An introduction to genetic algorithms
An introduction to genetic algorithms
The design and analysis of a computational model of cooperative coevolution
The design and analysis of a computational model of cooperative coevolution
A Cooperative Coevolutionary Approach to Function Optimization
PPSN III Proceedings of the International Conference on Evolutionary Computation. The Third Conference on Parallel Problem Solving from Nature: Parallel Problem Solving from Nature
Evolutionary computation in civil engineering: research frontiers
Civil and structural engineering computing: 2001
Improving problem definition through interactive evolutionary computation
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
Emergent engineering design: design creativity and optimality inspired by nature
Emergent engineering design: design creativity and optimality inspired by nature
Understanding EA dynamics via population fitness distributions
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
Resource sharing and coevolution in evolving cellular automata
IEEE Transactions on Evolutionary Computation
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The paper proposes formal criteria and a visualisation concept to measure relative innovation in a population of design concepts. The main criterion is called the 'Configuration Distance', and is the summation of two sub-criteria called the 'Component Distance' and 'Value Distance'. The visualisation concept is called the 'Design Solution Topography', which allows visualisation of a population of design concepts in terms of their performance, Component and Value Distances. When incorporated into a conceptual designing method, being developed by the first author, the criteria will enable designers to evaluate innovation in selected designs that also satisfy the desired performance objectives at a minimum threshold or greater.