Imitation learning is an effective method for training an autonomous agent to accomplish a task by imitating expert behaviors in their demonstrations. However, traditional imitation learning methods require a large number of expert demonstrations in order to learn a complex behavior. Such a disadvantage has limited the potential of imitation learning in complex tasks where the expert demonstrations are not sufficient. In order to address the problem, we propose a Generative Adversarial Network-based model which is designed to learn optimal policies using only a single demonstration. The proposed model is evaluated on two simulated tasks in comparison with other methods. The results show that our proposed model is capable of completing considered tasks despite the limitation in the number of expert demonstrations, which clearly indicate the potential of our model.
In the literature, several correlations have been proposed for hold-up prediction in rotating disk contactor. However,
these correlations fail to predict hold-up over wide range of conditions. Based on a databank of around 611
measurements collected from the open literature, a correlation for hold up was derived using Artificial Neiral Network
(ANN) modeling. The dispersed phase hold up was found to be a function of six parameters: N, vc , vd , Dr , c d m / m ,
s . Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 6.52%
and Standard Deviation (SD) 9.21%. A comparison with selected correlations in the literature showed that the
developed ANN correlation noticeably
The inverse kinematic equation for a robot is very important to the control robot’s motion and position. The solving of this equation is complex for the rigid robot due to the dependency of this equation on the joint configuration and structure of robot link. In light robot arms, where the flexibility exists, the solving of this problem is more complicated than the rigid link robot because the deformation variables (elongation and bending) are present in the forward kinematic equation. The finding of an inverse kinematic equation needs to obtain the relation between the joint angles and both of the end-effector position and deformations variables. In this work, a neural network has been proposed to solve the problem of inverse kinemati
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Cutting forces are important factors for determining machine serviceability and product quality. Factors such as speed feed, depth of cut and tool noise radius affect on surface roughness and cutting forces in turning operation. The artificial neural network model was used to predict cutting forces with related to inputs including cutting speed (m/min), feed rate (mm/rev), depth of cut (mm) and work piece hardness (Map). The outputs of the ANN model are the machined cutting force parameters, the neural network showed that all (outputs) of all components of the processing force cutting force FT (N), feed force FA (N) and radial force FR (N) perfect accordance with the experimental data. Twenty-five samp
... Show MoreE-Health care system is one of the great technology enhancements via using medical devices through sensors worn or implanted in the patient's body. Wireless Body Area Network (WBAN) offers astonishing help through wireless transmission of patient's data using agreed distance in which it keeps patient's status always controlled by regular transmitting of vital data indications to the receiver. Security and privacy is a major concern in terms of data sent from WBAN and biological sensors. Several algorithms have been proposed through many hypotheses in order to find optimum solutions. In this paper, an encrypting algorithm has been proposed via using hyper-chaotic Zhou system where it provides high security, privacy, efficiency and
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This research aim to overcome the problem of dimensionality by using the methods of non-linear regression, which reduces the root of the average square error (RMSE), and is called the method of projection pursuit regression (PPR), which is one of the methods for reducing dimensions that work to overcome the problem of dimensionality (curse of dimensionality), The (PPR) method is a statistical technique that deals with finding the most important projections in multi-dimensional data , and With each finding projection , the data is reduced by linear compounds overall the projection. The process repeated to produce good projections until the best projections are obtained. The main idea of the PPR is to model
... Show MoreThe university press is an essential pillar in building an academic community to achieve its objectives in the service of society. Since the university press is a means of university media, which is issued by the departments or units of media in Iraqi universities as academic governmental-institutions, so it highlights the activities of the university and link them to its internal society in the first place as the university press is a mirror of the university and its voice is sincerely expressed. This research comes to know the extent of interest of the university press in various student issues.
In order to identify the problem of the research, the method of content analysis was adopted within the survey method
... Show Moreهدف البحث التعرف الى اسباب سلوك التنمر لدى طلاب الصف الاول المتوسط من وجهة نظر المدرسين والمدرسات واساليب تعديله، واستعمل الباحثان المنهج الوصفي واختيار عينة عشوائية من المدرسين والمدرسات في متوسطة أرض الرافدين ومتوسطة الرحمن للبنين وكان عددهم (46) مدرساً ومدرسة بواقع (32) مدرساً و(14) مدرسة، واعتمد الباحثان الاستبانة أداة للتعرف الى اسباب سلوك التنمر واساليب تعديله، واشارت نتائج البحث الى تنوع اسباب التن
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