Al Wong's Profile

Interactive evolutionary computation, an interesting technique first
developed in the early 1990s and more recently known as human
computation, (7) also puts the human at the center, but in a different
way. In traditional computation, a human provides a formalized problem
description to a computer and receives a solution to interpret. In human
computation, the roles are reversed: The computer asks a person or a large
number of people to solve a problem, then collects, interprets, and integrates
their solutions. In other words, the computer "asks" the human to do
the work it cannot do. This is done as a way to overcome technical
difficulties: Instead of trying to get computers to solve problems that are too
complex, use human beings.

In human computation, the human is helping the computer solve difficult
problems, but in HCC, the computer helps humans maximize their abilities
regardless of the situation—the human need not be in front of a computer
performing a computing task when dealing with the computer.

Although HCC and human-based computation approach computing from two
different perspectives, they both try to maximize the synergy between human
abilities and computing resources. Work in human computation can therefore be
of significant importance to HCC. On one hand, data collected through human
computation systems can be valuable for developing machine-learning models. On
the other hand, it can help us better understand human behavior and abilities,
again of direct use in HCC algorithm development and system design.

• Kosorukoff, A. (2001), & Goldberg, D. E. Genetic algorithms for social innovation and creativity (Illigal report No 2001005). Urbana, IL: University of Illinois at Urbana-Champaign (PDF)
  
  
• Kosorukoff, A. (2001) Human based genetic algorithm. (Illigal report No 2001004). Urbana, IL: University of Illinois at Urbana-Champaign (PDF)