Abstract a paradigm of modern Machine Learning (ML) which uses rewards and punishments to guide the learning process. One of the central ideas of RL is learning by “direct-online...
We explore a periodic analysis in the context of unobserved components time series models that decompose time series into components of interest such as trend, seasonal and irregu...
In this paper we develop a theoretical analysis of the performance of sampling-based fitted value iteration (FVI) to solve infinite state-space, discounted-reward Markovian decisi...
Abstract. This paper is concerned with arti cial evolution of neurocontrollers with adaptive synapses for autonomous mobile robots. The method consists of encoding on the genotype ...
Background: Because a priori knowledge about function of G protein-coupled receptors (GPCRs) can provide useful information to pharmaceutical research, the determination of their ...