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In this paper, we present a multi-agent system for planning and plan execution monitoring in a real-time railroad transportation scenario. The planning process is implemented as incremental anytime algorithm that is capable of integrating new task specifications in the ongoing planning and plan execution process. An initial solution is obtained by executing the contract-net protocol for every new task, the resulting solution is then optimized by a simulated trading approach. The execution of the resulting plans is monitored by a plan execution monitor that dynamically controls ongoing driving or coupling activities of transportation units and that handles deviations from the original plan in the case of external events, e.g. location route failures or train delays.

Transportation Scheduling and Simulation in a Railroad Scenario: A Multi-Agent Approach