144 citations · 175 across the 16 of their papers we have counts for
3 papers · 1 filter
Faster Convergence in Multi-Objective Optimization Algorithms Based on Decomposition
Yuri Lavinas, Marcelo Ladeira, Claus Aranha
The Resource Allocation approach (RA) improves the performance of MOEA/D by maintaining a big population and updating few solutions each generation. However, most of the studies on…
MOEA/D with Adaptative Number of Weight Vectors
Yuri Lavinas, Abe Mitsu Teru, Yuta Kobayashi +1
The Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D) is a popular algorithm for solving Multi-Objective Problems (MOPs). The main component of MOEA/D is to de…
Impressions of the GDMC AI Settlement Generation Challenge in Minecraft
Christoph Salge, Claus Aranha, Adrian Brightmoore +15
The GDMC AI settlement generation challenge is a PCG competition about producing an algorithm that can create an "interesting" Minecraft settlement for a given map. This paper cont…