Use Of Multi-agent Systems Research Articles

Use of multi-agent systems and the Internet of Things to monitor the environment of commercial broiler poultry houses through specific air enthalpy

The intensive production system for broilers requires the availability of an environment (aviary) that promotes an artificial microclimate that favors both animal well-being and productive performance; therefore, monitoring this environment is critical for production success, especially in tropical countries. This criticality opens up a range of research opportunities for monitoring because of the currently available technologies, especially in the areas of the Internet of Things and Expert Systems. Thus, this study presents a proposal for the environmental monitoring of an aviary using an Internet of Things technological apparatus combined with multi-agent systems to monitor climatic variables with the guidance of thermal comfort indicators. The experiment took place in a Cobb broiler aviary located in the countryside of the State of São Paulo, Brazil. With this objective in mind, the production period of Cobb broilers was analyzed through the construction of an Internet of Things system to collect air temperature, relative humidity, and atmospheric pressure variables combined with a data transfer mechanism for cloud recording. These variables were then analyzed by computational agents using the Java programming language with the Jade framework, which generated animal comfort indicators. The results showed that real-time monitoring of environmental variables is possible with the combination of the Internet of Things with agents that can determine animal comfort conditions according to the specific enthalpy of the air through the orchestration of a deliberative agent and with the participation of several reactive agents.

Use of multi-agent system for industrial production control

This paper describes specific implementation of Asset Administration Shell technology used for an industrial distributed control system. The base of this control system is a multiagent system of digital twins which was created by AAS. This multiagent system was developed for a specific platform CP Factory (mainly based on Simatic PLC) but the implementation is y portable to each common platform. Digital twin of several types of components of typical industrial production process are described in this paper with the implementation of active and passive administration shell. The main focus is on describing the way of integrating digital twins into the production system and the necessary SW tools. Industry 4.0 language was used as a common communication protocol as well as OPC UA and MQTT.

Distributed Artificial Intelligence Application in Agri-food Supply Chains 4.0

Supply Chain 4.0 is characterized by various factors, including seamless integration and connectivity, the Internet of Things (IoT), Big Data, AI participation, Cyber-Physical Systems (CPSs), flexibility, adaptability, and customer-centricity across different parts of the supply chain. The application of Distributed AI (DAI) systems like Multi-Agent Systems (MAS) opens new horizons to enhance the efficiency, responsiveness, and intelligence of these supply chains. DAI facilitates advanced autonomous decision-making and real-time optimization at different stages of the agri-food supply chain, such as demand forecasting, inventory management, production planning, logistics optimization, and quality assurance and control. This article, by focusing on the case of scheduling through the entire supply chain, examines how DAI initiatives, including Multi-Agent Systems (MASs) enhanced with Case-Based Reasoning (CBR), enable the distribution of intelligence across smart, interconnected elements of the supply chain network. It is shown that through the use of DAI in SCM, the performance of the entire supply chain optimizes consistently and adaptively through the use of MAS, in which different parts of SCM collaborate as agents. Supply Chain 4.0 can gain autonomy, self-organization, self-optimization, self-adaptation, robustness, and flexibility, and its knowledge base can be enriched over time by using CBR to learn from past situations. It also discusses the opportunities and challenges associated with the adoption of DAI in Supply Chain 4.0, including operational efficiency, cost reduction, agility enhancement, and improved customer satisfaction. However, several concerns, such as data security, privacy issues, and interoperability, must be addressed.

Decentralized control strategies for resilient power systems using multi-agent systems

The study examines the use of Multi-Agent Systems (MAS) in decentralized control mechanisms to improve the resilience of power systems. The analysis included simulations, agent interactions, and system dynamics. The results demonstrate the durability of Generator 001 in City A, as it constantly maintains an average power production of 46.5 MW. On the other hand, Generator 002 in City B regularly generates around 29 MW. Storage Unit 003 efficiently fulfills requests by distributing 15 MW upon receiving a prompt from Generator 001. The system is notably influenced by consumer behavior, as seen by Consumer 004 in City C consistently demanding 31 MW. Significantly, when Consumer 005 is activated, it increases demand to 27.5 MW. An examination of percentage variations indicates little swings in generator outputs at peak times, underscoring their stability. Nevertheless, consumer engagement during periods of high demand results in significant surges in the need for resources. The agents demonstrate effective communication by swiftly acknowledging and fulfilling requests for extra power. The results emphasize the potential of MAS as a viable framework for effectively distributing resources and coordinating various agents. This research provides useful insights into adaptive solutions for effectively managing changing power system circumstances. It highlights the crucial role of Multi-Agent Systems (MAS) in maintaining stability, maximizing the use of resources, and meeting the developing energy needs.

