Genetic network programming with reinforcement learning and optimal search component : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Computer Sciences at Massey University, Auckland, New Zealand

This thesis presents ways of improving the genetic composition, structure and learning strategies for a graph-based evolutionary algorithm, called Genetic Networking Programming with Reinforcement Learning (GNP-RL), particularly when working with multi-agent and dynamic environments. GNP-RL is an improvement over Genetic Programming, allowing for the concise representation of solutions in terms of a networked graph structure and uses RL to further refine the graph solutions. This work has improved GNP-RL by combining three new techniques: Firstly, it has added a reward and punishment scheme as part of its learning strategy that supports constraint conformance, allowing for a more adaptive training of the agent, so that it can learn how to avoid unwanted situations more effectively. Secondly, an optimal search algorithm has been combined in the GNP-RL core to get an accurate analysis of the exploratory environment. Thirdly, a task prioritization technique has been added to the agent’s learning by giving promotional rewards, so they are trained on how to take priority into account when performing tasks. In this thesis, we applied the improved algorithm to the Tile World benchmarking testbed, which is considered as one of the standard complex problems in this domain, having only a sparse training set. Our experiment results show that the proposed algorithm is superior than the best existing variant of the GNP-RL algorithm [1]. We have achieved 86.66% test accuracy on the standard benchmarking dataset [2]. In addition, we have created another benchmarking dataset, similar in complexity to the one proposed in [1], to test the proposed algorithms further, where it achieved a test accuracy of 96.66%; that is 33.66% more accurate

The need for national medical licensing examination in Saudi Arabia

<p>Abstract</p> <p>Background</p> <p>Medical education in Saudi Arabia is facing multiple challenges, including the rapid increase in the number of medical schools over a short period of time, the influx of foreign medical graduates to work in Saudi Arabia, the award of scholarships to hundreds of students to study medicine in various countries, and the absence of published national guidelines for minimal acceptable competencies of a medical graduate.</p> <p>Discussion</p> <p>We are arguing for the need for a Saudi national medical licensing examination that consists of two parts: Part I (Written) which tests the basic science and clinical knowledge and Part II (Objective Structured Clinical Examination) which tests the clinical skills and attitudes. We propose this examination to be mandated as a licensure requirement for practicing medicine in Saudi Arabia.</p> <p>Conclusion</p> <p>The driving and hindering forces as well as the strengths and weaknesses of implementing the licensing examination are discussed in details in this debate.</p

Violence towards healthcare workers: A study conducted in Abha City, Saudi Arabia

Background: Workplace violence in healthcare settings is a common, but an underreported problem that has been largely ignored. Violence against healthcare workers can have an adverse effect on their performance outcomes and thus influence patients' health and satisfaction. The aim of this study was to determine the frequency and types of violence against healthcare workers in a Saudi Arabian city. It was also to identify the risk factors of violence against healthcare workers and to investigate the possible consequences of such behavior. Materials and Methods: In Abha city, there are two government hospitals and ten primary healthcare centers. All healthcare workers in these healthcare institutions including physicians, nurses, dentists, pharmacists, laboratory technicians or specialists, radiologists, social workers, and psychologists were eligible to participate in this cross-sectional study. Data were collected using a structured self-administered questionnaire. Results: A total of 738 healthcare workers responded (92% response rate). The mean age was 31 ± 7.7 years (range 21–60) and the majority (64.9%) were females and 69.4% were Saudis. More than half (57.5%) had experienced some workplace violence at least once. Verbal assaults and slaps were the most common form of workplace-related violence (58%). Conclusions: Violence against healthcare workers in Abha city is more common, especially against nurses. The reasons need to be explored in order to set and develop policies, regulations and interventions to prevent violence against workers