scholarly journals Intellectual technology for computation control in the package of applied microservices

2019 ◽  
Author(s):  
I.V. Bychkov ◽  
G.A. Oparin ◽  
V.G. Bogdanova ◽  
A.A. Pashinin
Keyword(s):  
Qualitative Analysis ◽  
Dynamic System ◽  
Computational Model ◽  
Large Scale ◽  
Multi Agent System ◽  
Loosely Coupled ◽  
Computational Environment ◽  
Automated Technology ◽  
Multi Agent ◽  
Decentralized Management

The complexity of exhaustive problems with the properties of large-scale, openness, unpredictable dynamics, and component mobility determines the relevance of developing microservice-oriented software for their solving in a hybrid computational environment. We propose an approach for adapting to this environment both the existing software and new ones developed using new automated technology for creating an applied microservice package and organizing control of computations in it. The distributed computational model is represented by a set of small, loosely coupled, replaceable, interacting with the use of lightweight communication mechanisms autonomous microservices that implement the functions of the program package modules. The decentralized management of the microservices interaction is carried out by a self-organizing multi-agent system, agents of which are delegated the rights to launch microservices. The paper discusses the models, methods, and software platform that form the basis of the proposed technology. We demonstrate the application of the applied microservice package, based on this technology, for solving the problems of qualitative analysis of binary dynamic system using the author's Boolean constraints method.

Modernization of Healthcare and Medical Diagnosis System Using Multi Agent System (MAS)

2013 ◽  
pp. 592-622
Author(s):  
Shibakali Gupta ◽  
Sripati Mukherjee ◽  
Sesa Singha Roy
Keyword(s):  
Healthcare System ◽  
Appropriate Technology ◽  
Multi Agent System ◽  
Agent System ◽  
Healthcare Facilities ◽  
Loosely Coupled ◽  
System A ◽  
Multi Agent ◽  
Main Components ◽  
Medical Diagnosis System

The healthcare system that prevailed some years ago was a mere pen and paper based system. A number of workers, staff, and written records were the main components of the prevailing system of healthcare. This had a number of drawbacks, and a number of mishaps occurred due to mismanagement of data and information. There was a need for development. Then, the concept of telemedicine came, which revolutionized the healthcare paradigm to a great extent. With the advancement of telemedicine, many major problems of the prevailing system were removed. But, still there were many other aspects which could be further improved to make healthcare facilities more enhanced. Keeping this in mind, the concept of Multi Agent System (MAS) was introduced in the healthcare system later. MASes are considered as the best and most appropriate technology that can be used in the development of applications in healthcare paradigm where the presence of multiple agents, heterogeneous and loosely coupled components, the data management in a dynamic and distributed environment, and multi-user collaborations are considered the most pertinent requirements for healthcare system. This chapter focuses mainly about MAS, its applications, and some systems that were developed by the authors.

Modernization of Healthcare and Medical Diagnosis System Using Multi Agent System (MAS)

2015 ◽  
pp. 1426-1455
Author(s):  
Shibakali Gupta ◽  
Sripati Mukherjee ◽  
Sesa Singha Roy
Keyword(s):  
Healthcare System ◽  
Appropriate Technology ◽  
Multi Agent System ◽  
Agent System ◽  
Healthcare Facilities ◽  
Loosely Coupled ◽  
System A ◽  
Multi Agent ◽  
Main Components ◽  
Medical Diagnosis System

The healthcare system that prevailed some years ago was a mere pen and paper based system. A number of workers, staff, and written records were the main components of the prevailing system of healthcare. This had a number of drawbacks, and a number of mishaps occurred due to mismanagement of data and information. There was a need for development. Then, the concept of telemedicine came, which revolutionized the healthcare paradigm to a great extent. With the advancement of telemedicine, many major problems of the prevailing system were removed. But, still there were many other aspects which could be further improved to make healthcare facilities more enhanced. Keeping this in mind, the concept of Multi Agent System (MAS) was introduced in the healthcare system later. MASes are considered as the best and most appropriate technology that can be used in the development of applications in healthcare paradigm where the presence of multiple agents, heterogeneous and loosely coupled components, the data management in a dynamic and distributed environment, and multi-user collaborations are considered the most pertinent requirements for healthcare system. This chapter focuses mainly about MAS, its applications, and some systems that were developed by the authors.

