In the problem of probability forecasting the learner’s goal is to output, given a training set and a new object, a suitable probability measure on the possible values of the ne...
The paper generalizes the notion of a social law, the foundation of the theory of artificial social systems developed for coordinating Multi-Agent Systems. In an artificial social...
We shed light on the connections between different approaches to constraint satisfaction by showing that the main consistency concepts used to derive tractability results for cons...
Methods for learning Bayesian networks can discover dependency structure between observed variables. Although these methods are useful in many applications, they run into computat...
Eran Segal, Dana Pe'er, Aviv Regev, Daphne Koller,...
Previous researchers note the problem for semantic optimisation of database queries caused by its production of a large number of semantically equivalent alternative queries, from...