Samuel Carvalho
Research Subjects
Samuel Carvalho has a total of 9 co-authors. Here are the top co-authors by number of shared publications:
- Conor Ryan
University of Limerick
4 shared publications - Douglas Mota Dias
Atlantic Technological University, Galway, Ireland
4 shared publications - Allan de Lima
University of Limerick, Limerick, Ireland
3 shared publications - Joe Sullivan
Limerick Institute of Technology
3 shared publications - Aidan Murphy
University College Dublin, Dublin, Ireland
1 shared publication - Ayman Youssef
Department of Computers and Systems, Electronics Research Institute, Cairo 12622, Egypt
1 shared publication
Latest Publications
- 28 March 2024
- Published by Springer Nature
- p. 3-20
Fuzzy Pattern Trees for Classification Problems Using Genetic Programming
- 28 March 2024
- Published by Springer Nature
- p. 3-20
Fuzzy Pattern Trees for Classification Problems Using Genetic Programming
- 26 October 2023
- Published by Springer Nature
- p. 90-103
Performance Upgrade of Sequence Detector Evolution Using Grammatical Evolution and Lexicase Parent Selection Method
- 26 October 2023
- Published by Springer Nature
- p. 90-103
Performance Upgrade of Sequence Detector Evolution Using Grammatical Evolution and Lexicase Parent Selection Method
- Open Access
- 15 July 2023
- Published by Association for Computing Machinery (ACM)
- p. 555-558
Leap Mapping: Improving Grammatical Evolution for Modularity Problems
- 15 July 2023
- Published by Association for Computing Machinery (ACM)
- p. 555-558
Open AccessLeap Mapping: Improving Grammatical Evolution for Modularity Problems
- Open Access
GRAPE: Grammatical Algorithms in Python for Evolution
GRAPE is an implementation of Grammatical Evolution (GE) in DEAP, an Evolutionary Computation framework in Python, which consists of the necessary classes and functions to evolve a population of grammar-based solutions, while reporting essential measures. This tool was developed at the Bio-computing and Developmental Systems (BDS) Research Group, the birthplace of GE, as an easy to use (compared to the canonical C++ implementation, libGE) tool that inherits all the advantages of DEAP, such as selection methods, parallelism and multiple search techniques, all of which can be used with GRAPE. In this paper, we address some problems to exemplify the use of GRAPE and to perform a comparison with PonyGE2, an existing implementation of GE in Python. The results show that GRAPE has a similar performance, but is able to avail of all the extra facilities and functionality found in the DEAP framework. We further show that GRAPE enables GE to be applied to systems identification problems and we demonstrate this on two benchmark problems.
Open AccessGRAPE: Grammatical Algorithms in Python for Evolution
GRAPE is an implementation of Grammatical Evolution (GE) in DEAP, an Evolutionary Computation framework in Python, which consists of the necessary classes and functions to evolve a population of grammar-based solutions, while reporting essential measures. This tool was developed at the Bio-computing and Developmental Systems (BDS) Research Group, the birthplace of GE, as an easy to use (compared to the canonical C++ implementation, libGE) tool that inherits all the advantages of DEAP, such as selection methods, parallelism and multiple search techniques, all of which can be used with GRAPE. In this paper, we address some problems to exemplify the use of GRAPE and to perform a comparison with PonyGE2, an existing implementation of GE in Python. The results show that GRAPE has a similar performance, but is able to avail of all the extra facilities and functionality found in the DEAP framework. We further show that GRAPE enables GE to be applied to systems identification problems and we demonstrate this on two benchmark problems.