The model MAS4AT described in chapter 3 has been designed to be generic and adaptive to any surveillance systems as long as prerequisites are fulfilled: entity representation and numerical events representation. In this section, we describe the adaptation of MAS4AT for the BEhaviour ANalysis (BEAN) component of the project I2C. In the end, we explain how the changes made are not impacting the generic model or its running.
In I2C, there is a distinction between the supervised ships, and what can happen on them. The operators are able to intervene on the representation of the ships, in order to add or modify an information, to trigger or remove an alert, an so on. On the contrary, the rules and the subsequent events are internal to the component Behaviour Analysis and can only be modified by experts. In order to cope with this need, the agents in MAS4AT have been separated into two different multi-agent systems: the Operative Multi-Agent System (OpMAS) and the Parameter Multi-Agent System (PaMAS).
OpMAS is composed by the entity-agents and has the role of the ship representation and the computation of their behaviours while PaMAS represents the events and is able to learn their values according to the feedbacks from the operator. The new architecture of MAS4AT is shown in figure 4.4. This separation does not change the communication nor the relationships between the agents. It only allows a better optimisation of each part.
4.3.1 The Operative Multi-Agent System (OpMAS)
OpMAS is the multi-agent system within MAS4AT for I2C that is in charge of the representation of the ships in the monitored area and the alert triggering. Thus, OpMAS is composed of entity-agents which are here called ship-agents to be closer to the supervised entities. The appellation Entity Behaviour Value has been modified alike in Ship Behaviour Value. The changes of names are the only difference between the agents in OpMAS and the
Figure 4.4: Architecture of MAS4AT in the system I2C.
agents in the generic MAS4AT.
OpMAS also integrates a software component, called the Agent manager, whose role is to act as an interface between the operators and the system MAS4AT. On the one hand, the agent manager receives the alerts from a given ship-agent and sends it to the operator of I2C. On the other hand, the agent manager receives the feedbacks from the operator and the events from the rule engine and transmits them to the concerned ship-agent.
The operation of the ship-agents is the same than the entity-agents. Each ship agent is able to compute a numerical value, its Ship Behaviour Value according to the function 4.3.
SBV =
∑
n i=1(Init(ei) ×nb(Init, ei)
+ (Incr(ei) ×nb(Incr, ei) − (Decr(ei) ×nb(Decr, ei) (4.3) For each event received for the ship-agent, the SBV is computed according the weight of the three parameters Init, Incr and Decr and the values given by the related event-agents ei.
In a row, the Ship Behaviour Value represents the behaviour of a ship as the combination of several events of various importance, given by the value of the parameters. The higher is the result, the more suspicious is the behaviour of the ship. The figure 4.5 shows an example of the combination of different events happening on a given ship-agent.
Finally, for each time step, the ship-agents update the weights of the events involved in the computation of their SBV and trigger alerts when it is necessary. The time step unit in I2C is the duration of the interval between two updates of the Common Operational Traffic Picture.
Figure 4.5: Event Value Combination.
Figure 4.6: MAS4AT Learning Example for I2C.
4.3.2 The Parameter Multi-Agent System (PaMAS)
PaMAS is the multi-agent system within MAS4AT for I2C which is in charge of the representation of the events. According to the model in section 3.3.2, PaMAS contains event-agents composed of three parameter-event-agents each.
Their role is to value the events that are happening on the ship and send these values to the ship-agents when asked to do so. They are also able to perform a self-tuning in order to learn the values of the parameters according to the operator feedbacks. The figure 4.6 illustrates the result of the learning process.
The only difference between the generic model and I2C is that the events represented by the event-agents comes from the rule engine which performs a preprocessing of what happened in the monitored environment. It means that the rule engine can send anomalies to MAS4AT. These anomalies are taken into account as events by the ship-agents and are thus represented as event-agents. This can lead to events that are automatically trigger an
alert, for example on a ship that is blacklisted by the authorities because known to practice illegal fishing.
Ultimately, each ship-agent is able to give an accurate behaviour value and to represent each situation by an inequality compared with an alert threshold. Except for the refactoring of the agent names and the separation into two different multi-agent systems, OpMAS and PaMAS, the system MAS4AT used in I2C corresponds to the generic model presented in chapter 3.