Targeted Immunization has been researched as an applicable measure for network epidemics. Unless global information is collected, existing targeted strategies are short of strengt...
The MAP (maximum a posteriori hypothesis) problem in Bayesian networks is to find the most likely states of a set of variables given partial evidence on the complement of that set...
This paper presents the implementation of kDCI, an enhancement of DCI [10], a scalable algorithm for discovering frequent sets in large databases. The main contribution of kDCI re...
Salvatore Orlando, Claudio Lucchese, Paolo Palmeri...
Probabilistic Roadmaps (PRM) are a commonly used class of algorithms for robot navigation tasks where obstacles are present in the environment. We examine the situation where the ...
Designing distributed controllers for self-reconfiguring modular robots has been consistently challenging. We have developed a reinforcement learning approach which can be used bo...