## 4 Results and Discussion
### Integration of Human Interaction into the System  
Although the multi-agent system (MAS) automates much of the port management, it is essential to allow human intervention at different levels to ensure operational flexibility and responsiveness to unforeseen events.  
Three levels of interaction were established within the system (Table 5):  
1. Supervisors They adjust orchestrator agent (EOO) parameters to modify priorities. They review alerts generated by the monitoring and optimization agent (ESO). They can approve or block critical system decisions.
2. Operators in the terminal They can modify the allocation of spaces in the field managed by the vehicle distribution agent (EDV). They intervene in the modification of routes generated by the navigation and routing agent (ENR) if there are unexpected blockages. They make adjustments to flow control agent (ECF) traffic restrictions in cases of severe congestion.
3. Terminal managers Acceevaluate performance metrics and operational efficiency.  
Among the benefits of human integration are greater flexibility in strategic decision-making, better adaptability to unforeseen events such as ship delays or congestion, and the assurance of operational supervision without relying 100% on automation.  
This integration ensures that the MAS does not replace humans but rather enhances the responsiveness and optimization of the terminal.  
Finally, the multi-agent model could be represented as shown in Figure 4.  
\begin{table}
\begin{tabular}{l l l} \hline \hline \multicolumn{1}{c}{**Entity**} & \multicolumn{1}{c}{**Permitted Human Intervention**} & \multicolumn{1}{c}{**Level of Intervention**} \\ \hline EOO (Orchestrator) & Modification of priorities and operational rules. & Supervisors \\ \hline EDV (Vehicle Distribution) & Manual reassignment of spaces in the field. & Terminal operators \\ \hline ENR (Navigation and Routing) & Route adjustment and unlocking of closed areas. & Terminal operators \\ \hline ECF (Flow Control) & Application of restrictions or release of roads. & Terminal operators \\ \hline ECE (Shipping Coordination) & Rescheduling of boarding times. & Supervisors and managers \\ \hline ESO (Monitoring and Optimization) & Analysis and redefinition of strategies. & Terminal managers \\ \hline \hline \end{tabular}
\end{table}
Table 5: Human interaction by agent.  
Figure 4 illustrates the communication flow and functional dependencies among the intelligent agents defined in the proposed MAS architecture. The orchestrator agent acts as the central coordinator, receiving and distributing information to all other agents. Vehicle distribution, navigation, and routing agents interact closely to define optimal parking locations and internal routes. Flow control manages congestion based on routing outputs and relays restrictions to shipping aoordination, which schedules boarding accordingly. Monitoring and optimization collects performance indicators from all agents and provides system-level feedback to both the orchestrator and other agents, enabling adaptive behavior. The diagram highlights not only bilateral communication but also vertical dependencies, where decisions by downstream agents depend on the orchestration and data consolidation performed at higher levels. This structure enables scalable coordination across operational layers of a Ro-Ro terminal.