# A Regional Multi-Agent Air Monitoring Platform
## 4 The ACreM Platform
### Air Monitor Agent  
The Air Monitor (AM) is a personal assistant that is designed to identify and locate various anomalies related to the state of the air based on our measurements. AM was developed as a BDI (Beliefs-Desires-Intention) agent in the JaCaMo development environment [29]. The BDI model has its roots in the philosophical tradition for understanding practical reasoning in humans. Practical reasoning is action-oriented--a process of seeking what to do. A practical deliberation is a matter of weighing conflicting considerations for and against competing options dependent on the desires, concerns, or value judgments of the agent [30]. As a process, practical reasoning involves two distinct activities. The first one, known as deliberation, is deciding what state of affairs (goal) we want to achieve. The second, called planning, is deciding how to achieve that state of affairs (that goal). One of the advantages of this architecture is the ability to flexibly represent and work with the agent's environment, which is essential for our goals. Another advantage is that AM works with verified expertise for our application domain of interest (in this case air pollution). This circumstance is at the same time a disadvantage of the ReAct agent, which also works with free text created by non-professionals such as journalists, politicians, and interested citizens. Thus, we are of the opinion that combining the two approaches is an adequate way to achieve the aim of the study, namely the search for reliable information about the air situation in Plovdiv. At the same time, we want to demonstrate and explore the power of the integration of methods from the two main areas of artificial intelligence. Along with this, we want to show a concrete example that demonstrates the advantages of integrated artificial intelligence. Figure 9 shows the general architecture of AM situated in its working environment. The diagram presents the main components of the AM and its environment. Figure 8: ACreM platform architecture. The Beliefs Base is a discrete structure that models an agent's perception of its environment. Individual beliefs are represented as predicates (in the style of the Prolog logic programming language). The structure consists of two base components, static and dynamic (Figure 9). The static component contains parameters with immutable values (usually threshold and limit values) used to estimate the air condition and the type of pollutants. This component is initialized by interacting with the Air Pollution Ontology, from which the necessary parameters are extracted. The dynamic component models the current air status. The values of the dynamic parameters are extracted from the Sensor DB, which contains hot data from the actual measurements. Any change to the Beliefs Base (deleting or adding a belief) triggers an actual event and updates at a predefined time interval. A sample Beliefs Base segment is given in Figure 10.  
The Plan Library (Figure 11) stores AM plans, each following a three-component structure: triggering_event: context \(<\)- body, where: and \(<\)-serve as separators. Updates to the AM's beliefs or intentions--either additions (+) or deletions (\(-\))--are modeled through events. Belief-changing events occur when the AM updates its beliefs based on new perceptions of the environment. Intention-changing events (i.e., adding intentions) typically result from executing other plans. Contexts determine when a plan is applicable to the agent. Since the agent operates in a dynamic environment, contexts help delay commitment to a specific action until the latest possible moment. Thus, when selecting a plan to achieve a goal, the context ensures that a plan with the highest probability of success is chosen. The body of the plan contains a series of executable actions, separated by \",\". A plan may include subgoals, which are achieved using separate plans. Plan continuation requires that corresponding subgoals are met (i.e., the associated subplans are completed).