3 papers
Relational Multi-Agent Reinforcement Learning for Dynamic Pricing in High-Speed Railway Markets
Enrique Adrian Villarrubia-Martin, David Muñoz-Valero, Luis Rodriguez-Benitez +2
In liberalised railway systems, operators must set prices dynamically in an environment with partial observability, as they retain private information about their objectives and pe…
Uncertainty-Based Smooth Policy Regularisation for Reinforcement Learning with Few Demonstrations
Yujie Zhu, Charles A. Hepburn, Matthew Thorpe +1
In reinforcement learning with sparse rewards, demonstrations can accelerate learning, but determining when to imitate them remains challenging. We propose Smooth Policy Regularisa…
Dynamic Pricing in High-Speed Railways Using Multi-Agent Reinforcement Learning
Enrique Adrian Villarrubia-Martin, Luis Rodriguez-Benitez, David Muñoz-Valero +2
This paper addresses a critical challenge in the high-speed passenger railway industry: designing effective dynamic pricing strategies in the context of competing and cooperating o…