# Linked Data Aware Agent Development Framework for Mobile Devices
## 1 Introduction
Thus, the number of real-life semantic web applications has begun to increase with the introduction of linked data. On the other hand, although the close relationship has been emphasized from the very beginning, in practice there has been little collaboration between agent and semantic web/linked data communities. In this paper, we introduce the agent development framework that we have developed for mobile devices. Using this framework, developers can build intelligent agents that have the attributes of social ability, reactivity, proactivity, and autonomy. The main contribution of the presented framework is its linked data support. Linked data support in an agent simply corresponds to the ability to supply its beliefs from the linked data environment, to keep the obtained beliefs internally, and use those beliefs during planning process. By providing linked data support, we also aim to contribute to the establishment of the links between agents and the linked data environment. Since the ability to supply its beliefs from the linked data environment is the developed agent framework's distinguishing feature, we called it Linked Data Aware Agent Development Framework for Mobile Devices (LDAF-M). The belief component of LDAF-M uses the Resource Description Framework (RDF) model to represent the beliefs of an agent and provides a graph data structure to hold the beliefs internally. By this way, semantic data stored in ontologies as well as in open data stores, such as Freebase or DBpedia in the linked data environment, can be used to represent an agent's beliefs. Linked data support, which is the distinguishing property of LDAF-M, makes it the first linked data aware agent framework for mobile devices to the best of our knowledge. LDAF-M agents can be qualified as intelligent agents according to the definition of [PERSON] [2], since they support the attributes of autonomy, reactivity, proactivity, and social ability. Social ability is related to the ability of an agent to exchange agent communication language messages with others in the system. Social ability is provided through the LDAF-M communication infrastructure. Reactivity is the ability to respond to the changes in the environment, and proactivity is related to exhibiting goal directed behavior. Reactivity and proactivity are satisfied through the use of the BDI model of agency [14]. Finally, autonomy is satisfied through the use of a planner within the context of the BDI architecture. Communication infrastructure and the agency layer are discussed in detail in Section 2, where the architecture of LDAF-M is given. On the other hand, some highlights related to the communication infrastructure, standards followed during the development, and BDI model of agency are given below. Support for peer-to-peer (P2P) paradigm: In the communication layer, LDAF-M provides a P2P based communication and resource sharing infrastructure where each mobile device behaves as a peer. The P2P infrastructure provided by LDAF-M also includes a mechanism that can detect a peer that becomes offline due to a problem and can handle this situation so that the system continues to operate seamlessly. FIPA compliant execution platform: FIPA (Foundation for Intelligent Physical Agents) is an IEEE Computer Society standards organization that issues a set of specifications which intend to promote interoperability among heterogeneous agent systems [20]. LDAF-M provides a FIPA compliant platform for mobile device agents. Jade LEAP and AFME also support FIPA standards. On the other hand, during the design of LDAF-M, we have made slight modifications which are discussed in Section 2.2. Support for BDI model of agency: Belief-Desire-Intention (BDI) model of agency [14; 21; 22] is a framework for describing the behavior of agents in terms of their beliefs, desires (options) and intentions (adopted options). This model of agency draws its inspiration from practical reasoning which is a model of decision making proposed by [PERSON] [23].