scholarly journals Routing Based Multi-Agent System for Network Reliability in the Smart Microgrid

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2992
Author(s):  
Niharika Singh ◽  
Irraivan Elamvazuthi ◽  
Perumal Nallagownden ◽  
Gobbi Ramasamy ◽  
Ajay Jangra
Keyword(s):  
Large Scale ◽  
Network Performance ◽  
Performance Metrics ◽  
Network Reliability ◽  
Operating Conditions ◽  
Multi Agent System ◽  
Agent System ◽  
Agent Based ◽  
Multi Agent ◽  
System Operating

Microgrids help to achieve power balance and energy allocation optimality for the defined load networks. One of the major challenges associated with microgrids is the design and implementation of a suitable communication-control architecture that can coordinate actions with system operating conditions. In this paper, the focus is to enhance the intelligence of microgrid networks using a multi-agent system while validation is carried out using network performance metrics i.e., delay, throughput, jitter, and queuing. Network performance is analyzed for the small, medium and large scale microgrid using Institute of Electrical and Electronics Engineers (IEEE) test systems. In this paper, multi-agent-based Bellman routing (MABR) is proposed where the Bellman–Ford algorithm serves the system operating conditions to command the actions of multiple agents installed over the overlay microgrid network. The proposed agent-based routing focuses on calculating the shortest path to a given destination to improve network quality and communication reliability. The algorithm is defined for the distributed nature of the microgrid for an ideal communication network and for two cases of fault injected to the network. From this model, up to 35%–43.3% improvement was achieved in the network delay performance based on the Constant Bit Rate (CBR) traffic model for microgrids.

Combat Robot Strategy Adaptation Using Multiple Learning Agents

2012 ◽  
Author(s):  
Thomas Recchia ◽  
Jae Chung ◽  
Kishore Pochiraju
Keyword(s):  
Reinforcement Learning ◽  
Robotic Systems ◽  
Multi Agent System ◽  
Learning Agents ◽  
Loosely Coupled ◽  
Reward Function ◽  
Strategy Adaptation ◽  
Agent Learning ◽  
Multi Agent ◽  
Reward Functions

As robotic systems become more prevalent, it is highly desirable for them to be able to operate in highly dynamic environments. A common approach is to use reinforcement learning to allow an agent controlling the robot to learn and adapt its behavior based on a reward function. This paper presents a novel multi-agent system that cooperates to control a single robot battle tank in a melee battle scenario, with no prior knowledge of its opponents’ strategies. The agents learn through reinforcement learning, and are loosely coupled by their reward functions. Each agent controls a different aspect of the robot’s behavior. In addition, the problem of delayed reward is addressed through a time-averaged reward applied to several sequential actions at once. This system was evaluated in a simulated melee combat scenario and was shown to learn to improve its performance over time. This was accomplished by each agent learning to pick specific battle strategies for each different opponent it faced.

scholarly journals Multi-Agent System Supporting Automated Large-Scale Photometric Computations

Entropy ◽  
2016 ◽  
Vol 18 (3) ◽  
pp. 76 ◽  
Author(s):  
Adam Sȩdziwy ◽  
Leszek Kotulski
Keyword(s):  
Large Scale ◽  
Multi Agent System ◽  
Agent System ◽  
Multi Agent

scholarly journals Methods of Protecting the Distributed Computation in Multi-Agent System

2018 ◽  
Vol 7 (3.13) ◽  
pp. 38
Author(s):  
S A. Khovanskov ◽  
K E. Rumyantsev ◽  
V S. Khovanskova
Keyword(s):  
Distributed Computing ◽  
Large Scale ◽  
Computer Network ◽  
Multi Agent System ◽  
Agent System ◽  
Distributed Computing Systems ◽  
Modeling Process ◽  
Distributed Computations ◽  
False Result ◽  
Multi Agent

Currently, there are many different approaches for organization of the distributed calculations in computer network technology grid, metacomputing (BOINC, PVM, and others).  The main drawback of most existing approaches is that they are designed to create centralized distributed computing systems. In this article we propose to organize the solution of such problems as multivariate modeling, through the creation of distributed computations in computer networks based on decentralized multi-agent system. When used as a computing environment a computer network on a large scale can cause threats to the security of distributed computing from the intruders. One of these threats is getting the calculation about the result by the attacker. A false result can leads in the modeling process to adopt is not optimal or wrong decisions. We developed a method of protecting distributed computing from the threat of receiving false result.  

