Spectrum sharing employs dynamic allocation of frequency resources for a more efficient use of the radio spectrum. Despite its appealing features, this technology inevitably compli...
Luca Sanguinetti, Michele Morelli, H. Vincent Poor
The application of Reinforcement Learning (RL) algorithms to learn tasks for robots is often limited by the large dimension of the state space, which may make prohibitive its appli...
Andrea Bonarini, Alessandro Lazaric, Marcello Rest...
With the increasing use of the internet, many problemsolving tasks such as resource allocation, scheduling, planning, and configuration pose themselves in an open setting involvi...
Action modeling is an important skill for agents that must perform tasks in novel domains. Previous work on action modeling has focused on learning STRIPS operators in discrete, r...
Abstract. In this paper we introduce the concept of knowledge granularity and study its influence on an agent's action selection process. Action selection is critical to an ag...