Jessica Mégane

PhD Student

University of Coimbra

About me

I am a PhD student at the University of Coimbra, Portugal, and I work as a researcher for the Evolutionary and Complex Systems (ECOS) group of the Centre for Informatics and Systems of the University of Coimbra (CISUC).

I am the author of Probabilistic Grammatical Evolution and some variants, and it will continue to be the main focus of my research. I like to hear other researchers’ opinions and discuss ideas, so feel free to get in touch!

Outside of academia, in my spare time I like to watch series, read mostly fiction books and play tennis.

Interests

Evolutionary Computation
Neuroevolution
Complex Systems

Education

PhD in Informatics Engineering, 2021-now
University of Coimbra
MSc in Intelligent Systems, 2019-2021
University of Coimbra
BSc in Informatics Engineering, 2016-2019
University of Coimbra

Publications

Co-evolutionary Probabilistic Structured Grammatical Evolution

In Co-evolutionary Probabilistic Structured Grammatical Evolution (Co-PSGE) each individual in the population is composed by a grammar and a genotype, which is a list of dynamic lists, each corresponding to a non-terminal of the grammar containing real numbers that correspond to the probability of choosing a derivation rule. Each individual uses its own grammar to map the genotype into a program.

Jessica Mégane, Nuno Lourenço, Penousal Machado

Probabilistic Structured Grammatical Evolution

Probabilistic Structured Grammatical Evolution (PSGE) is a new approach that combines the Structured Grammatical Evolution (SGE) and Probabilistic Grammatical Evolution (PGE) representation variants and mapping mechanisms. The genotype is a set of dynamic lists, one for each non-terminal in the grammar, with each element of the list representing a probability used to select the next Probabilistic Context-Free Grammar (PCFG) derivation rule.

Jessica Mégane, Nuno Lourenço, Penousal Machado

Probabilistic Grammatical Evolution

Probabilistic Grammatical Evolution (PGE) introduces a new genotypic representation and new mapping mechanism for GE. Specifically, we resort to a Probabilistic Context-Free Grammar (PCFG) where its probabilities are adapted during the evolutionary process, taking into account the productions chosen to construct the fittest individual. The genotype is a list of real values, where each value represents the likelihood of selecting a derivation rule.

Jessica Mégane, Nuno Lourenço, Penousal Machado

Recent & Upcoming Talks

21 Jul, 2022 13:00 — 14:00 Padua, Italy

Probabilistic Structured Grammatical Evolution at IEEE WCCI 2022

Presentation of Probabilistic Structured Grammatical Evolution (PSGE) algorithm which combines the Structured Grammatical Evolution (SGE) and Probabilistic Grammatical Evolution (PGE) representation variants and mapping mechanisms.

Jessica Mégane, Penousal Machado, Nuno Lourenço

11 Jul, 2022 14:40 — 15:00 Caspian Room

Co-evolutionary Probabilistic Structured Grammatical Evolution at GECCO 2022

Presentation of Co-evolutionary Probabilistic Structured Grammatical Evolution (Co-PSGE) algorithm, in which each individual in the population is composed by a grammar and a genotype, which is a list of dynamic lists, each corresponding to a non-terminal of the grammar containing real numbers that correspond to the probability of choosing a derivation rule. Each individual uses its own grammar to map the genotype into a program. During the evolutionary process, both the grammar and the genotype are subject to variation operators.