Notification Date: TBA
Session Co-ChairsAlberto Falcone University of Calabria, Rende, Italy Danielle Azar Lebanese American University, Byblos, Lebanon
Goals of the Session
Modeling and Simulation (M&S) is one of the most important and effective methods for designing and studying complex systems in a variety of industrial and scientific domains such as biology, energy, and aerospace. M&S methods, models, and techniques allow the effective analysis and evaluation of different design alternatives by avoiding risks, costs, and failures associated with extensive field experimentation. These aspects are crucial when exhaustive real-world testing is not possible due to geographic distribution of system’s components, security, cost, and time issues.
This special session focuses on general aspects and specific research results on Artificial intelligence (AI) approaches to support M&S and Distributed and Real-Time Simulation (DRTS), and vice versa. Specifically, the special session aims at: (i) presenting the current state-of-the-art about M&S and DRTS infrastructures and frameworks based on open standards, recent extensions, and innovations related to AI technologies; (ii) identifying research directions and technologies that will drive innovations in M&S and DRTS by adopting AI, Machine Learning (ML) and Meta-Heuristics (MH) techniques, and (iii) adopting M&S and DRTS techniques to formalize and study AI environments and services.
Topics of interest include, but are not limited to:
- High-performance distributed simulation through AI approaches
- Performance and Scalability Analysis through AI and ML techniques
- AI, ML, and MH approaches for designing Parallel and Distributed simulations
- Distributed simulation for accelerating AI, ML and MH approaches for solving complex problems.