"TRUE" INCIDENCE OF SKIN MELANOMA, BASED ON A MASSIVE 3-DAY EARLY DIAGNOSIS CAMPAIGN IN A BIG INDUSTRIAL CITY

2021 ◽  
pp. 71-83
Author(s):  
E.Yu. Neretin ◽  
S.Kh. Sadreeva
Keyword(s):  
Early Diagnosis ◽  
Incidence Rate ◽  
Large Scale ◽  
Multi Agent System ◽  
Skin Melanoma ◽  
True Incidence ◽  
Industrial City ◽  
Non Invasive ◽  
Official Rate ◽  
Multi Agent

Skin melanoma (SM) is a malignant tumor that is quite rarely diagnosed in Russia. However, both absolute and relative numbers (incidence) of patients with this diagnosis are growing. The trend persists for many years, but the official incidence rate does not reflect the true picture, so it is likely to be lower than the true one. The aim of the study was to calculate the assumed incidence of skin melanoma based on the data from a large-scale early diagnosis campaign. Materials and Methods. In 2019, 800 patients were examined during a 3-day campaign in the Samara region. A non-invasive diagnostic method (digital dermatoscopy), a multi-agent technology based on artificial intelligence and a proprietary technology (patent No. 2018620399, No. 2018613016) were used during the campaign. Four skin melanomas were identified at an early, pre-invasive stage. Results. Two different methods (depending on the percentage of population coverage and the campaign duration), made it possible to calculate a true indicator of the skin melanoma incidence. Conclusion. It was possible to adjust the "true" incidence rate of skin melanoma. In 2019, it ranged from 9.65 to 15.31 per 100 000 people, which is significantly higher than the official rate registered that year (8.11 per 100 000 population). Keywords: skin melanoma, true incidence, large-scale campaign, multi-agent system, skin melanoma modeling. Меланома кожи (МК) является злокачественной опухолью, которая встречается в РФ довольно редко, причем растет как абсолютное количество пациентов с данным диагнозом, так и относительное (заболеваемость). Данная тенденция стабильно сохраняется на протяжении многих лет, однако официальный показатель заболеваемости не отражает реальной картины и вполне вероятно, что он несколько ниже «истинного». Целью исследования был расчет предполагаемой заболеваемости меланомой кожи на основании данных, полученных в результате масштабной кампании по ранней диагностике. Материалы и методы. В Самарской области в 2019 г. была проведена 3-дневная кампания, которая позволила обследовать 800 обратившихся пациентов с помощью неинвазивного метода диагностики (цифровой дерматоскопии) и мультиагентной технологии, основанной на искусственном интеллекте и авторской методике (патент на изобретение № 2018620399, № 2018613016). Всего было выявлено 4 меланомы кожи на ранней, доинвазивной, стадии. Результаты. В ходе расчета по 2 различным методикам (в зависимости от процента охвата населения и продолжительности акции) был получен «истинный» показатель заболеваемости МК. Выводы. «Истинный» показатель заболеваемости МК был скорректирован и составил от 9,65 до 15,31 на 100 тыс. населения, что значительно больше официального, зарегистрированного в отчетном 2019 г. (8,11 на 100 тыс. населения). Ключевые слова: меланома кожи, «истинная» заболеваемость, масштабная кампания, мультиагентная система, моделирование заболеваемости меланомы кожи.

Solving Large-Scale Multipoint Lighting Design Problem Using Multi-Agent Environment

2011 ◽  
Vol 486 ◽  
pp. 179-182 ◽  
Author(s):  
Adam Sędziwy ◽  
Leszek Kotulski
Keyword(s):  
Computational Complexity ◽  
Design Process ◽  
Large Scale ◽  
Lighting Design ◽  
The Other ◽  
Economic Issues ◽  
Computational Environment ◽  
Multi Agent ◽  
Design Requirements ◽  
Large Systems

In the paper we focus on the problem of large-scale distribution of lighting points. Its solution is constrained by economic issues like power consumption or exploitation costs and, on the other side, by the computational complexity of design process. Multi-agent computational environment combined with graph and hypergraph representations of a problem allow meeting design requirements and objectives and, on the other hand, make the method applicable for large systems for which computational effectiveness is a crucial factor.

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