Exploring the Use of Multiagent Systems in Educational Robotics Activities

Multi-Agent Systems (MAS) have been demonstrated to be a useful tool for addressing complex problems by breaking them down into simpler tasks. In this paper, we explore the potential of the MAS approach in designing educational robotics learning experiences. Specifically, we aim to identify the pedagogical possibilities and technical considerations of using MAS in designing robot-based activities. We have designed three educational robotics experiences based on the MAS approach. The first experience describes the use of the MAS approach in creating a learning activity based on Multi-Robots Systems (MRS). The second experience describes the use of the MAS approach for implementing theater-based activities with MRS. Finally, the third experience outlines the implementation of an artificial cognitive architecture based on MAS to control the educational actions of an anthropomorphic social robot. The results reveal that MAS and MRS offer opportunities to design distributed learning environments with distributed artificial intelligence.

The use of multi-agent systems in an automated restoration process for power distribution networks

The capacity of future smart grids to automatically detect problems, isolate them, and restore service is a key feature. Traditional mathematical programming techniques and heuristic approaches become computationally highly expensive when used for the restoration issue, which is a comprehensive nonlinear optimization challenge. Distributed control must offer comfortable and safe power system operation and improve consumer supply quality. In this article, we suggest the multi-agent system (MAS) as the creative process that applies to the existing power distribution network. The MAS agents are installed in "Intelligent electronic devices (IEDs)" and interact with one another using open protocols from the "Foundation for Intelligent Physical Agents (FIAP)." A Java-based distribution system simulator was built to test how well MAS works. In-lab experiments were conducted with the simulator connected to the MAS. The test findings demonstrated that the MAS effectively restored healthy divides by changing them to their original configuration following a predetermined sequence, notwithstanding the system's operating limits. The suggested MAS has shown the efficacy of a distributed control method that uses in the absence of the technologies currently employed in IEDs for control and protection.

An Intelligent Decision Support System Based on Multi Agent Systems for Business Classification Problem

The development of e-systems has given consumers and businesses access to a plethora of information, which has complicated the process of decision making. Document classification is one of the main decisions that any business adopts in their decision making to categorize documents into groups according to their structure. In this paper, we combined multi-agent systems (MASs), which is one of the IDSS systems, with Bayesian-based classification to filter out the specialization, collaboration, and privacy of distributed business sources to produce an efficient distributed classification system. Bayesian classification made use of MAS to eliminate distributed sources’ specialization and privacy. Therefore, incorporating the probabilities of various sources is a practical and swift solution to such a problem, where this method works the same when all the data are merged into a single source. Each intelligent agent can collaborate and ask for help from other intelligent agents in classifying cases that are difficult to classify locally. The results demonstrate that our proposed technique is more accurate than those of the non-communicated classification, where the results proved the ability of the utilized productive distributed classification system.

Multi-agents in transport process control

Abstract. Problem The problem is computer science, car transfer, road maintenance, synergy, principles and paradigms of using car computer systems - ACS. The use of multi-agent systems in the virtual management of the transport process allows improving the quality of transport management. A multi-agent system is a collection of interacting agents that can work together to achieve a common goal. Multi-agent systems can be used for better management of logistics processes, in particular in the field of transport. The role of agents in decision-making, including in real time, is considered, which allows more accurate forecasting and control of the transport process. Goal. The goal is integration of the intelligent multi-agent system (IMAS) and agents in the task of virtual management of transport processes. Results. A program installed on a server that supports Internet functions can potentially be accessed from any workstation. This opens the way to the use of intellectual and production tools by almost all employees of the enterprise at minimal costs. The same application becomes available from any workstation connected to the Internet, which is critical for e-commerce applications. Such an opportunity opens access to applications to corporate partners for creating virtual enterprises and virtual management.

