In a simulated supply chain driven by a fitted demand model, MARL pricing agents earn far higher revenue than rule-based agents while reducing fairness and stability.
Snellius: de Nationale Supercomputer
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Multi-Agent Reinforcement Learning for Dynamic Pricing in Supply Chains: Benchmarking Strategic Agent Behaviours under Realistically Simulated Market Conditions
In a simulated supply chain driven by a fitted demand model, MARL pricing agents earn far higher revenue than rule-based agents while reducing fairness and stability.