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Ontology-Based Simulation and Qualification of Buildings

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In Proc. of 2èmes Journées des Jeunes Chercheurs de l'UTBM (IngéDoc 2012), Doceo, UTBM, UTBM Press, 2012.
Poster Session. Multiagent-based simulation is now a common tool in various application domains to assess/validate different use-case scenarios: social sciences, urban management, transport, building security assesment, etc. The idea is to develop realistic virtual environment to test particular domain-specific procedures. Develop realistic scenarios implies that they must be non- deterministic and agents inhabiting virtual environments are autonomous and intelligent. The variety of their behaviors must reflect the heterogeneity of human behavior. This poster presents our general framework for interactive multiagent-based simulation in virtual environment (2D or 3D). Its main objective is to integrate the notion of ontology as a core element of the design process of a behavioral simulation in order to facilitate its use/reuse by non AI-expert end- users in many application fields. To enable non AI-experts to easily exploit a multiagent simulation, it must be easily configurable: agents’ behaviors must be high level and their configuration as automated as possible. For empirical studies multiagent-based simulation results are generally integrated and compared with results from other types of simulation (discrete event, finite element, etc.) to merge the different views available on the studied system. It is therefore, interesting to have a common representation of the simulation results that is both interoperable and cross domain. We consider that the key point to address these issues is to have a semantic description of the environment in a multiagent- based simulation (MABS). To do this, this poster presents a new approach coupling multi- agent systems and semantic modeling with ontology. Ontology is a general term for a semantic modeling of knowledge to define the know- how. Using ontologies, system can infer new knowledge and relations from existing resources. To enable the development of high- level easy to configure agent’s behaviors, it is important to provide agents with the means to reason about their surrounding environment. Agents must be able to analyze unexpected situations to dynamically adapt their behavior to achieve their personal goals. Semantic rules and agent’s reasoning procedures may enable the development of such smart behaviors. For example, if you plan an agent to go to the restaurant, just specify that your agent is hungry. With semantic rules, agent decides that it must eat. This action is semantically link with “restaurant” (place where agents can eat in the ontology) and then it will go, in the environment, in a place defined as a restaurant. This solution saves a lot of designing and configuration time by just modeling the agent as hungry instead of designing a whole behavioural plan. The plan is dynamically determine at runtime according to a succession of semantic rules.
Ontology, IFC, Building, Qualification, Agent-based Simulation
Publication Category:
National conference without proceedings
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