Parallel Problem Solving from Nature PPSN VI
By Marc Schoenauer, Kalyanmoy Deb, G. Rudolph, Xin Yao, E. Lutton, J. Merelo, Hans-Paul Schwefel. Lecture Notes in Computer Science, 2000
650 citations recorded by the source corpus.
Spatially structured evolutionary algorithms (EAs) have shown to be endowed with useful features for global optimization. Distributed EAs (dEA) and cellular EAs (cEA) are two of the most widely known types of structured algorithms. In this paper we deal with cellular EAs. Two important parameters guiding the search in a cEA are the population topology and the neighborhood defined on it. Here we first review some theoretical results which show that a cEA with a 2D grid can be easily tuned to shift from exploration to exploitation. We initially make a study on the relationship between the topology and the neighborhood by defining a ratio measure between they two. Then, we encompass a set of tests aimed at discovering the performance that different ratio values have on different classes of problems. We find out that, with the same neighborhood, rectangular grids have some advantages in multimodal and epistatic problems, while square ones are more efficient for solving deceptive problems and for simple function optimization. Finally, we propose and study a cEA in which the ratio is dynamically changed.
Subfields: Computer Science Applications
View Paper: https://www.semanticscholar.org/paper/bf4652ef87c3e3e35aa092556a62b71d72b0e968
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Citations in the corpus
- Language as a Complex Adaptive System (2000, background): “But conversely, success in the language game influences the score of the categories used, so the categorisation process becomes tuned to be better adapted to the language in the environment of the agents.”
- Evolutionary Computation for Reinforcement Learning (2012, background): “In Pareto coevolution, the problem is treated as a multi-objective one, with each opponent as an objective (Ficici and Pollack, 2000, 2001).”
- MOEA/D with Adaptive Weight Adjustment (2014, background): “…Evolutionary Computation Volume 22, Number 2 D ow nloaded from http://direct.m it.edu/evco/article-pdf/22/2/231/1510396/evco_a_00109.pdf by guest on 29 Septem ber 2021 Pareto archived evolution strategy (PAES; Corne et al., 2000), and the improved version of NSGA (NSGA-II; Deb et al., 2002).”
- Biips: Software for Bayesian Inference with Interacting Particle Systems (2014, methodology): “Several softwares have been developed over the past few years, such as EASEA (Collet et al. 2000), Evolver 5 or ParadisEO (Cahon et al. 2004).”