Search results for: agent systems

Authors: Fatéma Zahra Benchara, Mohamed Youssfi, Omar Bouattane, Hassan Ouajji, Mohamed Ouadi Bensalah

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In this paper, we propose a new distributed environment for High Performance Computing (HPC) based on mobile agents. It allows us to perform parallel programs execution as distributed one over a flexible grid constituted by a cooperative mobile agent team works. The distributed program to be performed is encapsulated on team leader agent which deploys its team workers as Agent Virtual Processing Unit (AVPU). Each AVPU is asked to perform its assigned tasks and provides the computational results which make the data and team works tasks management difficult for the team leader agent and that influence the performance computing. In this work we focused on the implementation of the Mobile Provider Agent (MPA) in order to manage the distribution of data and instructions and to ensure a load balancing model. It grants also some interesting mechanisms to manage the others computing challenges thanks to the mobile agents several skills.

Keywords: image processing, distributed environment, mobile agents, parallel and distributed computing

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Authors: Hilary Rutto

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Leaching with acids are the most commonly reagents used to remove copper ions from its copper ores. It is important that the process conditions are optimized to improve the leaching efficiency. In the present study the effects of pH, oxidizing agent (hydrogen peroxide), stirring speed, solid to liquid ratio and acid concentration on the leaching of copper ions from it ore were investigated using a pH Stat apparatus. Copper ions were analyzed at the end of each experiment using Atomic Absorption (AAS) machine. Results showed that leaching efficiency improved with an increase in acid concentration, stirring speed, oxidizing agent, pH and decreased with an increase in the solid to liquid ratio.

Keywords: leaching, copper, oxidizing agent, pH stat apparatus

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Authors: Ayman M. Mansour

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In this paper, we propose a multi-agent intelligent system that is used for monitoring the health conditions of elderly people. Monitoring the health condition of elderly people is a complex problem that involves different medical units and requires continuous monitoring. Such expert system is highly needed in rural areas because of inadequate number of available specialized physicians or nurses. Such monitoring must have autonomous interactions between these medical units in order to be effective. A multi-agent system is formed by a community of agents that exchange information and proactively help one another to achieve the goal of elderly monitoring. The agents in the developed system are equipped with intelligent decision maker that arms them with the rule-based reasoning capability that can assist the physicians in making decisions regarding the medical condition of elderly people.

Keywords: fuzzy logic, inference system, monitoring system, multi-agent system

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Authors: Sagir M. Yusuf, Chris Baber

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In this paper, we describe how Bayesian inferential reasoning will contributes in obtaining a well-satisfied prediction for Distributed Constraint Optimization Problems (DCOPs) with uncertainties. We also demonstrate how DCOPs could be merged to multi-agent knowledge understand and prediction (i.e. Situation Awareness). The DCOPs functions were merged with Bayesian Belief Network (BBN) in the form of situation, awareness, and utility nodes. We describe how the uncertainties can be represented to the BBN and make an effective prediction using the expectation-maximization algorithm or conjugate gradient descent algorithm. The idea of variable prediction using Bayesian inference may reduce the number of variables in agents’ sampling domain and also allow missing variables estimations. Experiment results proved that the BBN perform compelling predictions with samples containing uncertainties than the perfect samples. That is, Bayesian inference can help in handling uncertainties and dynamism of DCOPs, which is the current issue in the DCOPs community. We show how Bayesian inference could be formalized with Distributed Situation Awareness (DSA) using uncertain and missing agents’ data. The whole framework was tested on multi-UAV mission for forest fire searching. Future work focuses on augmenting existing architecture to deal with dynamic DCOPs algorithms and multi-agent information merging.

Keywords: DCOP, multi-agent reasoning, Bayesian reasoning, swarm intelligence

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Authors: Muhamad Azani Yahya, Umi Nadiah Nor Ali, Mohammed Alias Yusof, Norazman Mohamad Nor, Vikneswaran Munikanan

