Semantic modeling of Virtual Environments using MASCARET

Chevaillier, Pierre; Trinh, Thanh-Hai; Barange, Mukesh; Loor, Pierre De; Devillers, Frédéric; Soler, Julien; Querrec, Ronan

doi:10.1109/searis.2012.6231174

Cited by 40 publications

(37 citation statements)

References 14 publications

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“…LORA++ relies on the model STORM , able to model collaborative actions. HAVE, a language extended from the UML activity diagram, relies VEHA (Chevaillier et al, 2012) (also an extension of UML) describing the behaviour of the objects in the environment. Other ways to model events can be found in the literature, even if they are not directly connected to scenario models.…”

Section: Modelling Of Eventsmentioning

confidence: 99%

Versatile Scenario Guidance for Collaborative Virtual Environments

Claude

Gouranton

Arnaldi

2015

Proceedings of the 10th International Conference on Computer Graphics Theory and Applications

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Abstract:Currently, the scenario of a virtual reality application depends greatly of the representation of the virtual environment and the goals of the application. Different needs arise from these elements such as the abstraction level of their events, the presence of multiple actors or their freedom of action. In this paper, we propose a scenario engine model that aims at being used in any virtual reality application where the scenario is a key feature. It differs from other models as it can be used without making any assumption on the simulation purpose or on the modelling of the Virtual Environment (events model, objects behaviour).

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Section: Modelling Of Eventsmentioning

confidence: 99%

Versatile Scenario Guidance for Collaborative Virtual Environments

Claude

Gouranton

Arnaldi

2015

Proceedings of the 10th International Conference on Computer Graphics Theory and Applications

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“…1). The semantic modeling of VE [6] is used as semantic knowledge. It contains semantic information that is known a priori by the agent, such as knowledge concerning concepts, and individual and shared plans.…”

Section: Knowledge Organisation and Processingmentioning

confidence: 99%

“…The C 2 BDI agent is considered to be situated in an informed VE [6]. It perceives VE through the perception module.…”

mentioning

confidence: 99%

Task-Oriented Conversational Behavior of Agents for Collaboration in Human-Agent Teamwork

Barange

Kabil

Keukelaere

et al. 2014

Advances in Practical Applications of Heterogeneous Multi-Agent Systems. The PAAMS Collection

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International audienceCoordination is an essential ingredient for human-agent teamwork. It requires team members to share knowledge to establish common grounding and mutual awareness among them. This paper proposes a be-havioral architecture C 2 BDI that enhances the knowledge sharing using natural language communication between team members. Collaborative conversation protocols and resource allocation mechanism have been defined that provide proactive behavior to agents for coordination. This architecture has been applied to a real scenario in a collaborative virtual environment for learning. The solution enables users to coordinate with other team members

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“…This is the case of the Generic Virtual Training (GVT) [9,19] in its collaborative version. The MASCARET model [3] also potentially handle collaborative interaction [5].…”

Section: Virtual Humans In Cvetmentioning

confidence: 99%

“…The 3 metaphors used are illustrated in fig.6: • flickering avatar (see 6(a)): each time an exchange happened, the two involved avatars flickered from a color to white, 5 http://www.razerzone.com/fr-fr/gaming-controllers/razer-hydra/…”

Section: Exchange Of Avatars and Attention Of The Usermentioning

confidence: 99%

An interaction abstraction model for seamless avatar exchange in CVET

Bouville

Lopez

Nouviale

et al. 2014

2014 International Workshop on Collaborative Virtual Environments (3DCVE)

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Collaboration and interaction between users and virtual humans in virtual environments is a crucial challenge, notably for Collaborative Virtual Environments for Training (CVET). A training procedure, indeed, often involves several actors: trainees, teammates and many times a trainer. Yet, a major benefit of CVET is to propose to users to be trained even if the required number of person needed by the procedure is not available. Therefore, almost every CVET use autonomous virtual humans to replace the missing person. In this paper, we present the main results of our project that aims at improving the effective collaboration between users and virtual humans involved in a complex task within CVET. Using an entity called the "Shell", we are able to wrap the features common to both users and virtual humans. It gives us an abstraction level to pool the management of the main processes useful to control an avatar, interact with the environment and gather knowledge from a CVET. Besides, the Shell allows seamless exchange of avatars during a procedure. Thanks to the Shell, the exchange can be carried out at any time during a task while preserving all the data associated to a role in a procedure.

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Semantic modeling of Virtual Environments using MASCARET

Cited by 40 publications

References 14 publications

Versatile Scenario Guidance for Collaborative Virtual Environments

Versatile Scenario Guidance for Collaborative Virtual Environments

Task-Oriented Conversational Behavior of Agents for Collaboration in Human-Agent Teamwork

An interaction abstraction model for seamless avatar exchange in CVET

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