Abstract. Approximate Policy Iteration (API) is a reinforcement learning paradigm that is able to solve high-dimensional, continuous control problems. We propose to exploit API for...
— A robot exploring an environment can estimate its own motion and the relative positions of features in the environment. Simultaneous Localization and Mapping (SLAM) algorithms ...
We demonstrate that the performance of commodity parallel systems significantly depends on low-level details, such as storage layout and iteration space mapping, which motivates t...
Lee W. Howes, Anton Lokhmotov, Alastair F. Donalds...
Models of neurons based on iterative maps allows the simulation of big networks of coupled neurons without loss of biophysical properties such as spiking, bursting or tonic bursti...
Carlos Aguirre, Doris Campos, Pedro Pascual, Eduar...
Abstract-- This paper presents a reduced-complexity maximum a posteriori probability (MAP) channel estimator with iterative data detection for orthogonal frequency division multipl...