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...
The adaptive estimation of a time-varying parameter vector in a linear Gaussian model is considered where we a priori know that the parameter vector belongs to a known arbitrary s...
Most of today’s distributed computing systems in the field do not support the migration of execution entities among computing nodes during runtime. The relatively static associa...
Logic programming with the stable model semantics is put forward as a novel constraint programming paradigm. This paradigm is interesting because it bring advantages of logic prog...
The low-density attack proposed by Lagarias and Odlyzko is a powerful algorithm against the subset sum problem. The improvement algorithm due to Coster et al. would solve almost a...
Tetsuya Izu, Jun Kogure, Takeshi Koshiba, Takeshi ...