https://github.com/abm4all/rockpaperscissorstrainer
Example for `Trainer` implementation.
Science Score: 10.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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○codemeta.json file
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○.zenodo.json file
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○DOI references
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✓Academic publication links
Links to: ieee.org -
○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (4.9%) to scientific vocabulary
Repository
Example for `Trainer` implementation.
Basic Info
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
README
This RockPaperScissorsTrainer model is built to show how the
Trainer module of Melodie can be used.
It implements the "evolutionary training" framework proposed in this paper:
Yu, S. (2022). An Agent-Based Framework for Policy Simulation: Modeling Heterogeneous Behaviors With Modified Sigmoid Function and Evolutionary Training. IEEE Transactions on Computational Social Systems.
You can find the document of this RockPaperScissorsTrainer model here.
Compatibility Notice
Branch main is for Melodie>=1.0.0. To run this example
with Melodie under 1.0.0, please checkout the legacy branch.
Owner
- Name: ABM4ALL
- Login: ABM4ALL
- Kind: organization
- Email: abm4all@outlook.com
- Location: Germany
- Repositories: 12
- Profile: https://github.com/ABM4ALL