This paper presents a geometric approach to meaning representation within the framework of continuous mathematics. Meaning representation is a central issue in Natural Language Pr...
Background: Phenomenological information about regulatory interactions is frequently available and can be readily converted to Boolean models. Fully quantitative models, on the ot...
State estimation in multiagent settings involves updating an agent’s belief over the physical states and the space of other agents’ models. Performance of the previous approac...
We present a new method for carrying out state estimation in multiagent settings that are characterized by continuous or large discrete state spaces. State estimation in multiagen...
We introduce a method for learning Bayesian networks that handles the discretization of continuous variables as an integral part of the learning process. The main ingredient in th...