A significant challenge in developing planning systems for practical applications is the difficulty of acquiring the domain knowledge needed by such systems. One method for acquir...
Bayesian network structure learning is a useful tool for elucidation of regulatory structures of biomolecular pathways. The approach however is limited by its acyclicity constraint...
S. Itani, Karen Sachs, Garry P. Nolan, M. A. Dahle...
Nowadays, the use of domain ontologies in e-Learning applications is rapidly increasing due to the important role they play in knowledge representation, sharing of didactical mate...
Nicola Capuano, Luca Dell'Angelo, Francesco Orciuo...
This paper presents and evaluates sequential instance-based learning (SIBL), an approach to action selection based upon data gleaned from prior problem solving experiences. SIBL le...
This paper proposes a methodology to generate artificial data sets to evaluate the behavior of machine learning techniques. The methodology relies in the definition of a domain an...
Joaquin Rios-Boutin, Albert Orriols-Puig, Josep Ma...