Machine Learning and AI in Simulation (MLAIS)

Machine Learning and AI in Simulation (MLAIS)

Track chairs

Modeling and Simulation (M&S) have made significant strides in enhancing our understanding of complex systems, improving the ability to predict future states, and enabling the development of (near-)optimal interventions and policies across diverse domains. With the rapid advancements in artificial intelligence and machine learning (AI/ML), there is now unprecedented potential to optimize simulation parameters, train agent behaviors dynamically, and adapt simulation environments through real-time observations and evolving data. The goal of this track is to expand the horizons of human knowledge by integrating the latest AI/ML technologies with M&S.

This Machine Learning and AI in Simulation (MLAIS) track provides a dedicated platform to share insights, research methodologies, and applications that address the intersection of AI/ML and M&S. It focuses on exploring how cutting-edge AI/ML techniques such as knowledge reasoning, computer vision, natural language processing, deep learning, and reinforcement learning can enhance Modeling and Simulation practices and, conversely, how Modeling and Simulation can be leveraged to advance AI/ML solutions. We invite full papers (up to 12 pages) presenting original research on the use of AI/ML in Modeling and Simulation, as well as interdisciplinary work that pushes the boundaries of both fields. Oral presentations will be the format for this track, fostering dynamic discussions around innovative ideas and findings. Topics of interest include, but are not limited to:

  • Enhancing validation and verification (V&V) processes with AI and ML
  • AI/ML techniques for training and evolving autonomous agents within simulations
  • Best practices for the convergence of AI, ML, and simulation
  • Using M&S to generate synthetic data for training AI/ML models
  • Empirical evaluations of state-of-the-art AI/ML methods in M&S
  • Facilitating experimentation and simulation optimization using AI/ML
  • Using M&S as a tool to advance AI/ML research and solutions
  • Developing simulation modeling tools and methodologies that integrate AI/ML
  • Visionary approaches for the future of AI/ML in simulation

This track aims to explore and uncover the full potential of AI/ML in driving the next generation of M&S innovations.