OpenRL: A Unified Reinforcement Learning Framework Article Swipe
Shi‐Yu Huang
,
Wentse Chen
,
Yiwen Sun
,
Fuqing Bie
,
Wei-Wei Tu
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2312.16189
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2312.16189
We present OpenRL, an advanced reinforcement learning (RL) framework designed to accommodate a diverse array of tasks, from single-agent challenges to complex multi-agent systems. OpenRL's robust support for self-play training empowers agents to develop advanced strategies in competitive settings. Notably, OpenRL integrates Natural Language Processing (NLP) with RL, enabling researchers to address a combination of RL training and language-centric tasks effectively. Leveraging PyTorch's robust capabilities, OpenRL exemplifies modularity and a user-centric approach. It offers a universal interface that simplifies the user experience for beginners while maintaining the flexibility experts require for innovation and algorithm development. This equilibrium enhances the framework's practicality, adaptability, and scalability, establishing a new standard in RL research. To delve into OpenRL's features, we invite researchers and enthusiasts to explore our GitHub repository at https://github.com/OpenRL-Lab/openrl and access our comprehensive documentation at https://openrl-docs.readthedocs.io.
Related Topics
Concepts
Computer science
Reinforcement learning
Scalability
Modularity (biology)
Flexibility (engineering)
Adaptability
Documentation
Interface (matter)
Human–computer interaction
Software engineering
Artificial intelligence
Programming language
Database
Operating system
Genetics
Maximum bubble pressure method
Bubble
Mathematics
Biology
Ecology
Statistics
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2312.16189
- https://arxiv.org/pdf/2312.16189
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4390436802
All OpenAlex metadata
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https://openalex.org/W4390436802Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2312.16189Digital Object Identifier
- Title
-
OpenRL: A Unified Reinforcement Learning FrameworkWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-12-20Full publication date if available
- Authors
-
Shi‐Yu Huang, Wentse Chen, Yiwen Sun, Fuqing Bie, Wei-Wei TuList of authors in order
- Landing page
-
https://arxiv.org/abs/2312.16189Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2312.16189Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/2312.16189Direct OA link when available
- Concepts
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Computer science, Reinforcement learning, Scalability, Modularity (biology), Flexibility (engineering), Adaptability, Documentation, Interface (matter), Human–computer interaction, Software engineering, Artificial intelligence, Programming language, Database, Operating system, Genetics, Maximum bubble pressure method, Bubble, Mathematics, Biology, Ecology, StatisticsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.framework | 8 |
| abstract_inverted_index.interface | 76 |
| abstract_inverted_index.research. | 110 |
| abstract_inverted_index.self-play | 28 |
| abstract_inverted_index.settings. | 38 |
| abstract_inverted_index.universal | 75 |
| abstract_inverted_index.Leveraging | 61 |
| abstract_inverted_index.Processing | 44 |
| abstract_inverted_index.challenges | 19 |
| abstract_inverted_index.experience | 81 |
| abstract_inverted_index.innovation | 91 |
| abstract_inverted_index.integrates | 41 |
| abstract_inverted_index.modularity | 67 |
| abstract_inverted_index.repository | 125 |
| abstract_inverted_index.simplifies | 78 |
| abstract_inverted_index.strategies | 35 |
| abstract_inverted_index.accommodate | 11 |
| abstract_inverted_index.combination | 53 |
| abstract_inverted_index.competitive | 37 |
| abstract_inverted_index.enthusiasts | 120 |
| abstract_inverted_index.equilibrium | 96 |
| abstract_inverted_index.exemplifies | 66 |
| abstract_inverted_index.flexibility | 87 |
| abstract_inverted_index.framework's | 99 |
| abstract_inverted_index.maintaining | 85 |
| abstract_inverted_index.multi-agent | 22 |
| abstract_inverted_index.researchers | 49, 118 |
| abstract_inverted_index.development. | 94 |
| abstract_inverted_index.effectively. | 60 |
| abstract_inverted_index.establishing | 104 |
| abstract_inverted_index.scalability, | 103 |
| abstract_inverted_index.single-agent | 18 |
| abstract_inverted_index.user-centric | 70 |
| abstract_inverted_index.adaptability, | 101 |
| abstract_inverted_index.capabilities, | 64 |
| abstract_inverted_index.comprehensive | 131 |
| abstract_inverted_index.documentation | 132 |
| abstract_inverted_index.practicality, | 100 |
| abstract_inverted_index.reinforcement | 5 |
| abstract_inverted_index.language-centric | 58 |
| abstract_inverted_index.https://openrl-docs.readthedocs.io. | 134 |
| abstract_inverted_index.https://github.com/OpenRL-Lab/openrl | 127 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 5 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/9 |
| sustainable_development_goals[0].score | 0.6000000238418579 |
| sustainable_development_goals[0].display_name | Industry, innovation and infrastructure |
| citation_normalized_percentile |