Neural Networks
Artificial evolution for computer graphics
Proceedings of the 18th annual conference on Computer graphics and interactive techniques
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Evolutionary Art and Computers
Evolutionary Art and Computers
A Survey of Optimization by Building and Using Probabilistic Models
Computational Optimization and Applications
From Recombination of Genes to the Estimation of Distributions I. Binary Parameters
PPSN IV Proceedings of the 4th International Conference on Parallel Problem Solving from Nature
An analysis of the behavior of a class of genetic adaptive systems.
An analysis of the behavior of a class of genetic adaptive systems.
A comprehensive survey of fitness approximation in evolutionary computation
Soft Computing - A Fusion of Foundations, Methodologies and Applications
A general regression neural network
IEEE Transactions on Neural Networks
A Neural-Network-Based Geographic Tendency Visualization
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
An interactive co-evolutionary CAD system for garment pattern design
Computer-Aided Design
ConBreO: a music performance rendering system using hybrid approach of IEC and automated evolution
Proceedings of the 12th annual conference on Genetic and evolutionary computation
A practical generative design method
Computer-Aided Design
Computer-aided appearance design based on BRDF measurements
Computer-Aided Design
Graph grammars as a representation for interactive evolutionary 3d design
EvoMUSART'12 Proceedings of the First international conference on Evolutionary and Biologically Inspired Music, Sound, Art and Design
A Computational Model of Collaborative Creativity: A Meta-Design Approach
International Journal of Knowledge and Systems Science
Graph grammars for evolutionary 3D design
Genetic Programming and Evolvable Machines
An IGA-based design support system for realistic and practical fashion designs
Computer-Aided Design
Hi-index | 0.00 |
Interactive Evolutionary Systems (IES) are capable of generating and evolving large numbers of alternative designs. When using such systems, users are continuously required to interact with the system by making evaluations and selections of the designs that are being generated and evolved. The evolutionary process is therefore led by the visual aesthetic intentions of the user. However, due to the limited size of the computer screen and fuzzy nature of aesthetic evaluations, evolution is usually a mutation-driven and divergent process. The convergent mechanisms typically found in standard Evolutionary Algorithms are more difficult to achieve with IES. To address this problem, this paper presents a computational framework that creates an IES with a higher level of convergence without requiring additional actions from the user. This can be achieved by incorporating a Neural Network based learning mechanism, called a General Regression Neural Network (GRNN), into an IES. GRNN analyses the user's aesthetic evaluations during the interactive evolutionary process and is thereby able to approximate their implicit aesthetic intentions. The approximation is a regression of aesthetic appeals conditioned on the corresponding designs. This learning mechanism allows the framework to infer which designs the users may find desirable. For the users, this reduces the tedious work of evaluating and selecting designs. Experiments have been conducted using the framework to support the process of parametric tuning of facial characters. In this paper we analyze the performance of our approach and discuss the issues that we believe are essential for improving the usability and efficiency of IES.