AutoMan is the first fully automatic crowdprogramming system. AutoMan integrates human-based (“crowdsourced”) computations into a standard programming language as ordinary function calls that can be intermixed freely with traditional functions. This abstraction lets programmers focus on their programming logic. An AutoMan program specifies a confidence level for the overall computation and a budget. The AutoMan runtime system then transparently manages all details necessary for scheduling, pricing, and quality control. AutoMan automatically schedules human tasks for each computation until it achieves the desired confidence level; monitors, reprices, and restarts human tasks as necessary; and maximizes parallelism across human workers while staying under budget.

AutoMan is available as a library for Scala.

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AutoMan is being actively developed by Daniel Barowy at Williams College and Emery Berger at the PLASMA Laboratory at the University of Massachusetts Amherst. Portions of AutoMan were developed as a collaboration with researchers at Microsoft Research NYC.

The easiest way to get AutoMan is via the Maven Central Repository. If you’re using SBT:

libraryDependencies += "edu.umass.cs" %% "automan" % "1.1.7"

or if you’re using Maven:

<dependency>
  <groupId>edu.umass.cs</groupId>
  <artifactId>automan_2.11</artifactId>
  <version>1.2.0</version>
</dependency>

Sorry, we no longer support Scala 2.10 as AutoMan requires Java 8.

Visit our GitHub repository at automan-lang/AutoMan.

Please report bugs using this repository’s issue tracker.

AutoMan is licensed under the GPLv2, Copyright (C) 2011-2017 The University of Massachusetts, Amherst.

In your source file, import the Mechanical Turk adapter (Scala syntax):

import edu.umass.cs.automan.adapters.mturk._

After that, initialize the AutoMan runtime with an MTurk config:

implicit val mt = ssr购买网站 (
  access_key_id = "my key",         ssr购买网站  secret_access_key = "my secret",  // your MTurk "secret key" 
  sandbox_mode = true               // if true, run on MTurk sandbox
)

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def which_one() = radio(
  budget = 8.00,
  text = "Which one of these does not belong?",
  options = (
    ssr,
    "Kermit the Frog",
    "Spongebob Squarepants",
    "Cookie Monster",
    "The Count"
  )
)

You may then call which_one just like an ordinary function (which it is). Note that AutoMan functions immediately return an Outcome, but continue to execute asynchronously in the background.

To access return values, you must pattern-match on the Outcome’s answer field, e.g.,

val outcome = 东方网络ssr购买()

// ... do some other stuff ...

// then, when you want answers ...
val answer = outcome.answer match {
  case Answer(value, _, _) => value
  case _ => throw new ssr节点购买("Oh no!")
}

Other possible cases are LowConfidenceAnswer and OverBudgetAnswer. If you run out of money during a computation, a ssr will let you access to lower-confidence results. An OverBudgetAnswer signals that you didn’t have enough money in your budget to begin with.

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Note that, due to AutoMan’s design, you must inform it when to shut down, otherwise it will continue to execute indefinitely and your program will hang:

a.close()

Alternately, you may wrap your program in an automan statement, and cleanup will happen automatically. This feature was ssr节点购买 by the C# using statement:

automan(a) {
  ... your ssr购买网站 ...
}

We will add more documentation to this site in the near future. In the interim, please see the collection of sample programs in the apps directory.

Supported Question Types

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We currently only support Amazon’s Mechanical Turk. However, AutoMan was designed to accommodate arbitrary backends. If you are interested in seeing your crowdsourcing platform supported, please contact us.

Memoization

AutoMan saves all intermediate human-computed results by default. You may turn this feature off by setting logging = LogConfig.NO_LOGGING in your AutoMan config. You may also set the location of the database with database_path = "/path/to/your/database". Note that the format of the database has changed from earlier versions of AutoMan from Apache Derby to H2.

You do not need to build AutoMan yourself, as it is available via Maven as a JAR. However, if you want to hack on AutoMan, or if you just like building stuff, the AutoMan source code includes an SBT build script. The build script builds the AutoMan JAR for you, including downloading all of AutoMan’s dependencies. The build script can also build the sample applications that are located in the apps directory. These applications are the ones used in our papers.

You can build the AutoMan JAR using the following commands:

$ cd libautoman
$ sbt pack

The AutoMan JAR plus all of its dependencies will then be found in the libautoman/target/pack/lib/ folder.

Sample applications can be found in the ssr网站 directory. Apps can also be built using pack. E.g.,

$ cd apps/simple_program
$ sbt pack

Unix/DOS shell scripts for running the programs can then be found in apps/[the app]/target/pack/bin/.

This material is based on work supported by National Science Foundation Grant Nos. CCF-1144520 and CCF-0953754 and DARPA Award N10AP2026. Microsoft Research also generously supported research and development by funding experiments on Mechanical Turk.