Modeling and Simulation of Intelligent, Adaptive and Autonomous Systems Track
When : 2017-07-09
Where : Washington, US
Submission Deadline : 2017-02-20
Categories : Internet Computing , Artificial Intelligence
Modeling and Simulation of Intelligent, Adaptive and Autonomous Systems Track (MSIAAS 2017)
July 9-12, 2017, Washington, US
Call for Papers:
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 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
User Name : shaun
Posted 03-02-2017 on 15:54:14 AEDT
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