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Notes on dynamic pricing
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Relational Multi-Agent Reinforcement Learning for Dynamic Pricing in High-Speed Railway Markets
Researchers propose a new approach for dynamic pricing in liberalized railway systems using Relational Multi-Agent Reinforcement Learning (RL). The method models the environment as a graph, process features of entities…
Dynamic multi-agent deep reinforcement learning-based pricing and incentivization approach in multimodal transportation networks
A research paper proposes a multi-agent deep reinforcement learning framework to address challenges in multimodal transportation systems, particularly regarding shared mobility services (SMSs) demand concentration and…
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