Analysis of direct manipulation in interactive evolutionary computation on fitness landscape
Jong-Ha Lee, Sung-Bae Cho
Abstract
Jong-Ha Lee, Sung-Bae Cho
Abstract
Interactive evolutionary computation (IEC), which takes a user's evaluation as a fitness function, performs poorly for local search due to the limitation of population size and generation length. To solve this, the direct manipulation (DM) method, well known in HCI, of evolution for IEC has been proposed. It allows the user to manipulate individuals directly, instead of using evolutionary operators as an interface to each individual. In this paper, we analyze the usefulness of DM with a fitness landscape and N-K model. We have applied the DM concept to a fashion design system based on IEC, and analyzed the results with the concept of fitness landscape and Boolean hypercube.
OpenAlex reports 10 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
Interactive evolutionary computation (IEC), which takes a user's evaluation as a fitness function, performs poorly for local search due to the limitation of population size and generation length. To solve this, the direct manipulation (DM) method, well known in HCI, of evolution for IEC has been proposed. It allows the user to manipulate individuals directly, instead of using evolutionary operators as an interface to each individual. In this paper, we analyze the usefulness of DM with a fitness landscape and N-K model. We have applied the DM concept to a fashion design system based on IEC, and analyzed the results with the concept of fitness landscape and Boolean hypercube.
Key concepts: Fitness landscape, Fitness function, Interactive evolutionary computation, Fitness approximation, Evolutionary computation, Computer science, Hypercube, Population