A survey on cooperative co-evolutionary algorithms
The first cooperative co-evolutionary algorithm (CCEA) was proposed by Potter and De Jong
in 1994 and since then many CCEAs have been proposed and successfully applied to …
in 1994 and since then many CCEAs have been proposed and successfully applied to …
Evolutionary ensemble learning
MI Heywood - Handbook of Evolutionary Machine Learning, 2023 - Springer
Abstract Evolutionary Ensemble Learning (EEL) provides a general approach for scaling
evolutionary learning algorithms to increasingly complex tasks. This is generally achieved …
evolutionary learning algorithms to increasingly complex tasks. This is generally achieved …
Emergent policy discovery for visual reinforcement learning through tangled program graphs: A tutorial
S Kelly, RJ Smith, MI Heywood - Genetic programming theory and practice …, 2019 - Springer
Abstract Tangled Program Graphs (TPG) represents a framework by which multiple
programs can be organized to cooperate and decompose a task with minimal a priori …
programs can be organized to cooperate and decompose a task with minimal a priori …
On botnet detection with genetic programming under streaming data, label budgets and class imbalance
Botnets represent a widely deployed framework for remotely infecting and controlling
hundreds of networked computing devices for malicious ends. Traditionally detection of …
hundreds of networked computing devices for malicious ends. Traditionally detection of …
On botnet behaviour analysis using GP and C4. 5
F Haddadi, D Runkel, AN Zincir-Heywood… - Proceedings of the …, 2014 - dl.acm.org
Botnets represent a destructive cyber security threat that aim to hide their malicious activities
within legitimate Internet traffic. Part of what makes botnets so affective is that they often …
within legitimate Internet traffic. Part of what makes botnets so affective is that they often …
Evolving autoencoding structures through genetic programming
L Rodriguez-Coayahuitl, A Morales-Reyes… - … and Evolvable Machines, 2019 - Springer
We propose a novel method to evolve autoencoding structures through genetic
programming (GP) for representation learning on high dimensional data. It involves a …
programming (GP) for representation learning on high dimensional data. It involves a …
Problem Decomposition Strategies and Credit Distribution Mechanisms in Modular Genetic Programming for Supervised Learning
L Rodriguez-Coayahuitl… - IEEE Transactions …, 2025 - ieeexplore.ieee.org
In this review article, we provide a comprehensive guide to the endeavor of problem
decomposition within the field of Genetic Programming (GP), specifically tree-based GP for …
decomposition within the field of Genetic Programming (GP), specifically tree-based GP for …
Solving complex problems with coevolutionary algorithms
❖ Case study: Evolving arbitrary sized teams❖ Case study: Non-stationary streams❖ Case
study: Diversity maintenance and policy reuse❖ Case study: Multi-task learning under …
study: Diversity maintenance and policy reuse❖ Case study: Multi-task learning under …
Bring your own learner: A cloud-based, data-parallel commons for machine learning
We introduce FCUBE, a cloud-based framework that enables machine learning researchers
to contribute their learners to its community-shared repository. FCUBE exploits data …
to contribute their learners to its community-shared repository. FCUBE exploits data …
WB Langdon “Jaws 30”
MI Heywood - Genetic Programming and Evolvable Machines, 2023 - Springer
At the 30th anniversary of 'Jaws', the Genetic programming field has much to celebrate.
However, in order continue to build on these successes, it might be necessary to look more …
However, in order continue to build on these successes, it might be necessary to look more …