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In construction, concrete is one of the materials that can commonly be used as for structural elements. Concrete consists of cement, sand, aggregate and water. Concrete can be added with admixture in the wet condition to suit the design purpose such as to prolong the setting time to improve workability. For strength improvement, concrete is being added with other hybrid materials to increase strength; this is because the tensile strength of concrete is very low in comparison to the compressive strength. This paper shows the usage of a waterproofing agent in concrete to enhance the tensile strength. High tensile concrete is expensive because the concrete mix needs fiber and also high cement content to be incorporated in the mix. High tensile concrete being used for structures that are being imposed by high impact dynamic load such as blast loading that hit the structure. High tensile concrete can be defined as a concrete mix design that achieved 30%-40% tensile strength compared to its compression strength. This research evaluates the usage of a waterproofing agent in a concrete mix as an element of reinforcement to enhance the tensile strength. According to the compression and tensile test, it shows that the concrete mix with a waterproofing agent enhanced the mechanical properties of the concrete. It is also show that the composite concrete with waterproofing is a high tensile concrete; this is because of the tensile is between 30% and 40% of the compression strength. This mix is economical because it can produce high tensile concrete with low cost.

Keywords: high tensile concrete, waterproofing agent, concrete, rheology

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Authors: Ogar Ofut Tumenayu, Olga Shabalina

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This paper describes the application of two types of pedagogical agents’ technology with different functions in an adaptive educational game with the sole aim of improving learning and enhancing interactivities in Digital Educational Games (DEG). This idea could promote the elimination of some problems of DEG, like isolation in game-based learning, by introducing a tutor and tutee pedagogical agents. We present an analysis of a learning companion interacting in a peer tutoring environment as a step toward improving social interactions in the educational game environment. We show that tutor and tutee agents use different interventions and interactive approaches: the tutor agent is engaged in tracking the learner’s activities and inferring the learning state, while the tutee agent initiates interactions with the learner at the appropriate times and in appropriate manners. In order to provide motivation to prevent mistakes and clarity a game task, the tutor agent uses the help dialog tool to provide assistance, while the tutee agent provides collaboration assistance by using the hind tool. We presented our idea on a prototype game called “Pyramid Programming Game,” a 2D game that was developed using Libgdx. The game's Pyramid component symbolizes a programming task that is presented to the player in the form of a puzzle. During gameplay, the Agents can instruct, direct, inspire, and communicate emotions. They can also rapidly alter the instructional pattern in response to the learner's performance and knowledge. The pyramid must be effectively destroyed in order to win the game. The game also teaches and illustrates the advantages of utilizing educational agents such as TrA and TeA to assist and motivate students. Our findings support the idea that the functionality of a pedagogical agent should be dualized into an instructional and learner’s companion agent in order to enhance interactivity in a game-based environment.

Keywords: tutor agent, tutee agent, learner’s companion interaction, agent collaboration

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Authors: Mohamed R. Mhereeg

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The paper discusses the implementation of the MultiAgent classification System (MACS) and utilizing it to provide an automated and accurate classification of end users developing applications in the spreadsheet domain. However, different technologies have been brought together to build MACS. The strength of the system is the integration of the agent technology with the FIPA specifications together with other technologies, which are the .NET widows service based agents, the Windows Communication Foundation (WCF) services, the Service Oriented Architecture (SOA), and Oracle Data Mining (ODM). Microsoft's .NET windows service based agents were utilized to develop the monitoring agents of MACS, the .NET WCF services together with SOA approach allowed the distribution and communication between agents over the WWW. The Monitoring Agents (MAs) were configured to execute automatically to monitor excel spreadsheets development activities by content. Data gathered by the Monitoring Agents from various resources over a period of time was collected and filtered by a Database Updater Agent (DUA) residing in the .NET client application of the system. This agent then transfers and stores the data in Oracle server database via Oracle stored procedures for further processing that leads to the classification of the end user developers.

Keywords: MACS, implementation, multi-agent, SOA, autonomous, WCF

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Authors: Georgi Y. Georgiev, Matthew Brouillet

