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Introduction. The most significant problem is the early diagnosis of skin melanoma (SM). In many countries of the world, there is a constant increase in the incidence rate, and the organization of population screening can help solve this problem. Purpose of the study. Evaluation of the use of multi-agent technology in the diagnosis of SM. Material and methods. Study design: at the 1st stage, primary medical documentation was studied - Charts No. 090/y; 027-2/y, statistical reports of the Samara Regional Clinical Oncological Dispensary - Charts No. 7, No. 35, according to the results revealed at stage 2. There was developed and implemented multi-agent technology for SM diagnostics, including various agents of both qualified and specialized levels, these were both individuals and teams of departments who worked in close contact: a public relations agent; artificial intelligence secondary prevention planning agent; agent for training doctors and nurses, patients in the basics of early diagnosis and assessing their level of training; an agent for evaluating performance indicators. Results. After introducing the multi-agent system, the indicator of the share of 1-2 stages of MC in 2010-2019. increased by 48.3% compared to the period 2000-2009 and outpaced the growth in the total number of patients with SM by 6.96%; from 2010 to 2019 the proportion of patients with SM who were actively identified began to increase; one-year mortality rate from 2010 to 2019 decreased in waves (y = 0.0003x5 - 0.0104x4 - 0.2647x3 + 1.4818x2 - 1.8942x + 10.585; R2 = 0.554). Conclusion. The use of multi-agent technology makes it possible to reduce the one-year mortality rate, to achieve a faster growth rate of the newly detected number of patients with an early stage of SM (stage 1-2) compared to the increase in the number of cases, to improve the indicators of early diagnosis, active detection of skin melanoma, which is a positive result.

In order to solve the problems of low security and response efficiency and slow running speed of the current designed higher education system, a higher education system based on artificial intelligence technology is designed. Firstly, according to the characteristics of artificial intelligence technology, intelligent teaching system, agent technology, and data mining technology are introduced in detail. Then it analyzes the overall and detailed functional requirements of the system and adaptively generates knowledge content and teaching mode suitable for students’ ability and personality by using intelligent reasoning ability and the collection and analysis of students’ personality characteristics. Through data mining of intelligent teaching system, the decision tree about curriculum is obtained, and the students’ cognitive ability is calculated. Based on the theory of cognitive science, using the “double master” teaching mode, combined with agent technology and intelligent teaching system, the system function is divided into six modules. Through the design of database structure and data table, the design of higher education system based on artificial intelligence technology is realized. The experimental results show that the proposed method has high security and response efficiency, fast running speed, and good teaching effect.

This article aims to identify and analyse the factors that impact the adoption of intelligent agent technology (IAT) in the food supply chain (FSC). The research was conducted based on 329 respondents from various hotels and the theoretical framework adopted in this study, that is, technological, organizational and environmental (TOE) framework. The findings indicated that multiple factors in TOE contribute significantly to the adoption of IAT. We have validated the proposed framework by structural equation modelling utilizing AMOS 22.0. This research offers a new and vital paradigm for adopting this innovation in the FSC, thereby increasing the overall efficiency of a hotel. The proposed TOE framework has identified several factors like relative advantage, reliability, complexity, cost, innovation adoption, top management support, skilled employees, IT awareness, environmental uncertainty, competitive pressure, information intensity and supplier’s pressure, which helps in the adoption process of IAT in the FSC. It also provides a foundation for future research and significant insights to adopt this new technology in the hotel industry.

BACKGROUND: Melanoma — is a tumor that in most cases affects the skin and is characterized by an extremely aggressive course and a steadily increasing morbidity in the world. However, diagnosed at an early stage, cutaneous melanoma (CM) has a good prognosis with correct treatment. The results of the diagnosis of CM can be improved by joint the efforts of dermatologists and artificial intelligence (AI). AIM: Cutaneous melanoma is a tumor with an unpredictable course. The article discusses ways to solve the problem of early diagnosis using multi-agent technology and an expert system based on AI. MATERIALS AND METHODS: In a large industrial city with more than three million population, a three-day campaign for the early diagnostics of cutaneous melanoma was carried out, which revealed 4 cases of CM (4.35%) at pT1a stage in 96 patients registered in 2019. A total of 800 people were examined. RESULTS: As a result of diagnostics, the following data were obtained: specificity of self-diagnostics of the region was 6.78% by the inhabitants, 78.89% by dermatologists, and 95.24% by expert oncologists. In prospective quality control of diagnostics within 6 months, such parameters as the sensitivity of diagnosing cutaneous melanoma by oncologists and dermatologists were both 100%. As a result of the study, it was found that the multi-agent technology is necessary to improve the results of CM diagnostics, and also for a more complete assessment of the onco-epidemiological situation, and for forecasting of the necessary resources in the region. CONCLUSIONS: The multi-agent technology can improve diagnostic results, but for a more complete assessment of the onco-epidemiological situation, a large-scale population screening in the region is required.

With the development, almost all the sectors, countries tend to grow adapting to latest technologies. The transport sector also has a huge impact on this development sphere. When it comes to traffic, it is a huge problem in the world. In Sri Lanka traffic is a problem that exists for a long period. Annually there is a loss of Rs. 400 billion due to traffic congestions. Over the past years various solutions have been proposed using different methods for traffic control. These solutions are based on different trending technologies such as machine learning, image processing, fuzzy logic and the Internet of Things. However, those systems are not able to handle traffic congestions problems in complex environments. Therefore, a real-time traffic controlling system with the ability to handle traffic congestions in dynamic environment is highly valued. This study aims to design and build a real-time traffic management system using Multi Agent technology. Simulations for both existing system and Agent-Based system are implemented using NetLogo simulation tool and compared for various traffic situations. According to the results obtained from the two simulations, Agent-Based systems provide more accuracy and efficiency than the existing fixed scheduling systems.

Maritime safety is an ongoing process in shipping that is constantly being improved by the modernization of equipment and constant improvements in operators’ safety procedures and training. However, human error remains a significant factor in maritime accidents, as it contributes to 75% of incidents. Addressing this problem, the current paper shows a proof of principal for on-board fire monitoring and extinguishing software agents that may be used to upgrade present systems and contribute to an autonomous ship design. Agent technology that engages fire detection and firefighting equipment while minimizing human intervention will reduce the risks of human error and increase maritime safety.