We propose a new approach to value function approximation which combines linear temporal difference reinforcement learning with subspace identification. In practical applications...
With the goal to generate more scalable algorithms with higher efficiency and fewer open parameters, reinforcement learning (RL) has recently moved towards combining classical tec...
Abstract. The definition of similarity measures is one of the most crucial aspects when developing case-based applications. In particular, when employing similarity measures that ...
We study the problem of learning regular tree languages from text. We show that the framework of function distinguishability as introduced by the author in Theoretical Computer Sc...
As a fundamental problem in pattern recognition, graph matching has found a variety of applications in the field of computer vision. In graph matching, patterns are modeled as gr...