[Amdnl] [CFP] IEEE Transactions on Cognitive and Developmental Systems Special Issue on Cognitive Learning of Multi-Agent Systems

[Chenguang Yang]

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Call for Papers: IEEE Transactions on Cognitive and Developmental Systems
Special Issue on Cognitive Learning of Multi-Agent Systems
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Deadline for submission:  Feb 15, 2023 (extended)
https://cis.ieee.org/images/files/Documents/call-for-special-issues/Cognitive_Learning_of_Multi-Agent_Systems-IEEE_TCDS-CFP-20211210.pdf


The 2021 Nobel Prize for physics was awarded to Prof. Giorgio Parisi, whose
exceptional research contributions include deciphering the collective
behavior of birds. This phenomenon reflects the development and
cognition of biological and intelligent individuals, which sheds light on
the development of cognitive, autonomous and evolutionary robotics. Each
individual effectively transmits information and learn from several
neighbors, and thus making cooperative decision-making among them. Such
interactions among individuals show the development and cognition of
natural groups in the evolutionary process, which can be modeled as
multi-agent systems. Multi-agent systems are capable of solving
complex tasks, which also improve the robustness and efficiency through
collaborative learning. Multi-agent learning is playing an increasingly
important role in various fields, such as aerospace systems, intelligent
transportation, smart grids, etc. As the environment is becoming more
complicated (e.g., highly dynamic environment and incomplete/imperfect
observational information, etc.), tasks are becoming more difficult (e.g.,
how to share information, how to set learning objectives, and how to deal
with the curse of dimensionality, etc.), most of the existing methods
cannot effectively solve these complex problems in cognitive intelligence.
In addition, cognitive learning of multi-agent systems shows the efficiency
of learning how to learn in a distributed way. From this aspect,
multi-agent learning, though of great research value, faces the challenges
of solving learning problems ranging from single to multiple, simplicity to
complexity, low dimension to high dimension, and one domain to other
domains.

In addition, there exist competitive or even adversarial activities in
multi-agent systems. This situation can be regarded as the agents making
more complex decisions through cognitive learning. In recent years,
scientists and engineers on antagonistic multi-agent systems have made
great breakthroughs, and the most representative ones are
AlphaGo/AlphaZero, Pluribus and AlphaStar, etc. However, there are still
limitations and challenges, including incomplete/imperfect information
environments and data/strategy generalization. How can agents autonomously
and quickly make swarm intelligent decision-making via cognitive learning
in complex environments under these circumstances? It is of great
significance to the development of various practical fields.

This special issue aims to investigate the cognitive learning in
multi-agent systems from the perspective of applications, including
practical applications including cognitive, autonomous and evolutionary
robotics, etc. All the related original researches that contribute to the
development and cognition of multi-agent systems along with their
applications are particularly welcome and encouraged.

.

*The primary list of topics (but is not limited to): * Development and
cognition of multiagent systems; Brain-inspired optimization/learning in
multi-agent systems; Federated learning/distributed learning;
Causal inference in distributed learning; Zero-shot/Few shot/No-regret
learning; Critical behavior in multi-agent systems; Meta multiagent
reinforcement learning; Multi-agent reinforcement learning in games;
Best-response and learning dynamics; Multiagent multi-armed bandits;
Cooperative-competitive multi-agent framework; Application to cognitive,
autonomous and evolutionary robotics


*Submission:* Manuscripts should be prepared according to the guidelines in
“Submission Guidelines” of the IEEE Transactions on Cognitive and
Developmental Systems in

https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=7274989.
IEEE Transactions on Cognitive and Developmental Systems | IEEE Xplore
<https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=7274989>
IEEE Transactions on Cognitive and Developmental Systems. null | IEEE Xplore
ieeexplore.ieee.org


Submissions should be done through the journal submission website:
https://mc.manuscriptcentral.com/tcds-ieee, by selecting the Manuscript
Type of “*Cognitive Learning **of Multi-Agent Systems*” and clearly marking
“Cognitive Learning of Multi-Agent Systems” in the comments to the
Editorin-Chief. Submitted papers will be reviewed by domain experts.
Submission of a manuscript implies that it is the authors’ original
unpublished work and is not being submitted for possible publication
elsewhere.


*Deadline for manuscript submissions*:   Feb 15, 2023 (extended)
*Final decision*: April 30, 2023
*Expected publication date*: August 30, 2023



*Guest Editors*

*Prof. Yang Tang, *East China University of Science and Technology, China,
tangtany at gmail.com

*Prof. Wei Lin, *Fudan University, China, wlin at fudan.edu.cn

*Prof. Chenguang Yang,* University of the West of England, UK,
cyang at ieee.org

*Prof. Nicola Gatti, *Politecnico di Milano (PoliMi), Italy,
nicola.gatti at polimi.it

*Prof. Gary G. Yen, *Oklahoma State University, USA, gyen at okstate.edu
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