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- posterAugust 2024
SAIS: A Novel Bio-Inspired Artificial Immune System Based on Symbiotic Paradigm
GECCO '24 Companion: Proceedings of the Genetic and Evolutionary Computation Conference CompanionPages 2115–2118https://doi.org/10.1145/3638530.3664188We propose a novel type of Artificial Immune System (AIS): Symbiotic Artificial Immune Systems (SAIS), drawing inspiration from symbiotic relationships in biology. SAIS parallels the three key stages (i.e., mutualism, commensalism and parasitism) of ...
- posterAugust 2024
Improving the Efficiency Of Genetic Programming for Classification Tasks Using a Phased Approach
GECCO '24 Companion: Proceedings of the Genetic and Evolutionary Computation Conference CompanionPages 1702–1705https://doi.org/10.1145/3638530.3664184Genetic Programming (GP) uses Darwinian evolution to generate algorithms for tasks such as classification and symbolic regression. However, a drawback is the interpreter used to evaluate candidate programs adding significant computational cost. Hence, ...
- research-articleAugust 2024
A Closer Look at Length-niching Selection and Spatial Crossover in Variable-length Evolutionary Rule Set Learning
GECCO '24 Companion: Proceedings of the Genetic and Evolutionary Computation Conference CompanionPages 1779–1787https://doi.org/10.1145/3638530.3664178We explore variable-length metaheuristics for optimizing sets of rules for regression tasks by extending an earlier short paper that performed a preliminary analysis of several variants of a single-objective Genetic Algorithm. We describe more in depth ...
- research-articleAugust 2024
Characterising the Double Descent of Symbolic Regression
GECCO '24 Companion: Proceedings of the Genetic and Evolutionary Computation Conference CompanionPages 2050–2057https://doi.org/10.1145/3638530.3664176Recent work has argued that many machine learning techniques exhibit a 'double descent' in model risk, where increasing model complexity beyond an interpolation zone can overcome the bias-variance tradeoff to produce large, over-parameterised models that ...
- research-articleAugust 2024
Shadow Gene Guidance: A Novel Approach for Elevating Genetic Programming Classifications and Boosting Predictive Confidence
GECCO '24 Companion: Proceedings of the Genetic and Evolutionary Computation Conference CompanionPages 2095–2098https://doi.org/10.1145/3638530.3664175This paper introduces a novel classification method that utilizes genetic programming (GP). The primary purpose of the proposed method is to enhance future generations of GP, through continuously refining the genetic makeup of the population for improved ...
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- research-articleAugust 2024
LLM Fault Localisation within Evolutionary Computation Based Automated Program Repair
GECCO '24 Companion: Proceedings of the Genetic and Evolutionary Computation Conference CompanionPages 1824–1829https://doi.org/10.1145/3638530.3664174Repairing bugs can be a daunting task for even a human experienced in debugging, so naturally, attempting to automatically repair programs with a computer system is quite challenging. The existing methods of automated program repair leave a lot of room ...
- research-articleAugust 2024
Minimizing the EXA-GP Graph-Based Genetic Programming Algorithm for Interpretable Time Series Forecasting
GECCO '24 Companion: Proceedings of the Genetic and Evolutionary Computation Conference CompanionPages 1686–1690https://doi.org/10.1145/3638530.3664173This work provides a modification to the Evolutionary eXploration of Augmenting Memory Models (EXA-GP) graph-based genetic programming (GGP) algorithm, enabling it to produce time series forecasting (TSF) equations that are vastly more simple and ...
- research-articleAugust 2024
Enhancing Classification Through Multi-view Synthesis in Multi-Population Ensemble Genetic Programming
- Mohammad Sadegh Khorshidi,
- Navid Yazdanjue,
- Hassan Gharoun,
- Danial Yazdani,
- Mohammad Reza Nikoo,
- Fang Chen,
- Amir H. Gandomi
GECCO '24 Companion: Proceedings of the Genetic and Evolutionary Computation Conference CompanionPages 2099–2102https://doi.org/10.1145/3638530.3664172This study proposes a genetic programming (GP) approach for classification, integrating cooperative co-evolution with multi-view synthesis. Addressing the challenges of high-dimensional data, we enhance GP by distributing features across multiple ...
- research-articleAugust 2024
Accelerating GP Genome Evaluation Through Real Compilation with a Multiple Program Single Data Approach
GECCO '24 Companion: Proceedings of the Genetic and Evolutionary Computation Conference CompanionPages 2041–2049https://doi.org/10.1145/3638530.3664168Genetic Programming (GP) presents a unique challenge in fitness evaluation due to the need to repeatedly execute the evolved programs, often represented as tree structures, to assess their quality on multiple input data. Traditional approaches rely on ...
- research-articleAugust 2024
Towards Evolutionary-based Automated Machine Learning for Small Molecule Pharmacokinetic Prediction
GECCO '24 Companion: Proceedings of the Genetic and Evolutionary Computation Conference CompanionPages 1544–1553https://doi.org/10.1145/3638530.3664166Machine learning (ML) is revolutionising drug discovery by expediting the prediction of small molecule properties essential for developing new drugs. These properties - including absorption, distribution, metabolism and excretion (ADME) - are crucial in ...
