This paper presents FEFFuL, an architecture used to estimate the fitness value of a generated artifact in any Evolution Strategy (ES) system that would otherwise require human evaluation, i.e.: Interactive Evolutionary Computation (IEC) systems. By learning directly human preferences, the FEFFuL network aims to reduce user's fatigue to a minimum while also adapting to new emergent artifacts. We apply here FEFFuL in the context of evaluating generated structures in the popular game Minecraft.
2021, SYSTEM 2021 Scholar’s Yearly Symposium of Technology, Engineering and Mathematics 2021, Pages 75-79 (volume: 3092)
FEFFuL: A Few-Examples Fitness Function Learner (04b Atto di convegno in volume)
Brandizzi N., Fanti A., Gallotta R., Napoli C.
Gruppo di ricerca: Artificial Intelligence and Robotics