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This research applies the power of agent-based modeling to a pivotal question at the intersection of biology, computer science, physics, and complex systems theory about the self-organization processes in open, complex, non-equilibrium thermodynamic systems. Central to this investigation is the principle of Maximum Entropy Production (MEP). This principle suggests that such systems evolve toward states that optimize entropy production, leading to the formation of structured environments. It is hypothesized that guided by the least action principle, open thermodynamic systems identify and follow the shortest paths to transmit energy and matter, resulting in maximal entropy production, internal structure formation, and a decrease in internal entropy. Concurrently, it is predicted that there will be an increase in system information as more information is required to describe the developing structure. To test this, an agent-based model is developed simulating an ant colony's formation of a path between a food source and its nest. Utilizing the Netlogo software for modeling and Python for data analysis and visualization, self-organization is quantified by calculating the decrease in system entropy based on the potential states and distribution of the ants within the simulated environment. External entropy production is also evaluated for information increase and efficiency improvements in the system's action. Simulations demonstrated that the system begins at maximal entropy, which decreases as the ants form paths over time. A range of system behaviors contingent upon the number of ants are observed. Notably, no path formation occurred with fewer than five ants, whereas clear paths were established by 200 ants, and saturation of path formation and entropy state was reached at populations exceeding 1000 ants. This analytical approach identified the inflection point marking the transition from disorder to order and computed the slope at this point. Combined with extrapolation to the final path entropy, these parameters yield important insights into the eventual entropy state of the system and the timeframe for its establishment, enabling the estimation of the self-organization rate. This study provides a novel perspective on the exploration of self-organization in thermodynamic systems, establishing a correlation between internal entropy decrease rate and external entropy production rate. Moreover, it presents a flexible framework for assessing the impact of external factors like changes in world size, path obstacles, and friction. Overall, this research offers a robust, replicable model for studying self-organization processes in any open thermodynamic system. As such, it provides a foundation for further in-depth exploration of the complex behaviors of these systems and contributes to the development of more efficient self-organizing systems across various scientific fields.

Keywords: complexity, self-organization, agent based modelling, efficiency

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Authors: Hiroyuki Aoki

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The optoacoustic effect is the energy conversion phenomenon from light to sound. In recent years, this optoacoustic effect has been utilized for an imaging agent to visualize a tumor site in a living body. The optoacoustic imaging agent absorbs the light and emits the sound signal. The sound wave can propagate in a living organism with a small energy loss; therefore, the optoacoustic imaging method enables the molecular imaging of the deep inside of the body. In order to improve the imaging quality of the optoacoustic method, the more signal intensity is desired; however, it has been difficult to enhance the signal intensity of the optoacoustic imaging agent because the fundamental mechanism of the signal generation is unclear. This study deals with the mechanism to generate the sound wave signal from the optoacoustic imaging agent following the light absorption by experimental and theoretical approaches. The optoacoustic signal efficiency for the nano-particles consisting of metal and polymer were compared, and it was found that the polymer particle was better. The heat generation and transfer process for optoacoustic agents of metal and polymer were theoretically examined. It was found that heat generated in the metal particle rapidly transferred to the water medium, whereas the heat in the polymer particle was confined in itself. The confined heat in the small particle induces the massive volume expansion, resulting in the large optoacoustic signal for the polymeric particle agent. Thus, we showed that heat confinement is a crucial factor in designing the highly efficient optoacoustic imaging agent.

Keywords: nano-particle, opto-acoustic effect, in vivo imaging, molecular imaging

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Authors: Fouzia Qamar, Shahida Hasnain

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The objective of the present study was to evaluate the possible role of Agrobacterium tumefaciens as a possible insect biocontrol agent. Pests selected for the present challenge were adult males of Periplaneta americana and last instar larvae of Pieris brassicae and Spodoptera litura. Different ranges of bacterial doses were selected and tested to score the mortalities of the insects after 24 hours, for the lethal dose estimation studies. Mode of application for the inoculation of the bacteria, was the microinjection technique. The evaluation of the possible entomopathogenic carrying attribute of bacterial Ti plasmid, led to the conclusion that the loss of plasmid was associated with the loss of virulence against target insects.

Keywords: agrobacterium tumefaciens, toxicity assessment, biopesticidal attribute, entomopathogenic agent

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Authors: A. Arshad, M. Lehtonen. M. Humayun