- research-articleAugust 2024
A Survey on Learning Classifier Systems from 2022 to 2024
GECCO '24 Companion: Proceedings of the Genetic and Evolutionary Computation Conference CompanionPages 1797–1806https://doi.org/10.1145/3638530.3664165Learning classifier systems (LCSs) are a state-of-the-art methodology for developing rule-based machine learning by applying discovery algorithms and learning components. LCSs have become proficient at linking environmental features to describe simple ...
- research-articleAugust 2024
Genetic Programming for the Reconstruction of Delay Differential Equations in Economics
GECCO '24 Companion: Proceedings of the Genetic and Evolutionary Computation Conference CompanionPages 2119–2122https://doi.org/10.1145/3638530.3664164In this paper we explore the reconstruction of a delay differential equation (DDE) model from economics, the Kalecki's business cycle model, with a variant of genetic programming (GP) encoding the structure of DDEs. The results of this preliminary work ...
- research-articleAugust 2024
Backend-agnostic Tree Evaluation for Genetic Programming
GECCO '24 Companion: Proceedings of the Genetic and Evolutionary Computation Conference CompanionPages 1649–1657https://doi.org/10.1145/3638530.3664161The explicit vectorization of the mathematical operations required for fitness calculation can dramatically increase the efficiency of tree-based genetic programming for symbolic regression. In this paper, we introduce a modern software design for the ...
- research-articleAugust 2024
A Generative Evolutionary Many-Objective Framework: A Case Study in Antimicrobial Agent Design
- Matheus Muller Pereira Da Silva,
- Jaqueline Silva Angelo,
- Isabella Alvim Guedes,
- Laurent Emmanuel Dardenne
GECCO '24 Companion: Proceedings of the Genetic and Evolutionary Computation Conference CompanionPages 1623–1630https://doi.org/10.1145/3638530.3664159de novo drug design (dnDD) aims to generate novel molecules that meet several conflicting objectives, positioning it as a quintessential many-objective optimization problem (MaOP), where more than three objectives must be simultaneously optimized. This ...
- research-articleAugust 2024
Analyzing the Runtime of the Gene-pool Optimal Mixing Evolutionary Algorithm (GOMEA) on the Concatenated Trap Function
GECCO '24 Companion: Proceedings of the Genetic and Evolutionary Computation Conference CompanionPages 1520–1526https://doi.org/10.1145/3638530.3664158The Gene-pool Optimal Mixing Evolutionary Algorithm (GOMEA) is a state of the art evolutionary algorithm that leverages linkage learning to efficiently exploit problem structure. By identifying and preserving important building blocks during variation, ...
- research-articleAugust 2024
Learning Classifier Systems as a Solver for the Abstraction and Reasoning Corpus
GECCO '24 Companion: Proceedings of the Genetic and Evolutionary Computation Conference CompanionPages 1770–1778https://doi.org/10.1145/3638530.3664157The abstraction and reasoning corpus (ARC) is a challenging AI benchmark as it requires models to learn unseen relationships from a few data points. Each puzzle only contains 2--5 training examples, which makes it hard for models that require training on ...
- research-articleAugust 2024
Explaining Session-based Recommendations using Grammatical Evolution
GECCO '24 Companion: Proceedings of the Genetic and Evolutionary Computation Conference CompanionPages 1590–1597https://doi.org/10.1145/3638530.3664156This paper concerns explaining session-based recommendations using Grammatical Evolution. A session-based recommender system processes a given sequence of products browsed by a user and suggests the most relevant next product to display to the user. ...
- research-articleAugust 2024
EvoAl - Codeless Domain-Optimisation
GECCO '24 Companion: Proceedings of the Genetic and Evolutionary Computation Conference CompanionPages 1640–1648https://doi.org/10.1145/3638530.3664154Applying optimisation techniques such as evolutionary computation to real-world tasks often requires significant adaptation. However, specific application domains do not typically demand major changes to existing optimisation methods. The decisive aspect ...
- research-articleAugust 2024
Efficacy of using a dynamic length representation vs. a fixed-length for neuroarchitecture search
GECCO '24 Companion: Proceedings of the Genetic and Evolutionary Computation Conference CompanionPages 1888–1894https://doi.org/10.1145/3638530.3664149Deep learning neuroarchitecture and hyperparameter search are important in finding the best configuration that maximizes learned model accuracy. However, the number of types of layers, their associated hyperparameters, and the myriad of ways to connect ...
- research-articleAugust 2024
XCS with dynamic sized experience replay for memory constrained applications
GECCO '24 Companion: Proceedings of the Genetic and Evolutionary Computation Conference CompanionPages 1807–1814https://doi.org/10.1145/3638530.3664148The eXtended Classifier System (XCS) is the most widely studied classifier system in the community. It is a class of interpretable AI which has shown strong capability to master various classification and regression tasks. It has also shown strong ...