# Linked Data Aware Agent Development Framework for Mobile Devices
## 2 Architecture of LDAF-M
### Agency Layer  
The agency layer in LDAF-M framework is based on the Belief-Desire-Intention (BDI) architecture. BDI is a model of agency which has been widely used in the development of agents and multi-agent systems, including commercial agent software. Hence, the design and implementation of the basic modules in this layer are inevitably similar with the existing BDI supported agent frameworks. On the other hand, the main difference of LDAF-M is that it can obtain knowledge from linked data resources and handle the obtained knowledge. In this regard, new functionalities and internal constructs has been added to a standard BDI implementation. These variations are explained in Section 3, where linked data support is discussed. The BDI architecture's origins lie in the theory of practical reasoning [23] developed by [PERSON]. As stated in Reference [22], this kind of reasoning is always directed towards doing an action and consists of two activities. The first activity is deliberation which is about deciding what state of affairs the agent wants to achieve. The second activity is means-ends reasoning (planning) and it decides how to achieve those selected state of affairs using an available set of actions. Practical reasoning is realized in agent systems based on the concepts of beliefs, desires and intentions. This is why these architectures are called BDI architectures. Everything that an agent knows and believes about the world in which it is located, including itself and also other agents around it, is represented by the belief component within the BDI architecture. Agents obtain their beliefs by continuously perceiving the environment in which they operate. The motivational stance of an agent is represented by the desire component located within the BDI agent architecture. The desire concept characterizes the goals of an agent which define what the agent wants to achieve. In other words, desires are the possible options of an agent [14; 21; 22; 28]. At the end of the deliberation mechanism, desires which are adopted by an agent become intentions. This means that the adopted desire would lead to an action. In this regard, during the process of identifying the actions that an agent will perform, the intention component within the BDI agent architecture has a much stronger role than the desire component. An agent may host many desires which can possibly be transformed into intentions and then to actions in the near future. The agent evaluates desires in terms of agent's beliefs, other desires and intentions, and then suitable desires are adopted as intentions that would lead to actions. In LDAF-M, beliefs may come from the environment in which the agent runs, or from the linked data environment. The messages delivered from other agents may also cause the beliefs of an agent to be updated. The ability to obtain its beliefs from the linked data environment (e.g., from interrelated RDF documents) is the distinguishing feature of LDAF-M. The beliefs are used in option generation together with the current intentions to produce desires. The filter function uses beliefs, desires and intentions to produce new intentions. The filter component has a typical rule base which is used in determining which goals to adopt. Primarily, the beliefs in the active state at the belief base are processed using this rule base. Then the filter component determines what goals to adopt by matching the beliefs in the active state and the rules defined in its own context. Since an intention is directed towards an action, the related actions corresponding to an intention are executed next. Basic components of the BDI architecture that are implemented in LDAF-M are shown in Figure 4.  
In fact, desire and intention which is a strong form of desire are similar notions, and in the implementation of BDI architectures they are represented by the \"goal\" concept. An agent may have many goals (i.e., desires) and the adopted goals are its intentions.