One of the key problems in reinforcement learning is balancing exploration and exploitation. Another is learning and acting in large or even continuous Markov decision processes (...
Lihong Li, Michael L. Littman, Christopher R. Mans...
Self-organising multi-agent systems provide a suitable paradigm for developing autonomic computing systems that manage themselves. Towards this goal, we demonstrate a robust, dece...
Ramachandra Kota, Nicholas Gibbins, Nicholas R. Je...
The bounded diameter minimum spanning tree problem is an NP-hard combinatorial optimization problem arising, for example, in network design when quality of service is of concern. ...
Most of the software developed in the world follows the object-oriented (OO) paradigm. However, the existing work on evolutionary testing is mainly targeted to procedural language...
As a foundation for the design of groupware, we need a new science of group interaction, a systematic description of the processes at the group level of description that may contr...