We explore the macro-financial consequences of the disruption of a supply chain in an agent based framework characterized by two networks, a credit network connecting banks and firms and a production network connecting upstream and down-stream firms. We consider two scenarios. In the first one,...

We apply Multi-Agent Deep Reinforcement Learning (MADRL) to inventory management problems with multiple echelons and evaluate MADRL's performance to minimize the overall costs of a supply chain. We also examine whether the upfront-only information-sharing mechanism used in MADRL helps alleviate...

After land prices in Germany increased continuously since 2006, policy makers, representatives of farmers' unions, NGOs, and farmers started and continued to discuss or propose new land market regulations to stop price increases and to protect particularly smaller farmers. In this paper we...

This contribution addresses the impact of high-frequency electronic liquidity provision strategies on financial markets' intraday dynamics, by evaluating the interaction between multiple trading strategies within a computer laboratory, i.e. an artificial stock market. Initially, a realistic...