Integrating miniMin-HSP Agents in a Dynamic Simulation Framework

Lozano, Miguel; Grimaldo, Francisco; Barber, Fernando

doi:10.1007/978-3-540-24674-9_56

Cited by 2 publications

(3 citation statements)

References 10 publications

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“…Planningbased agents are normally inspired by the STRIPS (ADL/PDDL) action language, where activities are represented using a classic state model with a conjunction of grounded literals. This approach has been used in storytelling domains (Charles et al, 2003) and other task-oriented 3D agents (Lozano et al, 2004). In these contexts, the usual representation of the actions suffers from different drawbacks when an actor is interested in reusing his/her operators with different objects.…”

Section: Task Librarymentioning

confidence: 99%

Simulating socially intelligent agents in semantic virtual environments

Grimaldo

Lozano²,

Barber

et al. 2008

The Knowledge Engineering Review

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The simulation of synthetic humans inhabiting virtual environments is a current research topic with a great number of behavioral problems to be tackled. Semantical virtual environments (SVEs) have recently been proposed not only to ease world modeling but also to enhance the agent–object and agent–agent interaction. Thus, we propose the use of ontologies to define the world’s knowledge base and to introduce semantic levels of detail that help the sensorization of complex scenes—containing lots of interactive objects. The object taxonomy also helps to create general and reusable operativity for autonomous characters—for example, liquids can be poured from containers such as bottles. On the other hand, we use the ontology to define social relations among agents within an artificial society. These relations must be taken into account in order to display socially acceptable decisions. Therefore, we have implemented a market-based social model that reaches coordination and sociability by means of task exchanges. This paper presents a multi-agent framework oriented to simulate socially intelligent characters in SVEs. The framework has been successfully tested in three-dimensional (3D) dynamic scenarios while simulating a virtual university bar, where groups of waiters and customers interact with both the objects in the scene and the other virtual agents, finally displaying complex social behaviors.

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Section: Task Librarymentioning

confidence: 99%

Simulating socially intelligent agents in semantic virtual environments

Grimaldo

Lozano²,

Barber

et al. 2008

The Knowledge Engineering Review

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“…Agents presented in [15] suffer from autonomous communication modules to coordinate their actuation or exchange information with their partners. Thus, the behavioral consistency of the multi-agent animations can be poor.…”

Section: Social Modelmentioning

confidence: 99%

“…As previously exposed, characters are benevolent and their intention is to let the others finish their previous commitments. Following this premise, the miniMin-HSP planner used by our 3DIVA [15] will now start the search from a future virtual state resulted from applying the c beliefs over the current perceived state (this mental execution uses the add and delete lists of the STRIPS definition for the the external ongoing actions).In this manner, it constructs a prospective situation that skips actual dependences. Additionally, each c belief will lock the objects being used by other agents thereby forbidding to jeopardize the success of the tasks previously initiated (see figure 3).…”

Section: Coordinated Task-oriented Agentsmentioning

confidence: 99%

Integrating Social Skills in Task-Oriented 3D IVA

Grimaldo

Lozano

Barber

et al. 2005

Intelligent Virtual Agents

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Abstract. This paper presents a set of mechanisms oriented to incorporate social information into the decision taking of task-oriented 3DIVA. The aim of this approach is to integrate collaborative skills in different character's roles (seller/buyer, worker, pedestrian, etc.) in order to enhance its behavioral animation. The collective intelligence expected in this kind of multi-character domains (e.g. storytelling, urban simulation, interactive games, etc.) requires agents able to dialogue/interact with other characters, to autonomously group/ungroup (according to their goals), or to distribute tasks and coordinate their execution for solving possible conflicts. The social model implemented follows the definitions for collaborative agents, since agents use communicative acts to cooperate. In this context, collaboration derives mainly from two points: team formation (grouping for 3DIVA) and task coordination (reducing dependences between agent activities). Finally, we show the results obtained in 3D multi-character simulations (resource competition), created to verify the social behavior introduced.

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Integrating miniMin-HSP Agents in a Dynamic Simulation Framework

Cited by 2 publications

References 10 publications

Simulating socially intelligent agents in semantic virtual environments

Simulating socially intelligent agents in semantic virtual environments

Integrating Social Skills in Task-Oriented 3D IVA

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