The workshop will comprise three tracks:
Foundational AI Agent Technologies for Energy Systems
This track focuses on the fundamental AI methodologies powering the next generation of energy agents, including reinforcement learning, multi-agent systems, knowledge representation, and reasoning capabilities specific to energy domain challenges. Sessions will cover advances in agent architectures that enable real-time autonomous decision-making while maintaining human oversight, explainability, and alignment with safety requirements critical for energy infrastructure.
Digital Twin Integration and Simulation Environments
The second track explores the synergy between AI agents and digital twins across the energy sector. Topics include high-fidelity modeling of energy assets, real-time data integration techniques, physics-informed neural networks, and simulation environments that enable agents to train safely before deployment. Special emphasis will be placed on bridging the reality gap between simulated and physical energy systems.
Applications and Case Studies in Energy Dominance
The final track showcases real-world implementations and case studies where AI agents coupled with digital twins are advancing energy security and efficiency. Sessions will highlight applications in grid optimization, energy storage management, nuclear facility operations, critical infrastructure protection, cybersecurity, and energy market optimization. Demonstrations will illustrate how these technologies collectively contribute to energy dominance by enhancing reliability and resilience, efficiency, and safety and security.