Ngā tūemi rite

• AI2STOW: End-to-End Deep Reinforcement Learning to Construct Master Stowage Plans under Demand Uncertainty
  mā: Van Twiller, Jaike, me ētahi atu.
  I whakaputaina: (2025)
• An Efficient Integer Programming Model for Solving the Master Planning Problem of Container Vessel Stowage
  mā: van Twiller, Jaike, me ētahi atu.
  I whakaputaina: (2024)
• Risk-Aware Decision Making in Restless Bandits: Theory and Algorithms for Planning and Learning
  mā: Akbarzadeh, Nima, me ētahi atu.
  I whakaputaina: (2024)
• Fair Resource Allocation in Weakly Coupled Markov Decision Processes
  mā: Tu, Xiaohui, me ētahi atu.
  I whakaputaina: (2024)
• A Benchmark Study of Deep Reinforcement Learning Algorithms for the Container Stowage Planning Problem
  mā: Huang, Yunqi, me ētahi atu.
  I whakaputaina: (2025)