Effective learning in multi-label classification (MLC) requires an ate level of abstraction for representing the relationship between each instance and multiple categories. Curren...
In open, dynamic multi-agent systems, agents may form short-term ad-hoc groups, such as coalitions, in order to meet their goals. Trust and reputation are crucial concepts in thes...
In this paper, we propose a new integration approach for simulation and behaviour in the learning context that is able to coherently manage the shared virtual environment for the ...
Motivated by recent work on quantum black-box query complexity, we consider quantum versions of two wellstudied models of learning Boolean functions: Angluin’s model of exact le...
Recent work in transfer learning has succeeded in making reinforcement learning algorithms more efficient by incorporating knowledge from previous tasks. However, such methods typ...