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With the increasing Distributed Generation (DG) penetration, distribution systems are advancing towards the smart grid technology for least latency in tackling voltage control problem in a distributed manner. This paper proposes a Multi-agent based distributed voltage level control. In this method a flat architecture of agents is used and agents involved in the whole controlling procedure are On Load Tap Changer Agent (OLTCA), Static VAR Compensator Agent (SVCA), and the agents associated with DGs and loads at their locations. The objectives of the proposed voltage control model are to minimize network losses and DG curtailments while maintaining voltage value within statutory limits as close as possible to the nominal. The total loss cost is the sum of network losses cost, DG curtailment costs, and voltage damage cost (which is based on penalty function implementation). The total cost is iteratively calculated for various stricter limits by plotting voltage damage cost and losses cost against varying voltage limit band. The method provides the optimal limits closer to nominal value with minimum total loss cost. In order to achieve the objective of voltage control, the whole network is divided into multiple control regions; downstream from the controlling device. The OLTCA behaves as a supervisory agent and performs all the optimizations. At first, a token is generated by OLTCA on each time step and it transfers from node to node until the node with voltage violation is detected. Upon detection of such a node, the token grants permission to Load Agent (LA) for initiation of possible remedial actions. LA will contact the respective controlling devices dependent on the vicinity of the violated node. If the violated node does not lie in the vicinity of the controller or the controlling capabilities of all the downstream control devices are at their limits then OLTC is considered as a last resort. For a realistic study, simulations are performed for a typical Finnish residential medium-voltage distribution system using Matlab ®. These simulations are executed for two cases; simple Distributed Voltage Control (DVC) and DVC with optimized loss cost (DVC + Penalty Function). A sensitivity analysis is performed based on DG penetration. The results indicate that costs of losses and DG curtailments are directly proportional to the DG penetration, while in case 2 there is a significant reduction in total loss. For lower DG penetration, losses are reduced more or less 50%, while for higher DG penetration, loss reduction is not very significant. Another observation is that the newer stricter limits calculated by cost optimization moves towards the statutory limits of ±10% of the nominal with the increasing DG penetration as for 25, 45 and 65% limits calculated are ±5, ±6.25 and 8.75% respectively. Observed results conclude that the novel voltage control algorithm proposed in case 1 is able to deal with the voltage control problem instantly but with higher losses. In contrast, case 2 make sure to reduce the network losses through proposed iterative method of loss cost optimization by OLTCA, slowly with time.

Keywords: distributed voltage control, distribution system, multi-agent systems, smart grids

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Authors: Abdelhadi Adel, Kadri Ouahab

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This paper proposes a hybrid algorithm for the integration of systematic preventive maintenance policies in hybrid flow shop scheduling to minimize makespan. We have implemented a problem-solving approach for optimizing the processing time, methods based on metaheuristics. The proposed approach is inspired by the behavior of the human body. This hybridization is between a multi-agent system and inspirations of the human body, especially genetics. The effectiveness of our approach has been demonstrated repeatedly in this paper. To solve such a complex problem, we proposed an approach which we have used advanced operators such as uniform crossover set and single point mutation. The proposed approach is applied to three preventive maintenance policies. These policies are intended to maximize the availability or to maintain a minimum level of reliability during the production chain. The results show that our algorithm outperforms existing algorithms. We assumed that the machines might be unavailable periodically during the production scheduling.

Keywords: multi-agent systems, emergence, genetic algorithm, makespan, systematic maintenance, scheduling, hybrid flow shop scheduling

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Authors: X. Han, S. Duan, C. Liu, C. Zhou, W. Zhu, L. Kong

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The ionic imprinting technique refers to the three-dimensional rigid structure with the fixed pore sizes, which was formed by the binding interactions of ions and functional monomers and used ions as the template, it has a high level of recognition to the ionic template. The preparation of monolithic column by the in-situ polymerization need to put the compound of template, functional monomers, cross-linking agent and initiating agent into the solution, dissolve it and inject to the column tube, and then the compound will have a polymerization reaction at a certain temperature, after the synthetic reaction, we washed out the unread template and solution. The monolithic columns are easy to prepare, low consumption and cost-effective with fast mass transfer, besides, they have many chemical functions. But the monolithic columns have some problems in the practical application, such as low-efficiency, quantitative analysis cannot be performed accurately because of the peak shape is wide and has tailing phenomena; the choice of polymerization systems is limited and the lack of theoretical foundations. Thus the optimization of components and preparation methods is an important research direction. During the preparation of ionic imprinted monolithic columns, pore-forming agent can make the polymer generate the porous structure, which can influence the physical properties of polymer, what’ s more, it can directly decide the stability and selectivity of polymerization reaction. The compounds generated in the pre-polymerization reaction could directly decide the identification and screening capabilities of imprinted polymer; thus the choice of pore-forming agent is quite critical in the preparation of imprinted monolithic columns. This article mainly focuses on the research that when using different pore-forming agents, the impact of zinc ion imprinted monolithic column on the enrichment performance of zinc ion.

