We present metric?? , a provably near-optimal algorithm for reinforcement learning in Markov decision processes in which there is a natural metric on the state space that allows t...
We address the problem of autonomously learning controllers for visioncapable mobile robots. We extend McCallum's (1995) Nearest-Sequence Memory algorithm to allow for genera...
Viktor Zhumatiy, Faustino J. Gomez, Marcus Hutter,...
Abstract— Kinodynamic planning algorithms like RapidlyExploring Randomized Trees (RRTs) hold the promise of finding feasible trajectories for rich dynamical systems with complex...
This paper considers the problem of designing heterogeneous multiprocessor embedded systems. The focus is on a step of the design flow: the definition of innovative metrics for th...
Donatella Sciuto, Fabio Salice, Luigi Pomante, Wil...
Abstract. We present an approach and associated computer tool support for conducting distributed state space exploration for Coloured Petri Nets (CPNs). The distributed state space...