Communication and Cognition in Primate Group Movement

We here review the communicative and cognitive processes underpinning collective group movement in animals. Generally, we identify 2 major axes to explain the dynamics of decision making in animal or human groups or aggregations: One describes whether the behavior is largely determined by simple rules such as keeping a specific distance from the neighbor, or whether global information is also factored in. The second axis describes whether or not the individual constituents of the group have overlapping or diverging interests. We then review the available evidence for baboons, which have been particularly well studied, but we also draw from further studies on other nonhuman primate species. Baboons and other nonhuman primates may produce specific signals in the group movement context, such as the notifying behavior of male hamadryas baboons at the departure from the sleeping site, or clear barks that are given by chacma baboons that have lost contact with the group or specific individuals. Such signals can be understood as expressions of specific motivational states of the individuals, but there is no evidence that the subjects intend to alter the knowledge state of the recipients. There is also no evidence for shared intentionality. The cognitive demands that are associated with decision making in the context of group coordination vary with the amount of information and possibly conflicting sources of information that need to be integrated. Thus, selective pressures should favor the use of signals that maintain group cohesion, while recipients should be selected to be able to make the decision that is in their own best interest in light of all the available information

An architecture that supports task-centered adaptation in intelligent environments

The realization of the vision of ambient intelligence requires developments both at infrastructure and application levels. As a consequence of the former, physical spaces are turned into intelligent AmI environments, which offer not only services such as sensing, digital storage, computing, and networking but also optimization, data fusion, and adaptation. However, despite the large capabilities of AmI environments, people's interaction with their environment will not cease to be goal-oriented and task-centric. In this chapter, we use the notions of ambient ecology to describe the resources of an AmI environment and activity spheres to describe the specific ambient ecology resources, data and knowledge required to support a user in realizing a specific goal. In order to achieve taskbased collaboration among the heterogeneous members of an ambient ecology, first one has to deal with this eterogeneity, while at the same time achieving independence between a task description and its respective realization within a specific AmI environment. Successful execution of tasks depends on the quality of interactions among artifacts and among people and artifacts, as well as on the efficiency of adaptation mechanisms. The formation of a system that realizes adaptive activity spheres is supported by a service-oriented architecture, which uses intelligent agents to support adaptive planning, task realization and enhanced human-machine interaction, ontologies to represent knowledge and ontology alignment mechanisms to achieve adaptation and device independence. The proposed system supports adaptation at different levels, such as the changing configuration of the ambient ecology, the realization of the same activity sphere in different AmI environments, the realization of tasks in different contexts, and the interaction between the system and the user. © 2009 Springer-Verlag US

Symbiotic ecologies in next generation ambient intelligent environments

International audienceThis paper describes a novel approach to realize symbiotic ecologies within Next Generation Ambient Intelligent Environments (NGAIEs). The proposed approach comprises novel ontology and agent technologies allowing for adaptation on a variety of levels. The metaphor of symbiotic ecologies reflects a meaningful integration of relevant entities (i.e., services, devices, agents) and information within NGAIEs to accomplish a specific user’s task by relying on the symbiotic relationship of the user and his/her intelligent environment. We adopt a service-oriented architecture, combined with (a) intelligent agents that support adaptive task realization and enhanced human-machine interaction and (b) ontologies that provide knowledge representation, management of heterogeneity at user and device level, semantically rich resource discovery and adaptation using ontology alignment mechanisms. In this article, we analyse heterogeneity concerning user behaviour and adaptive user interaction modelling. Furthermore, we focus on heterogeneity regarding the representation of the states of entities and their availability over different networks. The paper will also report on the deployment of a system prototype in a real world setting which is the intelligent flat (iSpace) at the University of Essex

A pervasive system architecture that supports adaptation using agents and ontologies

In the context of the EU funded R&D project ATRACO we are developing a conceptual framework and a system architecture that will support the realization of adaptive and trusted ambient intelligent systems. Our approach is based on a number of well established engineering principles, such as the distribution of control and the separation of service interfaces from the service implementation, adopting a SOA model combined with intelligent agents and ontologies. Agents support adaptive task realization and enhanced humanmachine interaction while ontologies provide knowledge representation, management of heterogeneity, semantically rich resource discovery and adaptation. ATRACO systems are dynamic compositions of distributed, loosely-coupled and highly cohesive components that operate in dynamic environments. © 2009 IEEE

Multidimensional pervasive adaptation into ambient intelligent environments

In this paper we describe the ATRACO (Adaptive and TRusted Ambient eCOlogies) approach towards next generation ambient intelligent environments. Several agents, such as a Fuzzy Task Agent with learning capabilities and an Interaction Agent collaborate in a goal-related Activity Sphere and adapt heterogeneous artifacts within the sphere in order to support the user to fulfill tasks. All components work on a dynamic Sphere Ontology, which forms the main knowledge base of the ecology. The presented prototype is able to realize the Goal "Feel comfortable at home after work" and was implemented in an existing intelligent environment. © 2009 IEEE