We present a probabilistic approach to language change in which word forms are represented by phoneme sequences that undergo stochastic edits along the branches of a phylogenetic ...
Hierarchical penalization is a generic framework for incorporating prior information in the fitting of statistical models, when the explicative variables are organized in a hiera...
Marie Szafranski, Yves Grandvalet, Pierre Morizet-...
Both explanation-based and inductive learning techniques have proven successful in a variety of distributed domains. However, learning in multi-agent systems does not necessarily ...
We present an architecture that provides a robust, scalable and flexible software framework for planning and scheduling systems through the use of standardized industrial-strength...
In this paper, we describe the theoretical framework that allows us to use of the expert system shell CLIPS to define the network model in the Distribution Management System (DMS)...