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Engineering Multi-Agent Systems

Overview of attention for book
Cover of 'Engineering Multi-Agent Systems'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 The Shaping of the Agent-Oriented Mindset
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    Chapter 2 Keeping a Clear Separation between Goals and Plans
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    Chapter 3 A Stepwise Refinement Based Development of Self-Organizing Multi-Agent Systems: Application to the Foraging Ants
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    Chapter 4 Improving the Design and Modularity of BDI Agents with Capability Relationships
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    Chapter 5 A Scalable Runtime Platform for Multiagent-Based Simulation
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    Chapter 6 Security Games in the Field: Deployments on a Transit System
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    Chapter 7 The AORTA Architecture: Integrating Organizational Reasoning in Jason
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    Chapter 8 Keep Improving MAS Method Fragments: A Medee-Based Case Study for MOISE+
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    Chapter 9 Towards Process-Oriented Modelling and Creation of Multi-Agent Systems
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    Chapter 10 Environments and Organizations in Multi-Agent Systems: From Modelling to Code
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    Chapter 11 From Multi-Agent Programming to Object Oriented Design Patterns
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    Chapter 12 CaFé: A Group Process to Rationalize Technologies in Hybrid AAMAS Systems
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    Chapter 13 Efficient Verification of MASs with Projections
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    Chapter 14 Infinite States Verification in Game-Theoretic Logics: Case Studies and Implementation
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    Chapter 15 Side Effects of Agents Are Not Just Random
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    Chapter 16 Mutation Testing for Jason Agents
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    Chapter 17 Tractable Reasoning about Group Beliefs
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    Chapter 18 Semantic Representations of Agent Plans and Planning Problem Domains
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    Chapter 19 Engineering Multi-Agent Systems
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    Chapter 20 Typing Multi-Agent Systems via Commitments
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    Chapter 21 Robust Collaboration: Enriching Decisions with Abstract Preferences
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    Chapter 22 The Interaction as an Integration Component for the JaCaMo Platform
Overall attention for this book and its chapters
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Mentioned by

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2 X users

Citations

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Readers on

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17 Mendeley
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Title
Engineering Multi-Agent Systems
Published by
Lecture notes in computer science, January 2014
DOI 10.1007/978-3-319-14484-9
ISBNs
978-3-31-914483-2, 978-3-31-914484-9
Editors

Dalpiaz, Fabiano, Dix, Jürgen, Riemsdijk, M. Birna

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 24%
Student > Bachelor 3 18%
Student > Master 3 18%
Researcher 2 12%
Professor 1 6%
Other 2 12%
Unknown 2 12%
Readers by discipline Count As %
Computer Science 11 65%
Engineering 2 12%
Economics, Econometrics and Finance 1 6%
Mathematics 1 6%
Unknown 2 12%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 08 October 2021.
All research outputs
#18,345,176
of 23,567,572 outputs
Outputs from Lecture notes in computer science
#5,942
of 8,153 outputs
Outputs of similar age
#224,782
of 308,501 outputs
Outputs of similar age from Lecture notes in computer science
#200
of 280 outputs
Altmetric has tracked 23,567,572 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,153 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one is in the 26th percentile – i.e., 26% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 308,501 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 280 others from the same source and published within six weeks on either side of this one. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.