scholarly journals Overcoming Challenges of Applying Reinforcement Learning for Intelligent Vehicle Control

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 7829
Author(s):  
Rafael Pina ◽  
Haileleol Tibebu ◽  
Joosep Hook ◽  
Varuna De Silva ◽  
Ahmet Kondoz

Reinforcement learning (RL) is a booming area in artificial intelligence. The applications of RL are endless nowadays, ranging from fields such as medicine or finance to manufacturing or the gaming industry. Although multiple works argue that RL can be key to a great part of intelligent vehicle control related problems, there are many practical problems that need to be addressed, such as safety related problems that can result from non-optimal training in RL. For instance, for an RL agent to be effective it should first cover all the situations during training that it may face later. This is often difficult when applied to the real-world. In this work we investigate the impact of RL applied to the context of intelligent vehicle control. We analyse the implications of RL in path planning tasks and we discuss two possible approaches to overcome the gap between the theorical developments of RL and its practical applications. Specifically, firstly this paper discusses the role of Curriculum Learning (CL) to structure the learning process of intelligent vehicle control in a gradual way. The results show how CL can play an important role in training agents in such context. Secondly, we discuss a method of transferring RL policies from simulation to reality in order to make the agent experience situations in simulation, so it knows how to react to them in reality. For that, we use Arduino Yún controlled robots as our platforms. The results enhance the effectiveness of the presented approach and show how RL policies can be transferred from simulation to reality even when the platforms are resource limited.

Author(s):  
Francesco Piccialli ◽  
Vincenzo Schiano di Cola ◽  
Fabio Giampaolo ◽  
Salvatore Cuomo

AbstractThe first few months of 2020 have profoundly changed the way we live our lives and carry out our daily activities. Although the widespread use of futuristic robotaxis and self-driving commercial vehicles has not yet become a reality, the COVID-19 pandemic has dramatically accelerated the adoption of Artificial Intelligence (AI) in different fields. We have witnessed the equivalent of two years of digital transformation compressed into just a few months. Whether it is in tracing epidemiological peaks or in transacting contactless payments, the impact of these developments has been almost immediate, and a window has opened up on what is to come. Here we analyze and discuss how AI can support us in facing the ongoing pandemic. Despite the numerous and undeniable contributions of AI, clinical trials and human skills are still required. Even if different strategies have been developed in different states worldwide, the fight against the pandemic seems to have found everywhere a valuable ally in AI, a global and open-source tool capable of providing assistance in this health emergency. A careful AI application would enable us to operate within this complex scenario involving healthcare, society and research.


1990 ◽  
Vol 117 (2) ◽  
pp. 173-277 ◽  
Author(s):  
C. D. Daykin ◽  
G. B. Hey

AbstractA cash flow model is proposed as a way of analysing uncertainty in the future development of a general insurance company. The company is modelled alongside the market in aggregate so that the impact of changes in premium rates relative to the market can be assessed. An extensive computer model is developed along these lines, intended for use in practical applications by actuaries advising the management of genera1 insurance companies. Simulation methods are used to explore the consequences of uncertainty, particularly in regard to inflation and investments. Some comments are made on the role of actuaries in general insurance. Alternative approaches to describing the behaviour of an insurance firm in the market are considered.


2020 ◽  
Vol 5 (19) ◽  
pp. 32-35
Author(s):  
Anand Vijay ◽  
Kailash Patidar ◽  
Manoj Yadav ◽  
Rishi Kushwah

In this paper an analytical survey on the role of machine learning algorithms in case of intrusion detection has been presented and discussed. This paper shows the analytical aspects in the development of efficient intrusion detection system (IDS). The related study for the development of this system has been presented in terms of computational methods. The discussed methods are data mining, artificial intelligence and machine learning. It has been discussed along with the attack parameters and attack types. This paper also elaborates the impact of different attack and handling mechanism based on the previous papers.


