In recent years, researches on reinforcement learning (RL) have focused on bridging the gap between adaptive optimal control and bio-inspired learning techniques. Neural network reinforcement learning (NNRL) is among the most popular algorithms in the RL framework. The advantage of using neural networks enables the RL to search for optimal policies more efficiently in several real-life applicat...

Using Markov random eld (MRF) theory, a variety of computer vision problems can be modeled in terms of optimization based on the maximum a poste-riori (MAP) criterion. The MAP connguration minimizes the energy of a posterior (Gibbs) distribution. When the label set is discrete, the minimization is combinatorial. This paper proposes to use the continuous relaxation labeling (RL) method for the m...

Reinforcement learning (RL) is a machine learning technique with strong links to natural learning. However, it shares several “unnatural” limitations with many other successful machine learning algorithms. RL agents are not typically able to take advice or to adjust to new situations beyond the specific problem they are asked to learn. Due to limitations like these, RL remains slower and less a...

The purpose of this paper is to give a brief introduction to reinforcement learning (RL) and show how it is applied in the field of automated control. It is written to be accessible to S3 undergraduate students and other people with little or no prior knowledge in the field of RL. The paper begins by describing the basic theory of RL. It will not go into detail but rather try to explain RL at a...

Erbium-doped Y3Al5O12 (YAG) single crystals grown using the micro-pulling-down technique were investigated. Three Er concentrations chosen: 0.1, 0.3 and 1 at%. Er3+ electron paramagnetic resonance (EPR) spectra measured in ground first excited states. The corresponding g tensors 167Er hyperfine interaction changing upon content indicating moderation of Er-O bond length and/or local surrounding....

The research reported in this paper is concerned with assessing the usefulness of reinforcment learning (RL) for on-line calibration of parameters in evolutionary algorithms (EA). We are running an RL procedure and the EA simultaneously and the RL is changing the EA parameters on-the-fly. We evaluate this approach experimentally on a range of fitness landscapes with varying degrees of ruggednes...

| The traveling salesman problem (TSP) consists of nding the length of the shortest closed tour visiting N \cities". We consider the Euclidean TSP where the cities are distributed randomly and independently in a d-dimensional unit hypercube. Working with periodic boundary conditions and inspired by a remarkable universality in the kth nearest neighbor distribution , we nd for the average optimu...

Wheat and barley DNA enriched for ribosomal RNA genes was isolated from actinomycin D-CsCl gradients and used to clone the ribosomal repeating units in the plasmid pAC184. All five chimeric plasmids isolated which contained wheat rDNA and eleven of the thirteen which had barley rDNA were stable and included full length ribosomal repeating units. Physical maps of all length variants cloned have ...

in order to genetic analysis of rice seed vigour, a cross was carried out between tarom mahalli (tolerant to osmotic stress) and khazar (sensitive to osmotic stress) crosses. linkage map based on ssr markers was derived using 74 polymorphic markers and 192 f2 individuals. germination rate, radicale and plumule length were recorded from 20 plants per 192 f3 families. the loci related to germinat...

Vulvar cancer is a gynecological cancer whose incidence rate is relatively low. Patients generally were admitted at advanced stage, and radiation therapy at advanced stage does not provide favorable prognosis. Two main modalities in the treatment of vulvar cancer are surgery and radiation therapy. However, radiation can be performed in early stage vulvar cancer but surgery is thought to have mo...