In this paper, we present a semantical approach to multi-agent belief revision and belief update. For this, we introduce relational structures called conditional doxastic models (...
Social laws have proved to be a powerful and theoretically elegant framework for coordination in multi-agent systems. Most existing models of social laws assume that a designer is...
During the last years, argumentation has been gaining increasing interest in modeling different reasoning tasks of an agent. Many recent works have acknowledged the importance of ...
We develop a biologically motivated oscillatory network model and related dynamical synchronizationbased method of image segmentation. The first version of successive segmentation...
In this paper, we propose a novel boosted mixture learning (BML) framework for Gaussian mixture HMMs in speech recognition. BML is an incremental method to learn mixture models fo...