MSIAAS@SCSC'17 2017 - Modeling and Simulation of Intelligent, Adaptive and Autonomous Systems Track held at the 49th Summer Computer Simulation Conference (SCSC 2017)

Website http://scs.org/summersim/ | Edit Freely

Category complexity; modeling; autonomous systems; IoT; multi-agent systems; self-*

Deadline: February 20, 2017 | Date: July 09, 2017-July 12, 2017

Venue/Country: Bellevue, Washington, U.S.A

Updated: 2017-02-02 22:19:41 (GMT+9)

Call For Papers - CFP

- held at the 49th Summer Computer Simulation Conference (SCSC 2017)

- July 9-12, 2017

- Bellevue, Washington, US

- http://scs.org/wp-content/uploads/2016/01/CFP_MSIAAS-v2.pdf

=== TRACK DESCRIPTION ===

The increasing popularity of the Internet of Things, or IoT metaphor emphasizes that heterogeneous

systems are the norm today. A system deployed in a netcentric environment eventually becomes a part

of a system of systems (SoS). This SoS also incorporates adaptive and autonomous elements (such as

systems that have different levels of autonomy and situated behavior). This makes design, analysis

and testing for the system-at-hand a complex endeavor in itself.

Testing in isolation is not the same as a real-system operation, since the system’s behavior is also

determined by the input, which evolves from the environment. This exact factor is difficult to

predict, due to an ever-increasing level of autonomy. Advanced Modeling and Simulation (M&S)

frameworks are required in order to facilitate SoS design, development, testing, and integration.

In more particular, these frameworks have to provide methods to deal with intelligent, emergent, and

adaptive behavior as well as autonomy.

The subject of emergent behavior and M&S of emergent behaviors takes the center stage in such systems

as it is unknown how a particular system responds in the face of emergent behavior arising out of

interactions with other complex systems. Intelligent behavior is also defined as an emergent property

in some complex systems. Consequently, systems that respond and adapt to such behaviors may be called

intelligent systems as well.

This track has two objectives.

The first objective aims to focus on M&S of the following aspects of complex SoS engineering and

brings researchers, developers and industry practitioners working in the areas of complex, adaptive

and autonomous SoS engineering that may incorporate human as an integral part of SoS operations.

This objective covers the following topics:

- Theory for adaptive and autonomous systems

- Intelligence-based systems

- Computational intelligence and cognitive systems

- Human-in-the-loop systems

- M&S Frameworks for intelligent behavior

- Methodologies, tools, and architectures for adaptive control systems

- Knowledge engineering, generation and management in IAAS

- Weak and Strong emergent behavior, Emergent Engineering

- Complex adaptive systems engineering

- Self-* (organization, explanation, configuration) capability and collaborative behavior in IAAS

- Applications to robotics, unmanned vehicles systems, swarm technology, semantic web technology, and

multi-agent systems

- Netcentric IAAS

- Live, Virtual and Constructive (LVC) environments

- Simulator design for IAAS systems

- Modeling tools for IAAS design

- Modeling, engineering, testing and verification of complex behavior

- Development and testing of complex and distributedsystems

- Modeling, simulating, and testing IoT environments and applications

The second objective is to advance the science of complexity as applicable in M&S discipline.

Complexity is a multi-level phenomenon that exists at structural, behavioral and knowledge levels in

such SoS. Emergent behavior is an outcome of this complexity. Understanding emergent behavior as an

outcome of this complexity will provide foundation for resilient intelligent systems. Following are

some of the topics related to this objective, but not limited to:

- Complexity in Structure: network, hierarchical, small-world, flat, etc.

- Complexity in Behavior: Micro and macro behaviors, local and global behaviors, teleologic and

epistemological behaviors

- Complexity in Knowledge: ontology design, ontology-driven modeling, ontology-evaluation, ontology

transformation, etc.

- Complexity in Human-in-the-loop: artificial agents, cognitive agents, multi-agents, man-in-loop,

human-computer-interaction

- Complexity in intelligence-based systems: Situated behavior, knowledge-based behavior, memoic

behavior, resource-constrained systems, energy-aware systems

- Complexity in adaptation and autonomy

- Complexity in architecture: Flat, full-mesh, hierarchical, adaptive, swarm, transformative

- Complexity in awareness: Self-* (organization, explanation, configuration)

- Complexity in interactions: collaboration, negotiation, greedy, rule-based, environment-based, etc.

- Complexity in Live, Virtual and Constructive environment

- Complexity in Artificial Systems, Social systems, techno-economic-social systems

- Complexity in Model Engineering of complex SoS

- Complexity in Model Specification using modeling languages and architecture frameworks such as UML,

PetriNets, SysML, DoDAF, MoDAF, etc.

- Complexity in Simulation environment engineering: distributed simulation, parallel simulation,

cloud simulation, netcentric parallel distributed environments

- Complexity in Testing and Evaluation tools for SoS engineering

- Complexity in Heterogeneity: Hardware/Software Co-design, Hardware in the Loop, Cyber Physical

Systems, the Internet of Things

- Metrics for Complexity design and evaluation

- Verification, validation and accreditation of Complexity in SoS

- Application of Complexity aspects in domain engineering: Financial, Power, Robotics, Swarm,

Economic, Policy, etc.

- SoS Failure due to Complexity

=== Important Dates ===

Paper Submission: February 20, 2017

Author Notification: May 1, 2017

Submission of Work in Progress (SCSC-WIP) Papers: May 5, 2017

Notification of Work in Progress: May 10, 2017

Camera-ready Paper: May 14, 2017

=== Track Chair(s) ===

Saurabh Mittal, MITRE Corporation (smittalmitre.org)

Jose L. Risco Martin, Universidad Complutense de Madrid (jlriscoucm.es)

Marco Lützenberger, DAI-Lab, TU Berlin, Germany (marco.luetzenbergerdai-labor.de)

Claudia Szabo, University of Adelaide, Australia (claudia.szaboadelaide.edu.au)

=== Submission Guidelines ===

Original and high-quality technical papers are solicited for review, possible presentation and

subsequent publication in the conference proceedings. For further instructions, please refer to the

Submission Instructions in the SCS Conference Proceedings Management System web site. Contributed

papers should be 5 to 12 pages long. They will be peer reviewed and – if accepted and presented at

the conference submitted to the ACM Digital Library. Papers must not have appeared before (or be

pending) in a journal or conference with published proceedings, nor may they be under review or

submitted to another forum during SummerSim’17 review process. At least one author of an accepted

paper must register for the symposium and must present the paper at the symposium. For author

guidelines on how to submit a paper, see: http://scs.org/authorskit/