We consider the problem of multi-task reinforcement learning where the learner is provided with a set of tasks, for which only a small number of samples can be generated for any g...
Analyzing and modelling a software system with separate views is a good practice to deal with complexity and maintainability. When adopting such a modular approach for modelling, i...
Franck Fleurey, Benoit Baudry, Robert B. France, S...
We extend our recent work on relevant subtask learning, a new variant of multitask learning where the goal is to learn a good classifier for a task-of-interest with too few train...
A large number of practical applications rely on effective algorithms for propositional model enumeration and counting. Examples include knowledge compilation, model checking and ...
In this paper we explore the object-oriented reflective world, performing an overview of the existing models and presenting a set of features suitable to evaluate the quality of e...