Benchmarking Robustness and Generalization in Multi-Agent Systems: A Case Study on Neural MMO Article Swipe
Yangkun Chen
,
Joseph Suárez
,
Junjie Zhang
,
Chenghui Yu
,
Bo Wu
,
Hanmo Chen
,
Hengman Zhu
,
Rui Du
,
Shanliang Qian
,
Shuai Liu
,
Weijun Hong
,
Jinke He
,
Yi-Bing Zhang
,
Liang Zhao
,
Clare Zhu
,
Julian Togelius
,
Sharada P. Mohanty
,
Jiaxin Chen
,
Xiu Li
,
Xiaolong Zhu
,
Phillip Isola
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2308.15802
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2308.15802
We present the results of the second Neural MMO challenge, hosted at IJCAI 2022, which received 1600+ submissions. This competition targets robustness and generalization in multi-agent systems: participants train teams of agents to complete a multi-task objective against opponents not seen during training. The competition combines relatively complex environment design with large numbers of agents in the environment. The top submissions demonstrate strong success on this task using mostly standard reinforcement learning (RL) methods combined with domain-specific engineering. We summarize the competition design and results and suggest that, as an academic community, competitions may be a powerful approach to solving hard problems and establishing a solid benchmark for algorithms. We will open-source our benchmark including the environment wrapper, baselines, a visualization tool, and selected policies for further research.
Related Topics
Concepts
Benchmarking
Robustness (evolution)
Reinforcement learning
Benchmark (surveying)
Computer science
Generalization
Artificial intelligence
Task (project management)
Competition (biology)
Machine learning
Visualization
Domain (mathematical analysis)
Engineering
Systems engineering
Management
Mathematics
Economics
Gene
Biology
Geography
Biochemistry
Mathematical analysis
Geodesy
Chemistry
Ecology
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2308.15802
- https://arxiv.org/pdf/2308.15802
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4386348109
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4386348109Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.2308.15802Digital Object Identifier
- Title
-
Benchmarking Robustness and Generalization in Multi-Agent Systems: A Case Study on Neural MMOWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-08-30Full publication date if available
- Authors
-
Yangkun Chen, Joseph Suárez, Junjie Zhang, Chenghui Yu, Bo Wu, Hanmo Chen, Hengman Zhu, Rui Du, Shanliang Qian, Shuai Liu, Weijun Hong, Jinke He, Yi-Bing Zhang, Liang Zhao, Clare Zhu, Julian Togelius, Sharada P. Mohanty, Jiaxin Chen, Xiu Li, Xiaolong Zhu, Phillip IsolaList of authors in order
- Landing page
-
https://arxiv.org/abs/2308.15802Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2308.15802Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2308.15802Direct OA link when available
- Concepts
-
Benchmarking, Robustness (evolution), Reinforcement learning, Benchmark (surveying), Computer science, Generalization, Artificial intelligence, Task (project management), Competition (biology), Machine learning, Visualization, Domain (mathematical analysis), Engineering, Systems engineering, Management, Mathematics, Economics, Gene, Biology, Geography, Biochemistry, Mathematical analysis, Geodesy, Chemistry, EcologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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