In this paper, we tackle learning in distributed systems and the fact that learning does not necessarily involve the participation of agents directly in the inductive process itse...
Markovian processes have long been used to model stochastic environments. Reinforcement learning has emerged as a framework to solve sequential planning and decision-making proble...
Web application testers need automated, effective approaches to validate the test results of complex, evolving web applications. In previous work, we developed a suite of automate...
Traditionally, optimizers are “programmed” to optimize queries following a set of buildin procedures. However, optimizers should be robust to its changing environment to gener...
In this paper we present an approach for creating user infrom abstract representations for the automotive domain. The approach is based on transformations between different user ...
Guido M. de Melo, Frank Honold, Michael Weber, Mar...