Cited by 1,218Multi-Agent Systems and NegotiationReinforcement Learning in RoboticsDistributed Control Multi-Agent Systems

Multiagent systems: A survey from a machine learning perspective

Stone, Peter, Veloso, Manuela·2000·Autonomous Robots

Integrity signals

Registry

Crossref · 10.1023/a:1008942012299

Cites

167 of 167 references verified0 citation errors · 0 not checkable

Statistics

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Claims the paper makes

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Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Compared to a single-agent setting, an MAS more realistically represents complex real-world scenarios involving multiple decision-makers or information sources.

    “Compared to a single-agent setting, an MAS more realistically represents complex real-world scenarios involving multiple decision-makers or information sources [7,8].”

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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
167
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
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 › Computer Science › Computer Networks and Communications › Distributed Control Multi-Agent Systems
Keywords
multi-agent systems, distributed artificial intelligence, distributed problem solving, behavior management, robot soccer

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

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