Multiobjective optimization in general aims at learning about the problem at hand. Usually the focus lies on objective space properties such as the front shape and the distributio...
This paper presents postponed updates, a new strategy for TD methods that can improve sample efficiency without incurring the computational and space requirements of model-based ...
We pose partitioning a b-bit Internet Protocol (IP) address space as a supervised learning task. Given (IP, property) labeled training data, we develop an IP-specific clustering a...
This paper extends an adaptive discretization method, Spliton-Demand (SoD), to be capable of handling multidimensional continuous search spaces. The proposed extension is called m...
Systems that act autonomously in the environment have to be able to integrate three basic behaviors: planning, execution, and learning. Planning involves describing a set of action...