11 research outputs found
Traffic Light Control Using Deep Policy-Gradient and Value-Function Based Reinforcement Learning
Recent advances in combining deep neural network architectures with
reinforcement learning techniques have shown promising potential results in
solving complex control problems with high dimensional state and action spaces.
Inspired by these successes, in this paper, we build two kinds of reinforcement
learning algorithms: deep policy-gradient and value-function based agents which
can predict the best possible traffic signal for a traffic intersection. At
each time step, these adaptive traffic light control agents receive a snapshot
of the current state of a graphical traffic simulator and produce control
signals. The policy-gradient based agent maps its observation directly to the
control signal, however the value-function based agent first estimates values
for all legal control signals. The agent then selects the optimal control
action with the highest value. Our methods show promising results in a traffic
network simulated in the SUMO traffic simulator, without suffering from
instability issues during the training process
Advances in Robotics, Automation and Control
The book presents an excellent overview of the recent developments in the different areas of Robotics, Automation and Control. Through its 24 chapters, this book presents topics related to control and robot design; it also introduces new mathematical tools and techniques devoted to improve the system modeling and control. An important point is the use of rational agents and heuristic techniques to cope with the computational complexity required for controlling complex systems. Through this book, we also find navigation and vision algorithms, automatic handwritten comprehension and speech recognition systems that will be included in the next generation of productive systems developed by man
Factors Influencing Customer Satisfaction towards E-shopping in Malaysia
Online shopping or e-shopping has changed the world of business and quite a few people have
decided to work with these features. What their primary concerns precisely and the responses from
the globalisation are the competency of incorporation while doing their businesses. E-shopping has
also increased substantially in Malaysia in recent years. The rapid increase in the e-commerce
industry in Malaysia has created the demand to emphasize on how to increase customer satisfaction
while operating in the e-retailing environment. It is very important that customers are satisfied with
the website, or else, they would not return. Therefore, a crucial fact to look into is that companies
must ensure that their customers are satisfied with their purchases that are really essential from the ecommerce’s
point of view. With is in mind, this study aimed at investigating customer satisfaction
towards e-shopping in Malaysia. A total of 400 questionnaires were distributed among students
randomly selected from various public and private universities located within Klang valley area.
Total 369 questionnaires were returned, out of which 341 questionnaires were found usable for
further analysis. Finally, SEM was employed to test the hypotheses. This study found that customer
satisfaction towards e-shopping in Malaysia is to a great extent influenced by ease of use, trust,
design of the website, online security and e-service quality. Finally, recommendations and future
study direction is provided.
Keywords: E-shopping, Customer satisfaction, Trust, Online security, E-service quality, Malaysia
Measuring knowledge sharing processes through social network analysis within construction organisations
The construction industry is a knowledge intensive and information dependent industry. Organisations risk losing valuable knowledge, when the employees leave them. Therefore, construction organisations need to nurture opportunities to disseminate knowledge through strengthening knowledge-sharing networks. This study aimed at evaluating the formal and informal knowledge sharing methods in social networks within Australian construction organisations and identifying how knowledge sharing could be improved. Data were collected from two estimating teams in two case studies. The collected data through semi-structured interviews were analysed using UCINET, a Social Network Analysis (SNA) tool, and SNA measures. The findings revealed that one case study consisted of influencers, while the other demonstrated an optimal knowledge sharing structure in both formal and informal knowledge sharing methods. Social networks could vary based on the organisation as well as the individuals’ behaviour. Identifying networks with specific issues and taking steps to strengthen networks will enable
to achieve optimum knowledge sharing processes. This research offers knowledge sharing good practices for construction organisations to optimise their knowledge sharing processes
The 45th Australasian Universities Building Education Association Conference: Global Challenges in a Disrupted World: Smart, Sustainable and Resilient Approaches in the Built Environment, Conference Proceedings, 23 - 25 November 2022, Western Sydney University, Kingswood Campus, Sydney, Australia
This is the proceedings of the 45th Australasian Universities Building Education Association (AUBEA) conference which will be hosted by Western Sydney University in November 2022. The conference is organised by the School of Engineering, Design, and Built Environment in collaboration with the Centre for Smart Modern Construction, Western Sydney University. This year’s conference theme is “Global Challenges in a Disrupted World: Smart, Sustainable and Resilient Approaches in the Built Environment”, and expects to publish over a hundred double-blind peer review papers under the proceedings