Titlebook: Constructing Ambient Intelligence; AmI 2007 Workshops D Max Mühlh?user,Alois Ferscha,Erwin Aitenbichler Conference proceedings 2008 Springe

認(rèn)識(shí)

Mexhid Ferati,Wondwossen M. Beyeneices and resources. Interacting in and with such environments requires new interaction paradigms, abstracting from single interaction devices to utilize the environment as interaction space. Using a networked set of interaction resources allows supporting multiple modalities and new interaction tech

生命層

擦試不掉

Lecture Notes in Computer Scienceended to meet the requirements in this context. The corresponding tool support has to be flexible in terms of integrating domain concepts rapidly. We propose a model-based approach for tool support of task model editors. By doing so, new modeling concepts can be introduced easily. Thus task models c

ECG769

exhilaration

Computable Transformations of Structuresironments should therefore also be dynamic at runtime. Developing such UIs is challenging since many aspects have to be considered. Most existing approaches follow Model-driven Engineering (MDE) as a solution. However, they only address design time issues. We successfully applied MDE for runtime gen

PARA

Compressibility and Probabilistic Proofselligence (AmI-07). The focus of the workshop was to bring together experts of diverse areas such as Ubiquitous Computing, Product Engineering, Cognitive Science, Human Computer Interaction, Economics, and Artificial Intelligence, with the specific goal of helping shape a vision of creating living a

抗體

Matthew J. Patitz,Mike Stannettsciplinary research will be required in order to achieve this vision. Here, Artificial Intelligence (AI) provides a rich set of methods for implementing the “intelligence bit” of the AmI vision. Speech recognition, image interpretation, learning (from user interaction), reasoning (about users’ goals

BABY

SMART

勉強(qiáng)

Workshop Summary: Artificial Intelligence Methods for Ambient Intelligencesciplinary research will be required in order to achieve this vision. Here, Artificial Intelligence (AI) provides a rich set of methods for implementing the “intelligence bit” of the AmI vision. Speech recognition, image interpretation, learning (from user interaction), reasoning (about users’ goals