Keywords: high performance liquid chromatography (HPLC), ionic imprinting, monolithic column, pore-forming agent

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Authors: Sanjal Gavande, Thomas Mazzuchi, Shahram Sarkani

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In a complex aerospace operational environment, identifying failures in a procedure involving multiple human-machine interactions are difficult. These failures could lead to accidents causing loss of hardware or human life. The likelihood of failure further increases if operational procedures are tested for a novel system with multiple human-machine interfaces and with no prior performance data. The existing approach in the literature of reviewing complex operational tasks in a flowchart or tabular form doesn’t provide any insight into potential system failures due to human decision-making ability. To address these challenges, this research explores an agent-based simulation approach for reliability assessment and fault detection in complex human-machine systems while utilizing a human decision-making model. The simulation will predict the emergent behavior of the system due to the interaction between humans and their decision-making capability with the varying states of the machine and vice-versa. Overall system reliability will be evaluated based on a defined set of success-criteria conditions and the number of recorded failures over an assigned limit of Monte Carlo runs. The study also aims at identifying high-likelihood failure locations for the system. The research concludes that system reliability and failures can be effectively calculated when individual human and machine agent states are clearly defined. This research is limited to the operations phase of a system lifecycle process in an aerospace environment only. Further exploration of the proposed agent-based and human decision-making model will be required to allow for a greater understanding of this topic for application outside of the operations domain.

Keywords: agent-based model, complex human-machine system, human decision-making model, system reliability assessment

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Authors: Adel Sabry Eesa, Adnan Mohsin Abdulazeez Brifcani, Zeynep Orman

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Feature selection has been used in many fields such as classification, data mining and object recognition and proven to be effective for removing irrelevant and redundant features from the original data set. In this paper, a new design of distributed intrusion detection system using a combination feature selection model based on bees and decision tree. Bees algorithm is used as the search strategy to find the optimal subset of features, whereas decision tree is used as a judgment for the selected features. Both the produced features and the generated rules are used by Decision Making Mobile Agent to decide whether there is an attack or not in the networks. Decision Making Mobile Agent will migrate through the networks, moving from node to another, if it found that there is an attack on one of the nodes, it then alerts the user through User Interface Agent or takes some action through Action Mobile Agent. The KDD Cup 99 data set is used to test the effectiveness of the proposed system. The results show that even if only four features are used, the proposed system gives a better performance when it is compared with the obtained results using all 41 features.

Keywords: distributed intrusion detection system, mobile agent, feature selection, bees algorithm, decision tree

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Authors: Ujjwall Sai Sunder Uppuluri

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Group theory is a powerful tool that researchers can use to provide a structural foundation for their Agent Based Models. These Agent Based models are argued by this paper to be the future of the Social Science Disciplines. More specifically, researchers can use them to apply evolutionary theory to the study of complex social systems. This paper illustrates one such example of how theoretically an Agent Based Model can be formulated from the application of Group Theory, Systems Dynamics, and Evolutionary Biology to analyze the strategies pursued by states to mitigate risk and maximize usage of resources to achieve the objective of economic growth. This example can be applied to other social phenomena and this makes group theory so useful to the analysis of complex systems, because the theory provides the mathematical formulaic proof for validating the complex system models that researchers build and this will be discussed by the paper. The aim of this research, is to also provide researchers with a framework that can be used to model political entities such as states on a 3-dimensional plane. The x-axis representing resources (tangible and intangible) available to them, y the risks, and z the objective. There also exist other states with different constraints pursuing different strategies to climb the mountain. This mountain’s environment is made up of risks the state faces and resource endowments. This mountain is also layered in the sense that it has multiple peaks that must be overcome to reach the tallest peak. A state that sticks to a single strategy or pursues a strategy that is not conducive to the climbing of that specific peak it has reached is not able to continue advancement. To overcome the obstacle in the state’s path, it must innovate. Based on the definition of a group, we can categorize each state as being its own group. Each state is a closed system, one which is made up of micro level agents who have their own vectors and pursue strategies (actions) to achieve some sub objectives. The state also has an identity, the inverse being anarchy and/or inaction. Finally, the agents making up a state interact with each other through competition and collaboration to mitigate risks and achieve sub objectives that fall within the primary objective. Thus, researchers can categorize the state as an organism that reflects the sum of the output of the interactions pursued by agents at the micro level. When states compete, they employ a strategy and that state which has the better strategy (reflected by the strategies pursued by her parts) is able to out-compete her counterpart to acquire some resource, mitigate some risk or fulfil some objective. This paper will attempt to illustrate how group theory combined with evolutionary theory and systems dynamics can allow researchers to model the long run development, evolution, and growth of political entities through the use of a bottom up approach.

