Session 1 — 10:00–11:30 AM EDT
TUT::QGDD::QTEM::359 – RL-QAS: Reinforcement learning for quantum architecture search | Session 1

• 10:00–10:45 – Introduction to RL-QAS
  Motivation, problem formulation, states/actions/rewards, and example architectures.
• 10:45–11:30 – Hands-on coding I
  Building the RL-QAS environment and running a first agent on small quantum circuits.

Session 2 — 1:00–2:30 PM EDT
TUT::QGDD::QTEM::359 – RL-QAS: Reinforcement learning for quantum architecture search | Session 2

• 1:00–1:45 – Hands-on coding II
  Continued experiments, hardware-aware constraints, and performance analysis.
• 1:45–2:30 – Advanced RL-QAS & future directions
  Advanced methods, open research questions, and future opportunities in RL-QAS.