Reinforcement learning is an effective machine learning paradigm in domains represented by compact and discrete state-action spaces. In high-dimensional and continuous domains, ti...
In dynamic heterogeneous environments, such as Pervasive Computing, context-aware adaptation is a key concept to meet the varying requirements of different clients. To enable such...
To achieve natural high quality synthesised speech in HMMbased speech synthesis, the effective modelling of complex acoustic and linguistic contexts is critical. Traditional appro...
Context aware middleware infrastructures have traditionally been implemented with a modular approach to allow different components to work cooperatively and supply context synthes...
Saad Liaquat Kiani, Maria Riaz, Yonil Zhung, Sungy...
Abstract. A viable ontology engineering methodology requires supporting domain experts in gradually building and managing increasingly complex versions of ontological elements and ...