Keywords: complex systems, evolutionary theory, group theory, international political economy

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Authors: Wafa Ghonaim

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Though quite fast on growth, Islamic financing at large, and its diverse instruments, is a controversial matter among scholars. This is evident from the ongoing debates on its Shariah compliance. Arguments, however, are inciting doubts and concerns among clients about its credibility, which is harming this lucrative sector. The work here investigates, particularly, some issues related to the Tawarruq instrument. The work examines the issues of linking Murabaha and Wakala contracts, the reselling of commodities to same traders, and the transfer of ownerships. The work affirms that a multi-agent smart electronic market design would facilitate Shariah compliance. The smart market exploits the rational decision-making capabilities of autonomous proxy agents that enable the clients, traders, brokers, and the bank buy and sell commodities, and manage transactions and cash flow. The smart electronic market design delivers desirable qualities that terminate the need for Wakala contracts and the reselling of commodities to the same traders. It also resolves the ownership transfer issues by allowing stakeholders to trade independently. The bank administers the smart electronic market and assures reliability of trades, transactions and cash flow. A multi-agent simulation is presented to validate the concept and processes. We anticipate that the multi-agent smart electronic market design would deliver Shariah compliance of personal financing to the aspiration of scholars, banks, traders and potential clients.

Keywords: Islamic finance, share'ah compliance, smart electronic markets design, multiagent systems

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Authors: Masayuki Higashino, Toshiya Kawato, Takao Kawamura

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A monolithic service is based on the N-tier architecture in many cases. In order to divide a monolithic service into microservices, it is necessary to redefine a model as a new microservice by extracting and merging existing models across layers. Refactoring a monolithic service into microservices requires advanced technical capabilities, and it is a difficult way. This paper proposes a design and concept to ease the migration of a monolithic service to microservices using the mobile agent technology. Our proposed approach, mobile agents-based design and concept, enables to ease dividing and merging services.

Keywords: mobile agent, microservice, web service, distributed system

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Authors: Muhammad Al Rizqi Dharma Fauzi, Dwi Yulian Fahruddin Shah, Andre Pratama, Ari Hasna Widyapuspa, Ganden Supriyanto

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Diabetes mellitus is still known as one of diseases which give a big amount of death in the world. From 2012 to 2014, diabetes is estimated to have resulted in 1.5 to 4.9 million deaths each year. In this paper, we present our research in the analysis and dose determination of Tenebrio molitor (Mealworm) extract as an anti-diabetic agent which is believed by Indonesian people as a traditional treatment to prevent and treat diabetes. We found that Tenebrio molitor extract has a potential as an anti-diabetic agent by in vitro test to Mus musculus which were divided into six group of treatment. Our dose determination analysis gave a conclusion that at 2,5 g/mL of concentration of the extract would give the optimal result in healing a wound given to Mus musculus which were induced by aloxane monohydrate. These results show that Tenebrio molitor extract is potential to be used as an Anti-Diabetic agent.

Keywords: diabetes, extraction, Tenebrio molitor, traditional medicine

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Authors: Sina Saadati, Mohammadreza Razzazi

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Since Java is an object-oriented language, It can be used to solve a wide range of problems. One of the considerable usages of this language can be found in Agent-based modeling and simulation. Despite the significant power of Java, There is not an easy method to render a 3-dimensional human model. In this article, we are about to develop a library which helps modelers present a 3D human model and control it with Java. The library runs two server programs. The first one is a web page server that can connect to any browser and present an HTML code. The second server connects to the browser and controls the movement of the model. So, the modeler will be able to develop a simulation and display a good-looking human model without any knowledge of any graphical tools.

Keywords: agent-based modeling and simulation, human model, graphics, Java, distributed systems

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Authors: Javad Khazaei, Rick Blum

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Distributed control is an efficient and flexible approach for coordination of multi-agent systems. One of the main challenges in designing a distributed controller is identifying the governing dynamics of the dynamical systems. Data-driven system identification is currently undergoing a revolution. With the availability of high-fidelity measurements and historical data, model-free identification of dynamical systems can facilitate the control design without tedious modeling of high-dimensional and/or nonlinear systems. This paper develops a distributed control design using consensus theory for linear and nonlinear dynamical systems using sparse identification of system dynamics. Compared with existing consensus designs that heavily rely on knowing the detailed system dynamics, the proposed model-free design can accurately capture the dynamics of the system with available measurements and input data and provide guaranteed performance in consensus and tracking problems. Heterogeneous damped oscillators are chosen as examples of dynamical system for validation purposes.

