Inverse Reinforcement Learning (IRL) is the problem of learning the reward function underlying a Markov Decision Process given the dynamics of the system and the behaviour of an e...
In this work we present an approach to solving time-critical decision-making problems by taking advantage of domain structure to expand the amountof time available for processing ...
Abstract. Transforming constraint models is an important task in recent constraint programming systems. User-understandable models are defined during the modeling phase but rewriti...
This work presents an XML-based authoring methodology that facilitates the different tasks associated with the development of standards-compliant e-learning content development. T...
Algorithmic skeletons intend to simplify parallel programming by providing a higher abstraction compared to the usual message passing. Task and data parallel skeletons can be dist...