Reinforcement learning (RL) has emerged as a powerful tool for addressing complex
decision making problems in various domains, including aviation. This paper provides a …

Reinforcement Learning (RL) techniques are being studied to solve the Demand and
Capacity Balancing (DCB) problems to fully exploit their computational performance. A …

Reinforcement learning (RL) techniques are under investigation for resolving conflict in air
traffic management (ATM), exploiting their computational capabilities and ability to cope with …

Reinforcement learning (RL) techniques have been studied for solving the conflict resolution
(CR) problem in air traffic management, leveraging their potential for computation and ability …

Monte-Carlo tree search (MCTS) is a widely used heuristic search algorithm. In model-
based reinforcement learning, MCTS is often utilized to improve action selection process …

This paper explores the optimization of Ground Delay Programs (GDP), a prevalent Traffic
Management Initiative used in Air Traffic Management (ATM) to reconcile capacity and …

Since flight delay hurts passengers, airlines, and airports, its prediction becomes crucial for
the decision-making of all stakeholders in the aviation industry and thus has been attempted …

In domains where a high-level strategy must be developed to achieve a vision of a future
state, there is risk inherent in the selection and implementation of a strategy. Within domains …

The field of reinforcement learning has been growing for the past ten years. Most significant
algorithms use one or more prediction models as policy function. In the dissertation thesis …