Review of Methods for Addressing Challenging Issues in the Operation of Protection Devices in Microgrids with Voltages of up to 1 kV That Integrates Distributed Energy Resources

With the large-scale integration of distributed energy resources (DER) into passive distribution networks with voltages of up to 1 kV, these networks are being converted into microgrids. When the topology and operating conditions change, several challenging issues arise related to the functioning of the protection devices (PD) that are in operation. Most DERs, including renewable generators, are integrated into microgrids by means of inverters. In the event of short circuits (SC) in microgrids, these DERs provide a fault current contribution of no more than 1.2–2.0 Irated at the fault location. This makes it difficult to identify the fault location and to carry out the selective disconnection of the faulty element by means of conventional PDs. This article provides an overview of engineering solutions for improving conventional protection schemes that have been historically used in passive distribution networks, as well as for creating modern protection schemes based on innovative principles and new methods. The use of adaptive protections built on decentralized and centralized principles in most cases ensures the reliable protection of microgrids. Modern intelligent electronic devices (IEDs), where protection functions are implemented, rank higher with respect to their technical perfection in terms of reliability, sensitivity, selectivity, and speed performance. The use of multi-agent systems in the implementation of modern protection schemes requires the availability of broadband communication channels, which hinders their use because of the high cost. The combined use of fault current limiters (FCL) and energy storage systems (ESS) allows for the reliable operation of microgrid protections. The use of modern PDs ensures the reliable operation of DERs and power supply to consumers in microgrids, both in the case of grid-connected and islanded operation modes. Since there is no unified concept of designing protection schemes for microgrids with DERs, the choice of specific approaches to the design of protection schemes should be based on the results of a comparative technical and economic analysis of different options.

GMP: A Genetic Mission Planner for Heterogeneous Multirobot System Applications.

The use of multiagent systems (MASs) in real-world applications keeps increasing, and diffuses into new domains, thanks to technological advances, increased acceptance, and demanding productivity requirements. Being able to automate the generation of mission plans for MASs is critical for managing complex missions in realistic settings. In addition, finding the right level of abstraction to represent any generic MAS mission is important for being able to provide general solution to the automated planning problem. In this article, we show how a mission for heterogeneous MASs can be cast as an extension of the traveling salesperson problem (TSP), and we propose a mixed-integer linear programming formulation. In order to solve this problem, a genetic mission planner (GMP), with a local plan refinement algorithm, is proposed. In addition, the comparative evaluation of CPLEX and GMP is presented in terms of timing and optimality of the obtained solutions. The algorithms are benchmarked on a proposed set of different problem instances. The results show that, in the presence of timing constraints, GMP outperforms CPLEX in the majority of test instances.

MULTIAGENT METHODS OF MANAGEMENT OF DISTRIBUTED COMPUTING IN HYBRID CLUSTERS

Modern information technologies include the use of server systems, virtualization technologies, communication tools for distributed computing and development of software and hardware solutions of data processing and storage centers, the most effective of such complexes for managing heterogeneous computing resources are hybrid GRID- distributed computing infrastructure combines resources of different types with collective access to these resources for and sharing shared resources. The article considers a multi-agent system that provides integration of the computational management approach for a cluster Grid system of computational type, the nodes of which have a complex hybrid structure. The hybrid cluster includes computing modules that support different parallel programming technologies and differ in their computational characteristics. The novelty and practical significance of the methods and tools presented in the article are a significant increase in the functionality of the Grid cluster computing management system for the distribution and division of Grid resources at different levels of tasks, the ability to embed intelligent computing management tools in problem-oriented applications. The use of multi-agent systems for task planning in Grid systems will solve two main problems - scalability and adaptability. The methods and techniques used today do not sufficiently provide solutions to these complex problems. Thus, the scientific task of improving the effectiveness of methods and tools for managing problem-oriented distributed computing in a cluster Grid system, integrated with traditional meta-planners and local resource managers of Grid nodes, corresponding to trends in the concept of scalability and adaptability.

Development and implementation of multi-agent systems for demand response aggregators in an industrial context

Demand Response (DR) mechanisms are an important pillar in the transition to a bigger share of renewable energy in the power grid. To utilize DR, industrial companies can offer load flexibility at DR markets by cooperating with DR aggregators. Numerous studies promote the use of multi-agent systems (MAS) in this domain, however there is a lack of actual implementations and real world adaption. The literature has identified several reasons for this. These include research that often focuses on a high level of abstraction, the assumption of homogeneous structures for the use of agents, and insufficient tools and solutions for industrial deployment. To help DR aggregators use MAS in their existing virtual power plants, this paper presents a MAS that enables a step-by-step switch to agent technology and enables them to implement the solutions developed by the research community to improve the management of their systems. The proposed technical implementation on standard industrial equipment and the required interfaces to flexibility provider and DR aggregator are derived from the German DR market requirements. A simulation of the MAS implemented on a laboratory setup via the Java Agent DEvelopment Framework will be presented. This should provide a foundation for the transition to real world adaption in the future, which will then be discussed to show the benefits and drawbacks of this solution.

