no code implementations • 12 Feb 2024 • Wolfgang Banzhaf, Illya Bakurov
In this contribution, we discuss the basic concepts of genotypes and phenotypes in tree-based GP (TGP), and then analyze their behavior using five benchmark datasets.
1 code implementation • 31 Jul 2023 • Nathan Haut, Wolfgang Banzhaf, Bill Punch
This paper examines various methods of computing uncertainty and diversity for active learning in genetic programming.
no code implementations • 31 Jul 2023 • Stephen Kelly, Daniel S. Park, Xingyou Song, Mitchell McIntire, Pranav Nashikkar, Ritam Guha, Wolfgang Banzhaf, Kalyanmoy Deb, Vishnu Naresh Boddeti, Jie Tan, Esteban Real
We evolve modular policies that tune their model parameters and alter their inference algorithm on-the-fly to adapt to sudden environmental changes.
no code implementations • 15 Nov 2022 • Ting Hu, Gabriela Ochoa, Wolfgang Banzhaf
Genotype-to-phenotype mappings translate genotypic variations such as mutations into phenotypic changes.
no code implementations • 9 Sep 2022 • Iliya Miralavy, Wolfgang Banzhaf
Gene Regulatory Networks are networks of interactions in biological organisms responsible for determining the production levels of proteins and peptides.
no code implementations • 31 May 2022 • Nathan Haut, Wolfgang Banzhaf, Bill Punch
The use of correlation as a fitness function is explored in symbolic regression tasks and the performance is compared against the typical RMSE fitness function.
no code implementations • 28 Apr 2022 • Shuyue Stella Li, Hannah Peeler, Andrew N. Sloss, Kenneth N. Reid, Wolfgang Banzhaf
In this paper, we present the novel use of genetic improvement to find problem-specific optimized LLVM pass sequences.
no code implementations • 26 Feb 2022 • Yuan Yuan, Wolfgang Banzhaf
In cases where large programs are required for a solution, it is generally believed that {\it stochastic} search has advantages over other classes of search techniques.
no code implementations • 9 Feb 2022 • Nathan Haut, Wolfgang Banzhaf, Bill Punch
The approach begins with a small number of data points for StackGP to model.
no code implementations • 8 Feb 2022 • Iliya Miralavy, Alexander Bricco, Assaf Gilad, Wolfgang Banzhaf
In this paper, we propose POET, a computational Genetic Programming tool based on evolutionary computation methods to enhance screening and mutagenesis in Directed Evolution and help protein engineers to find proteins that have better functionality.
1 code implementation • 31 Jan 2022 • Hannah Peeler, Shuyue Stella Li, Andrew N. Sloss, Kenneth N. Reid, Yuan Yuan, Wolfgang Banzhaf
In this paper we introduce Shackleton as a generalized framework enabling the application of linear genetic programming -- a technique under the umbrella of evolutionary algorithms -- to a variety of use cases.
no code implementations • 23 Jun 2021 • Stephen Kelly, Tatiana Voegerl, Wolfgang Banzhaf, Cedric Gondro
We use genetic programming to evolve highly-generalized agents capable of operating in six unique environments from the control literature, including OpenAI's entire Classic Control suite.
1 code implementation • 9 Feb 2021 • Kenneth N. Reid, Iliya Miralavy, Stephen Kelly, Wolfgang Banzhaf, Cedric Gondro
Efficient optimization of resources is paramount to success in many problems faced today.
1 code implementation • ECCV 2020 • Zhichao Lu, Kalyanmoy Deb, Erik Goodman, Wolfgang Banzhaf, Vishnu Naresh Boddeti
In this paper, we propose an efficient NAS algorithm for generating task-specific models that are competitive under multiple competing objectives.
Ranked #17 on Neural Architecture Search on ImageNet
no code implementations • 3 Jul 2020 • Wolfgang Banzhaf
We consider a number of Artificial Chemistry models for economic activity and what consequences they have for the formation of economic inequality.
no code implementations • 23 May 2020 • Honglin Bao, Wolfgang Banzhaf
In this model, the standard hunting game of stag is modified into a new situation with social hierarchy and penalty.
2 code implementations • 12 May 2020 • Zhichao Lu, Gautam Sreekumar, Erik Goodman, Wolfgang Banzhaf, Kalyanmoy Deb, Vishnu Naresh Boddeti
At the same time, the architecture search and transfer is orders of magnitude more efficient than existing NAS methods.
Ranked #1 on Neural Architecture Search on STL-10
Fine-Grained Image Classification Neural Architecture Search +1
no code implementations • 1 May 2020 • Francisco Fernández de Vega, Gustavo Olague, Francisco Chávez, Daniel Lanza, Wolfgang Banzhaf, Erik Goodman
This new perspective allows us to understand that new methods for bloat control can be derived, and the first of such a method is described and tested.
1 code implementation • 3 Dec 2019 • Zhichao Lu, Ian Whalen, Yashesh Dhebar, Kalyanmoy Deb, Erik Goodman, Wolfgang Banzhaf, Vishnu Naresh Boddeti
While existing approaches have achieved competitive performance in image classification, they are not well suited to problems where the computational budget is limited for two reasons: (1) the obtained architectures are either solely optimized for classification performance, or only for one deployment scenario; (2) the search process requires vast computational resources in most approaches.
Ranked #1 on Pneumonia Detection on ChestX-ray14
no code implementations • 18 Apr 2019 • Vinicius V. Melo, Danilo Vasconcellos Vargas, Wolfgang Banzhaf
Lexicase selection achieves very good solution quality by introducing ordered test cases.
2 code implementations • 8 Oct 2018 • Zhichao Lu, Ian Whalen, Vishnu Boddeti, Yashesh Dhebar, Kalyanmoy Deb, Erik Goodman, Wolfgang Banzhaf
This paper introduces NSGA-Net -- an evolutionary approach for neural architecture search (NAS).
no code implementations • 27 Sep 2018 • Zhichao Lu, Ian Whalen, Vishnu Boddeti, Yashesh Dhebar, Kalyanmoy Deb, Erik Goodman, Wolfgang Banzhaf
This paper introduces NSGA-Net, an evolutionary approach for neural architecture search (NAS).
no code implementations • 14 Mar 2017 • Vinícius Veloso de Melo, Wolfgang Banzhaf
This procedure is evolved by the Command Center during the global optimization process in order to adapt DSO to the search landscape.