Abstract. We present a formalism for modeling replication in a distributed system with concurrent users sharing information. It is based on actions, which represent operations requ...
Marc Shapiro, Karthikeyan Bhargavan, Nishith Krish...
Bayesian network models are widely used for discriminative prediction tasks such as classification. Usually their parameters are determined using 'unsupervised' methods ...
We have constructed ADVISOR, a two-agent machine learning architecture for intelligent tutoring systems (ITS). The purpose of this architecture is to centralize the reasoning of a...
Constraint networks have been shown to be useful in formulating such diverse problems as scene labeling, natural language parsing, and temporal reasoning. Given a constraint netwo...
Temporally expressive planning, an important class of temporal planning, has attracted much attention lately. Temporally expressive planning is difficult; few existing planners ca...