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Port logistics is characterised by a high degree of fragmentation, uncertainty and complexity. In a context with these characteristics, decision support can be of significant value. This study presents the prototype of an intelligent decision support system (DSS) that leads to horizontal and vertical cooperation among freight agents involved in port logistics. A multi-agent simulation model is presented where heterogeneous actions are enabled as a result of an adaptive reinforcement learning algorithm that is inspired by human decision-making strategies. The model combines optimisation modelling and decision theory to operate in a dynamic environment characterised by information asymmetry among agents and dynamic changes over time. A simulation demonstrates the dynamics and convergence to equilibrium of the interactions of heterogeneous agents for delivery and pick up of import/export shipments.

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