Fukase, Takafumi, Yuta, Kobayashi, ARANHA, Claus de Castro. Extending Lexicase DE for a Multi-Niche Constraint Satisfaction Industrial Design Problem. IEEE World Congress on Computational Intelligence. 2024
Mascarenhas, Alexandre, Yuta, Kobayashi, ARANHA, Claus de Castro. Novel Genotypic Diversity Metrics for Real-Coded Optimization on Multi-Modal Problems. IEEE World Congress on Computational Intelligence. 2024
He, Yifan, ARANHA, Claus de Castro. Evolving Benchmark Functions to Compare Evolutionary Algorithms via Genetic Programming. IEEE World Congress on Computational Intelligence. 2024
Miranda, Icaro, ARANHA, Claus de Castro, Carvalho, Andre C., P. L. F. de, Garcia, Luiz P. F. Empirical Comparison of EEG Signal Classification Techniques through Genetic Programming-based AutoML: An Extended Study. Journal of Information and Data Management (JIDM). 2024. 15. 1. 175-185
Practical Applications of Evolutionary Computation to Financial Engineering: Robust Techniques for Forecasting, Trading and Hedging
Springer Berlin Heidelberg 2012 ISBN:9783642276484
Genetic Programming Theory and Practice VIII
Springer New York 2011
Development of Hybrid Evolutionary Techniques to Solve Resource Allocation Problems
2010
Portfolio Management with Cost Model using Multi Objective Genetic Algorithms
2007
Auto-Diagnosis and Auto-Repair for Robots
Universidade Estadual de Campinas 2005
講演・口頭発表等 (70件):
Extending Lexicase DE for a Multi-Niche Constraint Satisfaction Industrial Design Problem
(IEEE World Congress on Computational Intelligence)
Novel Genotypic Diversity Metrics for Real-Coded Optimization on Multi-Modal Problems
(IEEE World Congress on Computational Intelligence)
Evolving Benchmark Functions to Compare Evolutionary Algorithms via Genetic Programming
(IEEE World Congress on Computational Intelligence)
Multi-agent City Expansion With Land Use and Transport
(ALIFE 2023: Ghost in the Machine: Proceedings of the 2023 Artificial Life Conference)
Simulating Disease Spread During Disaster Scenarios
(ALIFE 2023: Ghost in the Machine: Proceedings of the 2023 Artificial Life Conference)