研究著作內容
An Analytical Study of Puzzle Selection Strategies for the ESP Game
(NOTE: Sheng-Wei Chen is also known as Kuan-Ta Chen.)

Abstract
Human Computation represents a new paradigm of applications that take advantage of people’s desire to be entertained and produce useful metadata as a by-product. By creating games with a purpose, human computation has shown promise in solving a variety of problems that computer computation cannot currently resolve completely. Using the ESP game as an example, we propose a metric, called system gain, for evaluating the performance of human computation systems, and also use analysis to study the properties of the ESP game. We argue that human computation systems should be played with a strategy. To this end, we implement an Optimal Puzzle Selection Strategy (OPSA) based on our analysis to improve human computation. Using a comprehensive set of simulations, we demonstrate that the proposed OPSA approach can effectively improve the system gain of the ESP game, as long as the number of puzzles in the system is sufficiently large.

Related paper:
- An Analytical Approach to Optimizing The Utility of ESP Games


Materials
Citation
Ling-Jyh Chen, Bo-Chun Wang, Kuan-Ta Chen, Irwin King, and Jimmy Ho-Man Lee, "An Analytical Study of Puzzle Selection Strategies for the ESP Game," In IEEE/WIC/ACM Web Intelligence 2008, 2008.

BibTex
@INPROCEEDINGS{chen08:espgame,
  TITLE      = {An Analytical Study of Puzzle Selection Strategies for the {ESP} Game},
  AUTHOR     = {Ling-Jyh Chen and Bo-Chun Wang and Kuan-Ta Chen and Irwin King and Jimmy Ho-Man Lee},
  BOOKTITLE  = {IEEE/WIC/ACM Web Intelligence 2008},
  YEAR       = {2008}
}