Author(s):  
Christina L. McDowell Marinchak ◽  
Edward Forrest ◽  
Bogdan Hoanca

This entry will review the state of the art in AI, with a particular focus on applications in marketing. Based on the current capabilities of AI in marketing, the author's explore the new rules of engagement. Rather than simply targeting consumers, the marketing effort will also be directed at the algorithms controlling the consumers' virtual personal assistants (VPAs). Rather than exploiting human desires and weakness, marketing will need to focus on meeting the user's actual needs. The level of customer satisfaction will be even more critical as marketing will need to focus on establishing and maintaining a reputation in competition with those of similar offerings in the marketplace. This entry concludes with thoughts on the long-term implications, exploring the role of customer trust in the adoption of AI agents, the security requirements for agents and the ethical implications of access to such agents.


Author(s):  
Heru Susanto ◽  
Leu Fang Yie ◽  
Didi Rosiyadi ◽  
Akbari Indra Basuki ◽  
Desi Setiana

Digital ecosystems have grown rapidly over the years, and governments are investing in digital provision for their processes and services. Despite the advantages of distributed technologies, there are many security issues as well that result in breaches of data privacy with serious impact including legal and reputational implications. To deal with such threats, government agencies need to thoughtfully improve their security defences to protect data and systems by using automation and artificial intelligence (AI), as well as easing the data security measures including early warning of threats and detection. This study provides a comprehensive view of AI and automaton to highlight challenges and issues concerning data security and suggests steps to combat the issues. The authors demonstrate the role of AI-driven security tools and automation to mitigate the impact of data breaches to also propose recommendations for government agencies to enhance their data security protection.


Author(s):  
Oleksandr Burov

Keywords: human capital, remote work, cybersecurity, workforce, digital economics The article considers the role of human capital in the transitionto the remote work. The analysis of world changes in the field of safe and effectiveuse of digital business environment and qualification of workforce in the conditions ofgrowth of remote work is carried out. The analysis was conducted in the following areas:general features of the digitalizing in crisis and innovation, a new paradigm of business«Data is the new gold», the organization of the workforce in the transition to teleworking,the priorities of today's professions, the problems of cybersecurity in teleworking. It has been articulated that the main requirements for the today’s workforce are intellectualand creative abilities, competence in the field of creation and use of ICT, bigdata (data science, data mining, data analytics) and artificial intelligence, the role ofwhich has grown even more due to the COVID-19 pandemic. The human component ofintellectual capital (in the form of knowledge, skills and competencies, as well as intellectualand creative abilities) is gaining new importance in the digital economy.The analysis of relationship of the crisis and innovation made on the basis of the ClarivateDerwent report has demonstrated the impact of the pandemic on the global lifecycle of research and innovation projects in the first half of 2020, namely that COVID-19violated innovation strategy of the innovative leaders worldwide. The analysis hasdemonstrated: in the new conditions of accelerated digitalization, ingenuity and speed ofdecision-making and innovation are needed more than ever. These priorities will affectthe world economy in the coming year.Special attention in analysis has been paid to the new business paradigm related touse and role of data. It was highlighted that digitization generates vast amounts of datathat offer many opportunities for business, human well-being, and the environment. As aresult, new capabilities and opportunities arise for business with the ecosystem of cooperationand partnership, as well as collaboration of stakeholders.The core of changes in digitalization is reskilling and upskilling of the workforce accountingnew workplaces and new requirements for them. It is recognized that talentmanagement and creative people selection can be the main engine in future transformationof economics, and workforce becomes an effective pole for investments. At the sametime, it is argued that remote worker is outside the scope of corporate protection, and virtuallyany production information, like human capital, becomes much more vulnerablein such conditions and requires appropriate cybersecurity methods.As a conclusion, it is articulated that the ability of companies to use big data is beginningto play a significant role in the economy, which in turn requires the involvementand training of data processing and analysis specialists. The direction of professions thatis being actively formed recently — data science — is one of the most priority in the labormarket. At the same time, the labor market needs skills and abilities in the field of interpersonalcommunication (soft skills), which are able to ensure the effective operation ofpeople and systems of hybrid intelligence «human-artificial intelligence».For the further research it has been recommended a comprehensive study of protectionof objects and subjects of intellectual property in open networks.