Optimization of Multi Agent System for Distribution Control of Distinct Heating System Using Improved Q-Learning Controller

The aim of this research is the use of multi-agent systems for the optimization of a distributed control for district heating systems. A district heating system comprises of production units, a distribution network, and a host of consumer substations. The operations of district heating system usually involves conflicting goals, e.g., to satisfy customers and to minimize production costs. Hence the agent must be capable of optimizing between maximizing supply to substations and minimizing production cost. Current substations employ purely reactive devices, making local decisions without taking into account the global state. Moreover the substations determine the flow in all parts of the district heating system. The optimal operation of the district heating system is therefore limited to providing sufficiently high temperature and pressure to all customers by taking local measurement to achieve this goal without considering other factors such as cost of production and time. The approach studied in this research is to equip substations with software agents to form a multi-agent system using Q-learning. The study also shows that it is possible to control the trade-off between quality of service and degree of surplus production as well as the possibility of extending the system with new consumers without increasing production capacity. In another study, an experiment was conducted in a controlled physical environment, where two agent-based approaches were evaluated and compared to existing technologies. The experiment shows that it is possible to automatically load balance a small district heating network using agent technology.. Finally, a generalized formal characterization of the problem space under investigation is provided, i.e., production and logistics network management, together with a preliminary evaluation of the applicability of the suggested multi-agent system approach for this general problem area.

Multiagent System and Rainfall-Runoff Model in Hydrological Problems: A Systematic Literature Review

Typically, hydrological problems require approaches capable of describing and simulating part of the hydrological system, or the environmental consequences of natural or anthropic actions. Tools such as Multiagent System (MAS) and Rainfall-Runoff Model (RRM) have been used to help researchers to develop and better understand water systems. Thus, this study presents a Systematic Literature Review (SLR) on the joint use of MAS and RRM tools, in the context of hydrological problems. SLR was performed based on a protocol defined from the research question. Initially, 79 papers were found among six bibliographic databases. This total was reduced over four stages of selection, according to exclusion criteria. In the end, three papers were considered satisfactory within the scope of the research, where they were summarized, analyzed, and compared. While the MAS and RRM tools can interact with their results in a coupled model, SLR showed that there are still major challenges to be explored concerning the dynamics between them, as the steps of scales and validation. However, the coupling of MAS and RRM can provide an interesting alternative tool to analyse decision-making about water resources management systems.

The use of multi-agent systems for modeling technological processes

The article is devoted to the issues of using discrete simulation models for modeling some basic technological processes. In the scientific work, models in the form of multi-agent systems have been investigated, which allow us to consider a continuous environment as a set of interacting elements (agents), the behavior of which obeys local functions. The authors describe the basic techniques and general methodology for the development of deterministic agent-based models. The paper considers the use of multi-agent systems for modeling thermal conductivity, taking into account the nonlinearity of the process, in homogeneity of the material and the presence of volumetric heat sources of variable power in it. The obtained scientific results are in good agreement with the generally accepted classical approaches and do not contradict the provisions adopted in the theory of thermal phenomena.

The use of multi-agent systems in forestry

The purpose of the study is to review the current situation in the forestry sector, as well as to identify and accomplish tasks that could change the situation in this area.It focuses on the disclosure of operation principleof the multi-agent approach, as well as the identification of problem areas in forestry.The scientific novelty comes down to a promising direction in forestry that reduces the processing time of incoming information since the multi-agent approach gives a parallel process of assessing data that retrieved by an unmanned vehicle. In addition, the approach simplifies the structure of the agent’s algorithm. With that research, the technology of operation of multi-agent systems was disclosed, and examples of the application of this approach in production were presented. It is emphasized that the use of unmanned aerial vehicles with a multi-agent approach to recognition of terrain in the field of forestry will improve the quality of the data obtained, increase the amount of information received and processed, and increase the reliability of this process. The main advantages of the proposed approach are minimal control during remote use, forest resource taxation and analysis of the terrain for emergency situations.

Securing IoT Network against DDoS Attacks using Multi-agent IDS

The crucial issue of Internet of Things (IoT) is vulnerable towards various kinds of security threats, especially on denial-of-service (DoS) attacks as IoT network consists of millions of devices attached to the network. There are plenty of intrusion detection systems (IDSs) available for IoT networks, however, the accuracy detection yet still a big problem. To address the problem, this paper proposes an ensemble IDS for IoT networks. The proposed IDS uses Multi-agent System (MAS) concept and ensemble the Information Gain feature selection algorithm with J48 classifier algorithm for the proposed IDS. Experimental results show the proposed MAS-J48-IDS provides the best accuracy performance of 99.8% for all selected features compared to IDSs that use Naïve Bayesian (NB) and Random Forest (RF) classifiers. Besides, the use of MAS contributes towards the load balancing among the nodes in the network itself.

