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[PRE REVIEW]: OpenTTDLab: A Python framework for reproducible experiments using OpenTTD #7600
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Five most similar historical JOSS papers: Abmarl: Connecting Agent-Based Simulations with Multi-Agent Reinforcement Learning Pybehave: a hardware agnostic, Python-based framework for controlling behavioral neuroscience experiments neworder: a dynamic microsimulation framework for Python epyc: Computational experiment management in Python Simulation Decomposition in Python |
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Five most similar historical JOSS papers: Abmarl: Connecting Agent-Based Simulations with Multi-Agent Reinforcement Learning Pybehave: a hardware agnostic, Python-based framework for controlling behavioral neuroscience experiments neworder: a dynamic microsimulation framework for Python epyc: Computational experiment management in Python Simulation Decomposition in Python |
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Five most similar historical JOSS papers: Abmarl: Connecting Agent-Based Simulations with Multi-Agent Reinforcement Learning neworder: a dynamic microsimulation framework for Python Pybehave: a hardware agnostic, Python-based framework for controlling behavioral neuroscience experiments epyc: Computational experiment management in Python Simulation Decomposition in Python |
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Submitting author: @michalc (Michal Charemza)
Repository: https://github.com/michalc/OpenTTDLab
Branch with paper.md (empty if default branch): main
Version: v0.0.74
Editor: @skanwal
Reviewers: Pending
Managing EiC: Chris Vernon
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