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Multiagent Systems: A Survey from a Machine Learning Perspective
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“Compared to a single-agent setting, an MAS more realistically represents complex real-world scenarios involving multiple decision-makers or information sources [7,8].”
From A Review of Multi-Agent AI Systems for Biological and Clinical Data Analysis (2026) · cites this paper as [8]
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Metadata
- Authors
- Stone, P., & Veloso, M.
- Affiliations
- AT&T (United States) (US)
- Carnegie Mellon University (US)
- Venue
- Autonomous Robots
- Published
- 2000-06
- Volume
- 8
- Issue
- 3
- Pages
- 345-383
- ISSN
- 0929-5593 (ISSN-L)
- 1573-7527
- OpenAlex
- W2147492008
- Cited by
- 1,218
- References
- 178
- Citations by year
- 2026: 57 · 2025: 42 · 2024: 31 · 2023: 21 · 2022: 37 · 2021: 59 · 2020: 65 · 2019: 58 · 2018: 64 · 2017: 69 · 2016: 42 · 2015: 48 · 2014: 52 · 2013: 45 · 2012: 42
- FWCI
- 32.90
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Autonomous Robots (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Multi-Agent Systems and Negotiation
- Physical Sciences › Computer Science › Artificial Intelligence › Reinforcement Learning in Robotics
- Physical Sciences › Engineering › Control and Systems Engineering › Distributed Control Multi-Agent Systems
- Keywords
- multi-agent systems, distributed artificial intelligence, distributed problem solving, behavior management, robot soccer
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