This paper shows that a detailed, although non-emotional, description of event or an action can be a reliable source for learning opinions. Empirical results show the practical uti...
Our research addresses two important problems that arise in modern large-scale distributed systems: (1) the necessity to virtualize their data flows by applying actions such as ...
Radhika Niranjan, Ada Gavrilovska, Karsten Schwan,...
Tags or observable features shared by a group of similar agents are effectively used in real and artificial societies to signal intentions and can be used to infer unobservable ...
Temporal difference reinforcement learning algorithms are perfectly suited to autonomous agents because they learn directly from an agent’s experience based on sequential actio...