicy extends AnyRef

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Instance Constructors

  1. new AggregationPolicy(question: Question)

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Type Members

  1. class PrematureAggregationException extends Exception

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Abstract Value Members

  1. abstract def is_done(tasks: List[Task], num_comparisons: Int): (Boolean, Int)

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    Returns true if the strategy has enough data to stop scheduling work.

    Returns true if the strategy has enough data to stop scheduling work.

    tasks

    The complete list of scheduled tasks.

    num_comparisons

    The number of times this function has been called, inclusive.

    returns

    (true iff done, new num_comparisons)

  2. abstract def num_to_run(tasks: List[Task], num_comparisons: Int, reward: BigDecimal): Int

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    protected[edu.umass.cs.automan.core.policy]
  3. abstract def rejection_response(tasks: List[Task]): String

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    Returns a string explaining why the worker's answer was not accepted.

    Returns a string explaining why the worker's answer was not accepted.

    tasks

    The list of accepted tasks. Used to determine the correct answer.

    returns

    Explanation string.

  4. abstract def select_answer(tasks: List[Task], num_comparisons: Int): AA

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    Returns the top answer.

    Returns the top answer.

    tasks

    The complete list of tasks.

    num_comparisons

    The number of times is_done has been called.

    returns

    Top answer

  5. abstract def select_over_budget_answer(tasks: List[Task], need: BigDecimal, have: BigDecimal, num_comparisons: Int): AA

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    Returns an appropriate response for when the computation ran out of money.

    Returns an appropriate response for when the computation ran out of money.

    tasks

    The complete list of tasks.

    need

    The smallest amount of money needed to complete the computation under optimistic assumptions.

    have

    The amount of money we have.

    num_comparisons

    The number of times is_done has been called.

    returns

    A low-confidence or over-budget answer.

  6. abstract def tasks_to_accept(tasks: List[Task]): List[Task]

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  7. abstract def tasks_to_reject(tasks: List[Task]): List[Task]

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Concrete Value Members

  1. final def !=(arg0: Any): Boolean

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  2. final def ##(): Int

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  3. final def ==(arg0: Any): Boolean

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  4. def allow_early_termination(): Boolean

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    Determines whether a policy allows for canceling running tasks.

    Determines whether a policy allows for canceling running tasks. If true, is_done will be called more often, increasing the required confidence level to terminate. Note that an early termination check is always conducted when timeouts occur regardless of this setting.

  5. final def asInstanceOf[T0]: T0

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  6. def blacklisted_workers(tasks: List[Task]): List[String]

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    Returns a list of blacklisted worker_ids given a set of tasks, completed or not.

    Returns a list of blacklisted worker_ids given a set of tasks, completed or not.

    tasks

    The complete list of tasks.

    returns

    A list of worker IDs.

  7. def clone(): AnyRef

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  8. def completed_tasks(tasks: List[Task]): List[Task]

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  9. def completed_workerunique_tasks(tasks: List[Task]): List[Task]

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  10. final def eq(arg0: AnyRef): Boolean

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  11. def equals(arg0: Any): Boolean

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  12. def finalize(): Unit

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    @throws( classOf[java.lang.Throwable] )
  13. final def getClass(): Class[_]

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  14. def getDistribution(tasks: List[Task]): Array[Response[A]]

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  15. def hashCode(): Int

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  16. final def isInstanceOf[T0]: Boolean

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  17. final def ne(arg0: AnyRef): Boolean

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  18. def not_final(task: Task): Boolean

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  19. final def notify(): Unit

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  20. final def notifyAll(): Unit

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  21. def outstanding_tasks(tasks: List[Task]): List[Task]

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  22. def partition_duplicates(tasks: List[Task]): (List[Task], List[Task])

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    Partitions a set of tasks into those that should be marked as duplicate and those that should not be.

    Partitions a set of tasks into those that should be marked as duplicate and those that should not be. All tasks passed in are passed back out.

    tasks

    A list of tasks

    returns

    (list of non-duplicate tasks, list of duplicate tasks)

  23. def spawn(tasks: List[Task], suffered_timeout: Boolean, num_comparisons: Int): List[Task]

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    Computes the number of tasks needed to satisfy the quality-control algorithm given the already-collected list of tasks.

    Computes the number of tasks needed to satisfy the quality-control algorithm given the already-collected list of tasks. Returns only newly-created tasks.

    tasks

    The complete list of previously-scheduled tasks

    suffered_timeout

    True if any of the latest batch of tasks suffered a timeout.

    returns

    A list of new tasks to schedule on the backend.

  24. final def synchronized[T0](arg0: ⇒ T0): T0

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  25. def tasks_to_accept_on_failure(tasks: List[Task]): List[Task]

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  26. def tasks_to_cancel(tasks: List[Task]): List[Task]

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  27. def toString(): String

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  28. def unique_by_date(ts: List[Task]): List[Task]

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  29. final def wait(): Unit

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  30. final def wait(arg0: Long, arg1: Int): Unit

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  31. final def wait(arg0: Long): Unit

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