Keywords: consensus tracking, distributed control, model-free control, sparse identification of dynamical systems

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Authors: Hiroyuki Aoki

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Molecular imaging has attracted much attention recently, which visualizes biological molecules, cells, tissue, and so on. Among various in vivo imaging techniques, the fluorescence imaging method has been widely employed as a useful modality for small animals in pre-clinical researches. However, the higher signal intensity is needed for highly sensitive in vivo imaging. The objective of the current study is the development of a fluorescent imaging agent with high brightness for the tumor imaging of a mouse. The strategy to enhance the fluorescence signal of a bio-imaging agent is the increase of the absorption of the excitation light and the fluorescence conversion efficiency. We developed a nano-particle fluorescence imaging agent consisting of a π-conjugated polymer emitting a fluorescence signal in a near infrared region. A large absorption coefficient and high emission intensity at a near infrared optical window for biological tissue enabled highly sensitive in vivo imaging with a tumor-targeting ability by an EPR (enhanced permeation and retention) effect. The signal intensity from the π-conjugated fluorescence imaging agent is larger by two orders of magnitude compared to a quantum dot, which has been known as the brightest imaging agent. The π-conjugated polymer nano-particle would be a promising candidate in the in vivo imaging of small animals.

Keywords: fluorescence, conjugated polymer, in vivo imaging, nano-particle, near-infrared

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Authors: Umarov Jamshid, Ju-Su Kim, Hak-Jun Lee, Man-Kyo Han, Ryum-Duck Oh

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Recently, it becomes convenient to identify the location information of cargos by using GPS and wireless communication technologies. The development of IoT technologies and tracking system allows us to confirm site situation on an ad hoc basis in all the industries and social environments. Moreover, it allows us to apply IT technologies to a manageable extent. However, there have been many limitations for using the system due to the difficulty of identifying location information in real time and also due to the simple features. To globalize the logistics related tracking system, it is required to conduct a study to resolve the aforementioned problem. On that account, this paper designed and developed the IoT and RTLS based intelligent multi tracking agent system for more secure, accurate and reliable transportation in relation to logistics.

Keywords: GPS, tracking agent system, IoT, RTLS, Logistics

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Authors: Sagir M. Yusuf, Chris Baber

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We describe issues bedeviling the coordination of heterogeneous (different sensors carrying agents) multi-agent missions such as belief conflict, situation reasoning, etc. We applied Bayesian and agents' presumptions inferential reasoning to solve the outlined issues with the heterogeneous multi-agent belief variation and situational-base reasoning. Bayesian Belief Network (BBN) was used in modeling the agents' belief conflict due to sensor variations. Simulation experiments were designed, and cases from agents’ missions were used in training the BBN using gradient descent and expectation-maximization algorithms. The output network is a well-trained BBN for making inferences for both agents and human experts. We claim that the Bayesian learning algorithm prediction capacity improves by the number of training data and argue that it enhances multi-agents robustness and solve agents’ sensor conflicts.

Keywords: distributed constraint optimization problem, multi-agent system, multi-robot coordination, autonomous system, swarm intelligence

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Authors: G. B. Hong

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Liquid-Liquid Equilibrium (LLE) data are measured for the ternary mixtures of water + 1-butanol + butyl acetate and quaternary mixtures of water + 1-butanol + butyl acetate + glycerol at atmospheric pressure at 313.15 K. In addition, isothermal Vapor–Liquid–Liquid Equilibrium (VLLE) data are determined experimentally at 333.15 K. The region of heterogeneity is found to increase as the hydrophilic agent (glycerol) is introduced into the aqueous mixtures. The experimental data are correlated with the NRTL model. The predicted results from the solution model with the model parameters determined from the constituent binaries are also compared with the experimental values.

