Special Session on AI–driven methods for Multimodal Networks and Processes Modeling (AIMPM)

Scope

The special session entitled AI–driven methods for Multimodal Networks and Processes Modeling (AIMPM 2024) is a forum that will share ideas, projects, researches results, models, experiences, applications etc. associated with artificial intelligence solutions for different multimodal networks born problems (arising in transportation, telecommunication, manufacturing and other kinds of logistic systems). The session will be held in Salamanca as the part of The 21st International Symposium Distributed Computing and Artificial Intelligence 2024.

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Topics

Recently a number of researchers involved in research on analysis and synthesis of Multimodal Networks devote their efforts to modeling different, real-life systems. The generic approaches based on the AI methods, highly developed in recent years, allow to integrate and synchronize different modes from different areas concerning: the transportation processes synchronization with concurrent manufacturing and cash ones or traffic flow congestion management in wireless mesh and ad hoc networks as well‏ as an integration of different transportations networks (buses, rails, subway) with logistic processes of different character and nature (e.g., describing the overcrowded streams of people attending the mass sport and/or music performance events in the context of available holiday or daily traffic services routine). Due to the above mentioned reasons the aim of the workshop is to provide a platform for discussion about the new solutions (regarding models, methods, knowledge representations, etc.) that might be applied in that domain. There is a number of emerging issues with big potential for methods of artificial intelligence (evolutionary algorithms, artificial neural networks, constraint programming, constraint logic programming, data-driven programming, answer set programming, hybrid methods - AI/OR-Operation Research, fuzzy sets) like:

• multimodal processes management,
• modeling and planning production flow,
• production planning and scheduling, 
• stochastic models in planning and controlling, 
• simulation of discrete manufacturing system, 
• supply chain management, 
• robust resource planning and scheduling,   
• proactive and reactive approach to manufacturing and distribution processes, 
• mesh-like data network control, 
• multimodal social networks, 
• intelligent transport and passenger and vehicle routing, 
• security of multimodal systems, 
• network knowledge modeling, 
• intelligent web mining & applications, 
• business multimodal processes and projects planning. 

Contributions containing of both: the theoretical and practical results obtained in this area are welcome.