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Human-based computation game


A human-based computation game or game with a purpose (GWAP) is a human-based computation technique of outsourcing steps within a computational process to humans in an entertaining way (gamification).

Luis von Ahn first proposed the idea of "human algorithm games", or games with a purpose (GWAPs), in order to harness human time and energy for addressing problems that computers cannot yet tackle on their own. He believes that human intellect is an important resource and contribution to the enhancement of computer processing and human computer interaction. He argues that games constitute a general mechanism for using brainpower to solve open computational problems. In this technique, human brains are compared to processors in a distributed system, each performing a small task of a massive computation. However, humans require an incentive to become part of a collective computation. Online games are used as a means to encourage participation in the process.

The tasks presented in these games are usually trivial for humans, but difficult for computers. These tasks include labeling images, transcribing ancient texts, common sense or human experience based activities, and more. Human-based computation games motivate people through entertainment rather than an interest in solving computation problems. This makes GWAPs more appealing to a larger audience. GWAPs can be used to help build the semantic web, annotate and classify collected data, crowdsource general knowledge, and improving other general computer processes. GWAPs have a vast range of applications in variety of areas such as security, computer vision, Internet accessibility, adult content filtering, and Internet search. In applications such as these, games with a purpose have lowered the cost of annotating data and increased the level of human participation.

The first human-based computation game or games with a purpose was created in 2004 by Luis von Ahn. The game was called ESP because players had to come up with labels for images and try to guess what labels a randomly designated partner was coming up with. The game marked the first of many microtask games. Microtask games are games containing a simple task that can be solved quickly without the need of any credentials. More specifically, ESP was an output-agreement game. Games with a Purpose categorized as output-agreement games are microtask games where a pair of randomly assigned partners try to match output with each other given a shared input visible to both. In 2006 von Ahn introduced another microtask game called Peekaboom. This game extended upon ESP by having players associate a labels with a specific region of an image. Peekaboom demonstrated a new type of microtask game known as inversion-problem games. In inversion-problem games, two players are randomly paired together where one is assigned as the describer and the other as the guesser. The describer is given an input which the guesser must reproduce given hints from the describer. In Peekaboom, for example, the describer slowly reveals small sections of an image until the guesser correctly guesses the label provided to the describer. In 2008 Edith L. M. Law created the game called TagATune. In this game, players label sound clips. TagATune contributed a new category of microtask games known as input-agreement games. In input-agreement games two randomly paired players are each given an input that is hidden from the other player. Player inputs will either match or be different. The goal of these games is for players to tag their input such that the other player can determine whether or not the two inputs match. In TagATune, players describe sound clips and guess if their partner's sound clip is the same as their own given their partner's tags. Also in 2008, Foldit was introduced by Seth Cooper. Foldit was the first game with a purpose to be considered a macrotask game. Macrotask games contain complex problems usually left to experts to solve. In Foldit, player attempt to fold a three-dimensional representation of a protein. While this is a hard problem of computers to automate completely, it is not hard to score. Thus players are able to focus on their score to perform this complex task without much knowledge of biology.


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