Keywords: LLE, VLLE, hydrophilic agent, NRTL

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Authors: Edward W. Staley, Corban G. Rivera, Ashley J. Llorens

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Advances in reinforcement learning (RL) have resulted in recent breakthroughs in the application of artificial intelligence (AI) across many different domains. An emerging landscape of development environments is making powerful RL techniques more accessible for a growing community of researchers. However, most existing frameworks do not directly address the problem of learning in complex operating environments, such as dense urban settings or defense-related scenarios, that incorporate distributed, heterogeneous teams of agents. To help enable AI research for this important class of applications, we introduce the AI Arena: a scalable framework with flexible abstractions for distributed multi-agent reinforcement learning. The AI Arena extends the OpenAI Gym interface to allow greater flexibility in learning control policies across multiple agents with heterogeneous learning strategies and localized views of the environment. To illustrate the utility of our framework, we present experimental results that demonstrate performance gains due to a distributed multi-agent learning approach over commonly-used RL techniques in several different learning environments.

Keywords: reinforcement learning, multi-agent, deep learning, artificial intelligence

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Authors: Ratchanon Boonachathong, Bordin Kaewnok, Suksun Amornraksa

Abstract:

Rigid polyurethane foam (RPUF) used for imitation wood is typically prepared by using 1-Dichloro-1-fluoroethane (HCFC-141b) as a blowing agent. However, this chemical is a hydrofluorocarbon which severely causes ozone depletion to the atmosphere. In this work, a more environmental-friendly RPUF was prepared by using distilled water and cyclopentane (CP) as alternative blowing agent. Several properties of the prepared RPUF were investigated and measured such as density (kg/m³), surface hardness (shore D), and glass transition temperature (°C). It was found that when the amount of the blowing agents decreased, the foam density is increased as well as the surface hardness and glass transition temperature. The results showed that the proper amount of water and cylopentane blowing agent is around 0.3–1.2% and 0.5-1.3% respectively. And the new RPUF produced has a good potential to substitute for a conventional RPUF.

Keywords: blowing agent, cyclopentane co-blown, imitation wood, rigid polyurethane foam, surface hardness

Procedia PDF Downloads 138

Authors: Djamel Saba, Fatima Zohra Laallam, Brahim Berbaoui

Abstract:

This paper presents a contribution to the design of a multi-agent for the energy management system in a hybrid energy system (SEH). The multi-agent-based energy-coordination management system (MA-ECMS) is based mainly on coordination between agents. The agents share the tasks and exchange information through communications protocols to achieve the main goal. This intelligent system can fully manage the consumption and production or simply to make proposals for action he thinks is best. The initial step is to give a presentation for the system that we want to model in order to understand all the details as much as possible. In our case, it is to implement a system for simulating a process control of energy management.

Keywords: communications protocols, control process, energy management, hybrid energy system, modelization, multi-agents system, simulation

Procedia PDF Downloads 296

Authors: Saadia Drissi

Abstract:

The cloud computing is an innovative paradigm that introduces several changes in technology that have resulted a new ways for cloud providers to deliver their services to cloud consumers mainly in term of security risk assessment, thus, adapting a current risk assessment tools to cloud computing is a very difficult task due to its several characteristics that challenge the effectiveness of risk assessment approaches. As consequence, there is a need of risk assessment model adapted to cloud computing. This paper requires a new risk assessment model based on multi-agent system and AHP model as fundamental steps towards the development of flexible risk assessment approach regarding cloud consumers.

Keywords: cloud computing, risk assessment model, multi-agent system, AHP model, cloud consumer

Procedia PDF Downloads 518

Authors: Hyeongbok Kim, Lingling Zhao, Xiaohong Su

Abstract:

Deep reinforcement learning has been applied to address various problems in robotics, such as autonomous driving and unmanned aerial vehicle. However, because of the sparse reward penalty for a collision with obstacles during the navigation mission, the agent fails to learn the optimal policy or requires a long time for convergence. Therefore, using obstacles and enemy agents, in this paper, we present a curriculum-based boost learning method to effectively train compound skills during multi-agent reinforcement learning. First, to enable the agents to solve challenging tasks, we gradually increased learning difficulties by adjusting reward shaping instead of constructing different learning environments. Then, in a benchmark environment with static obstacles and moving enemy agents, the experimental results showed that the proposed curriculum learning strategy enhanced cooperative navigation and compound collision avoidance skills in uncertain environments while improving learning efficiency.

Keywords: curriculum learning, hard exploration, multi-agent reinforcement learning, robotic navigation, sparse reward

Procedia PDF Downloads 66