Building Ontologies for Agent-Based Simulation

Abstract

Abstract. Using ontologies for simulation models construction has some advantages that cannot be underestimated. Building the ontology, a modeler has to choose conceptualization method, which significantly affects the structure and usability of resulting models. A tendency of using standard ontologies without critically estimating their applicability for particular tasks may even lead to the loss of the model's efficiency and reliability. In this work, we are considering a simple criterion which may be used to pragmatically assess applicability of particular modeling techniques for building ontologies for simulation models. We will specially focus on the temporal aspect, states and events representation methods in the model. A fragment of ontology for the city social infrastructure optimization modeling will be considered. Keywords: Ontologies modeling · Ontology assessment · Collaborative modeling IntroductionSemantic Web technologies became attractive for the implementers of agent-based simulation methods since they have emerged. Semantic Web-oriented software is providing a convenient way for digital representation of conceptual models. The further development of this idea leads to the representation of the simulation model itself in the ontological form, and building a model execution framework around the semantic data storage [11]. This approach has many advantages, among which are:─ Simplification of the information gathering from various sources. A semantic model can be used for merge heterogeneous data into a single representation. ─ Ease of the model management during its development and exploration. Adding new object types, attributes and interaction rules into semantic model is simple. It is much more flexible that the relational data oriented model. ─ The ontologies are very convenient for expressing agent behavior and interaction rules in simulation models -especially the logical behavioral patterns. ─ The reasoning software can automate rules execution during the simulation.It is natural that the use of rather complex and flexible modeling methods and information representations is producing some uneasy problems. To ensure that the use of semantic technologies will benefit modeling process and result, it is necessary to adequately construct the target model ontology, and implement it. The term