Model checking agent-based communities against uncertain group commitments and knowledge

In recent years, the use of Multi-Agent Systems (MASs) to solve complex problems has grown rapidly. Social communicative commitments have been widely employed in such systems as a means of communication allowing heterogeneous agents to cooperate. However, to prevent undesirable outcomes, communicative commitments and their interactions with agents’ knowledge need to be verified. This paper aims at verifying MASs where agents have knowledge and communicate through manipulating uncertain social commitments, especially when the scope of commitments moves beyond the common agent-to-agent scheme. We introduce a model checking method for verifying those systems and capitalize on the interaction between not only individual but also group communicative commitments and knowledge in the presence of uncertainty. System’s properties are expressed using the Probabilistic Computation Tree Logic of Knowledge and Commitment (PCTLkc+). In the proposed approach, model checking PCTLkc+ is reduced to model checking the probabilistic branching-time logic PCTL. This is achieved by transforming PCTLkc+ model to a Markov Decision Process (MDP), and reducing PCTLkc+ formulae into PCTL formulae compatible with PRISM, a reference model checking tool for probabilistic temporal systems. Thereafter, we provide the soundness and completeness proofs of the reduction technique, and compute its time complexity. The effectiveness of the proposed approach is evaluated by implementing it on top of PRISM using two concrete applications, namely Online Shopping System from the business domain, and Insurance Claim Processing from the industrial domain. The obtained results of the two case studies underscore the scientific value of our proposed framework and confirm that verifying commitment-based probabilistic epistemic MASs has become attainable by utilizing this approach. The presented work outperforms existing proposals because it considers the problem of modeling and verifying MASs where group social commitments are interacting with participating agents’ knowledge in the presence of uncertainty, which has not been addressed yet in the literature.

Efficient use of electric energy in homes through multi-agent systems, case study Monterrey N.L., Mexico

This article presents an experimental research whose objective is to verify through experimentation if the systems for air conditioning and lighting homes based on the use of Multi- Agent Systems (MAS) are more efficient than traditional systems in terms of perceived environmental comfort. by people and the electricity cost generated. The proposed methodology involved the development of a housing simulator, the definition of the “environmental comfort” variable, the description of the evaluated lighting and air conditioning systems, and the definition of the proposed experiments based on independent variables that could impact on the performance of the aforementioned systems. Based on the data obtained when conducting the experiments and taking the homes in the Monterrey Metropolitan Area as a case study, it could be observed that the use of MAS is a very good alternative to reduce the consumption of electrical energy in homes taking care of not sacrificing people's comfort, thus helping to reduce the ecological impact generated by electricity generation.

Development of a multi-agent system for solving domain dictionary construction problem

The object of research is the use of multi-agent systems for text data mining. The need for this study arose with a tendency to increase the amount of textual information generated in the world. Accordingly, it is necessary to develop and research methods of its processing, as well as ways to use the results of this processing, because the methods can’t exist in isolation from practice. At the same time, there is a development of multi-agent systems (MAS), where agents are endowed with some kind of intelligence, these systems can be easily scaled. The use of MAS for text analysis is a promising area.The following methods of text data analysis were used in this study: TF-IDF and RAKE methods, Word2Vec neural network models, and TextRank. The algorithms were compared for their work and the results were compared. The corpus of documents (10–12 texts, 5732–12331 words) from the subject areas of physics and biology were used as a test set. According to the results of the study, one method was chosen, on the basis of which the MAS was built to solve the problem. Additionally, Schulze methods (with one and several winners) were used for voting. With the received system additional researches concerning accuracy and speed of work, and also – influence are carried out system parameters for its operation.It has been found that TF-IDF-based analysis is useful for finding terms in documents with a weak context. The resulting system shows an accuracy of 75 % (3 of the 4 words proposed by the system are terms). The maximum operating time on test cases is 2–3 seconds, which is achieved through the use of parallel calculations and modification of the Schulze method. The results obtained in this paper are heuristic (ontology is a rather vague concept) and require additional elaboration by experts in the relevant fields. However, the results are positive within this experiment