Agents that exist in an environment that changes over time, and are able to take into account the temporal nature of experience, are commonly called incremental learners. It is wid...
Nicola Di Mauro, Floriana Esposito, Stefano Ferill...
Reinforcement learning is a popular and successful framework for many agent-related problems because only limited environmental feedback is necessary for learning. While many algo...
Abstract. Multiple classifier systems based on neural networks can give improved generalisation performance as compared with single classifier systems. We examine collaboration in ...
We present an approach to classification of biomedical terms based on the information acquired automatically from the corpus of relevant literature. The learning phase consists of...
Autonomics or self-reorganization becomes pertinent for websites serving a large number of users with highly varying workloads. An important component of self-adaptation is to mod...