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Differential Evolution with Nearest & Better Option for Function Optimization
Differential evolution is the conventional algorithm with the fastest co...
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Hands-free Evolution of 3D-printable Objects via Eye Tracking
Interactive evolution has shown the potential to create amazing and comp...
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Boundary Evolution Algorithm for SAT-NP
A boundary evolution Algorithm (BEA) is proposed by simultaneously takin...
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Interactive Co-Design of Form and Function for Legged Robots using the Adjoint Method
Our goal is to make robotics more accessible to casual users by reducing...
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Alfie: An Interactive Robot with a Moral Compass
This work introduces Alfie, an interactive robot that is capable of answ...
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Arena Model: Inference About Competitions
The authors propose a parametric model called the arena model for predic...
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Interactive Shape Perturbation
We present a web application for the procedural generation of perturbati...
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Paired Comparisons-based Interactive Differential Evolution
We propose Interactive Differential Evolution (IDE) based on paired comparisons for reducing user fatigue and evaluate its convergence speed in comparison with Interactive Genetic Algorithms (IGA) and tournament IGA. User interface and convergence performance are two big keys for reducing Interactive Evolutionary Computation (IEC) user fatigue. Unlike IGA and conventional IDE, users of the proposed IDE and tournament IGA do not need to compare whole individuals each other but compare pairs of individuals, which largely decreases user fatigue. In this paper, we design a pseudo-IEC user and evaluate another factor, IEC convergence performance, using IEC simulators and show that our proposed IDE converges significantly faster than IGA and tournament IGA, i.e. our proposed one is superior to others from both user interface and convergence performance points of view.
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