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The 4th IEEE International Workshop on Distributed Intelligent Systems
(DistInSys 2024)

Paris, France - June 26th, 2024

https://fcrlab.unime.it/calls/distinsys2024

in conjunction with the 28th IEEE Symposium on Computers and
Communications (ISCC 2024)

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MISSION:
The digital environment is, nowadays, populated by sensing devices that are ubiquitous,
strongly interconnected, and heterogeneous. The vision of a large ecosystem of machines
that can cooperate in solving articulated tasks is becoming realistic day by day.
Teams of agents, sensors, and robots are ever more capable to sense the environment,
process the gathered information, and act in structured and unstructured scenarios,
even in space and harsh environments.

To deal with complexity and a large amount of produced data,
it is necessary to decompose systems into smaller, distributed, efficient, intelligent,
and autonomous units responsible for local decision-making and control,
let them explore knowledge stored locally and communicate among themselves only when needed.
That solutions opens issues when discussing the systems design, data, and knowledge exchange,
analysis of proper and optimal coupling of system parts as well as integration of subsystems,
introducing a completely diverse nature into the overall framework.

Given the depth of interests and applications, we invite all interested researchers,
scientists and engineers to take part in DistInSys 2024

TOPICS
Papers are solicited in all areas of Distributed Intelligent Systems, including,
but not restricted to:
- Machine Learning Methods for Multi-Agent Systems
- Distributed Architecture for Machine Learning
- Middleware for Distributed Learning and their applications
- Distributed Learning for Remote Sensing
- Distributed Learning for Satellite and Space Applications
- Distributed Learning for Autonomous Vehicles
- Federated Learning methods and applications
- Federated Reinforcement Learning
- Deep Learning for Distributed Systems Applications
- Deep Learning for Vision and Image Processing
- Knowledge Representation Methods for Distributed Learning Systems
- Knowledge Distillation and Quantization for Distributed Learning Systems
- Remote Sensing for Environmental Monitoring
- Internet of Autonomous Things
- Distributed Cooperative Perception, Action and Planning
- Distributed Decision Making
- Multi-Agent and Swarm Robotics
- Autonomous Systems, Vehicles, and Drones
- Sensor and Actuator networks
- Wireless and Robotic Sensor Networks
- Cloud Multi-Robot Systems
- Ambient Intelligence
- Distributed Cyber-Physical Systems
- Mobile, Pervasive, and Ubiquitous Computing
- Hyperdistributed Applications in the Cloud Continuum
- Trustworthy and verifiable distributed systems
- Societal/economic/ethical/regulatory/educational considerations for
distributed autonomous robotic systems

IMPORTANT DATES:
- Full-length paper submission: Apr 28, 2024
- Author notification: May 10, 2024
- Camera-ready: May 20, 2024
- Conference registration: May 15, 2024
* Each deadline expires at 23:59:59 EEST

PAPER SUBMISSION:
In order to download manuscript templates for IEEE conference proceedings,
use the following link:
https://www.ieee.org/conferences/publishing/templates.html.
Papers can be submitted directly to EDAS: https://edas.info/newPaper.php?c=32200

Note that accepted papers up to 6 pages will be published with no additional
charge. Exceeding pages will be charged an additional fee. Papers exceeding
7 pages will not be accepted. At least one author of each accepted paper is
required to register to the conference and present the paper. Only registered
and presented papers will be published in the conference proceedings. Accepted
papers will be included in the ISCC 2024 proceedings and will be submitted for
inclusion to IEEE Xplore. The ISCC proceedings have been indexed in the past by
ISI, DBLP and Scopus. This makes the ISCC conference one of the publication
venues with very high visibility and impact in both Computer and
Communications areas.

Please visit https://fcrlab.unime.it/calls/distinsys2024 for more information.

Kind regards,
DistInSys Organization
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