Genes ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 1465
Author(s):  
Kamila Majidova ◽  
Julia Handfield ◽  
Kamran Kafi ◽  
Ryan D. Martin ◽  
Ryszard Kubinski

Inflammatory bowel diseases (IBD), subdivided into Crohn’s disease (CD) and ulcerative colitis (UC), are chronic diseases that are characterized by relapsing and remitting periods of inflammation in the gastrointestinal tract. In recent years, the amount of research surrounding digital health (DH) and artificial intelligence (AI) has increased. The purpose of this scoping review is to explore this growing field of research to summarize the role of DH and AI in the diagnosis, treatment, monitoring and prognosis of IBD. A review of 21 articles revealed the impact of both AI algorithms and DH technologies; AI algorithms can improve diagnostic accuracy, assess disease activity, and predict treatment response based on data modalities such as endoscopic imaging and genetic data. In terms of DH, patients utilizing DH platforms experienced improvements in quality of life, disease literacy, treatment adherence, and medication management. In addition, DH methods can reduce the need for in-person appointments, decreasing the use of healthcare resources without compromising the standard of care. These articles demonstrate preliminary evidence of the potential of DH and AI for improving the management of IBD. However, the majority of these studies were performed in a regulated clinical environment. Therefore, further validation of these results in a real-world environment is required to assess the efficacy of these methods in the general IBD population.


2021 ◽  
Vol 67 (2) ◽  
pp. 69-75
Author(s):  
Vojislav Božanić ◽  
Vlastimir Dedovic ◽  
Milan Božović

The paper presents an overview of the most important regulations and institutions affecting the level of quality and fittingness of the vehicle fleet, in order to increase the level of general traffic safety in the Republic of Serbia. The Traffic Safety Agency, among other things, alone or in cooperation with others, regulates, controls and implements the system of homologation, testing and control of conformity of vehicles, equipment and parts. It authorizes and supervises other organizations for vehicle control and testing. The role of standardization in this process is dual: first - it refers to the subject of testing - vehicles, and second - to the quality of testing - authorized organizations. The paper discusses the important provisions of regulations for vehicle testing and analyzes the impact of the standards ISO 17020 and ISO 17025 on the work of authorized organizations. In conclusion, it was proposed that in order to achieve and maintain high level of testing quality, mandatory accreditation of authorized organizations should be prescribed. Mandatory application of the standards would have a positive impact on the traffic safety segment which depends on the technical characteristics of the vehicle, and as well, reduce the Agency's obligations.


2020 ◽  
Author(s):  
Samara Bin Salem ◽  
Jagadeesan Premanandh

Ongoing Covid-19 is a new global threat with a devastating impact on lives and economy especially in China, the origination spot of epidemic. The catastrophic nature of an epidemic depends on isolation and quarantine measures. The impact of mass quarantine in China in containing Covid -19 has been discussed. Repercussions of mass quarantine and its profound adverse concerns on healthy individuals and economy has been presented. Role of artificial intelligence in early warning alert and its impacts are discussed. In conclusion, the ability to recognize outbreaks and act is still challenging as each event is unique in its own way. In other words, the causative organisms are smarter than human and human made algorithms. Nevertheless, the expensive lessons learnt enable us to prepare ourselves to prevent such disasters which is an on-going battle.


2022 ◽  
pp. 191-213
Author(s):  
Heru Susanto ◽  
Leu Fang Yie ◽  
Didi Rosiyadi ◽  
Akbari Indra Basuki ◽  
Desi Setiana

Digital ecosystems have grown rapidly over the years, and governments are investing in digital provision for their processes and services. Despite the advantages of distributed technologies, there are many security issues as well that result in breaches of data privacy with serious impact including legal and reputational implications. To deal with such threats, government agencies need to thoughtfully improve their security defences to protect data and systems by using automation and artificial intelligence (AI), as well as easing the data security measures including early warning of threats and detection. This study provides a comprehensive view of AI and automaton to highlight challenges and issues concerning data security and suggests steps to combat the issues. The authors demonstrate the role of AI-driven security tools and automation to mitigate the impact of data breaches to also propose recommendations for government agencies to enhance their data security protection.


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