Evolve On Click (EvOC) - An Intuitive Web Platform to Collaboratively Implement, Execute, and Visualize Evolutionary Algorithms
Created by W.Langdon from
gp-bibliography.bib Revision:1.8620
- @InProceedings{murali:2025:GECCOcomp,
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author = "Ritwik Murali and Ashwin Narayanan Sivamani and
Abhinav Ramakrishnan and Hariharan Arul and Ananya R",
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title = "Evolve On Click {(EvOC)} - An Intuitive Web Platform
to Collaboratively Implement, Execute, and Visualize
Evolutionary Algorithms",
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booktitle = "Proceedings of the 2025 Genetic and Evolutionary
Computation Conference Companion",
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year = "2025",
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editor = "Carola Doerr and Mike Preuss",
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pages = "147--150",
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address = "Malaga, Spain",
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series = "GECCO '25 Companion",
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month = "14-18 " # jul,
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organisation = "SIGEVO",
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publisher = "Association for Computing Machinery",
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publisher_address = "New York, NY, USA",
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keywords = "genetic algorithms, genetic programming, evolutionary
algorithms, distributed artificial intelligence,
distributed evolutionary algorithms in python, DEAP,
software architectures, evolutionary computation,
Benchmarking, Benchmarks, Software, Reproducibility:
Poster",
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isbn13 = "979-8-4007-1464-1",
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URL = "
https://doi.org/10.1145/3712255.3726652",
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DOI = "
10.1145/3712255.3726652",
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size = "4 pages",
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abstract = "This paper proposes {"}Evolve On Click{"} (EvOC) - an
open-source intuitive web-based platform to simplify
the implementation, execution, and visualization of
Evolutionary Algorithms (EAs) including genetic
programming, by providing a user-friendly interface.
This facilitates easier accessibility of evolutionary
algorithm software packages such as DEAP, to users with
minimal programming experience. EvOC guides users
through the EA design process, allowing them to
experiment with different algorithms, parameters, and
configurations without the need for programming
expertise. The platform also incorporates features to
show code created based on the configuration so that
users can also learn from it, thus enhancing
collaboration and enabling users to easily share their
results with others. The architecture used by EvOC also
supports ease of access for parallel and distributed
EAs with real-time log streaming / monitoring and
visualization of the evolution runs. By incorporating
the latest DevOps techniques during the development
process, EvOC does not require extensive maintenance
and allows for the platform to be run as a service,
supporting multiple users on a single instance. This
paper details the design, implementation, and
evaluation of EvOC towards increasing accessibility and
ease of comfort with EAs for novice learners - thus
broadening the reach of the community.",
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notes = "GECCO-2025 BBSR A Recombination of the 34th
International Conference on Genetic Algorithms (ICGA)
and the 30th Annual Genetic Programming Conference
(GP)",
- }
Genetic Programming entries for
Ritwik Murali
Ashwin Narayanan Sivamani
Abhinav Ramakrishnan
Hariharan Arul
Ananya R
Citations