Restoration entails the development of a plan consisting of opening or closing of switches, which is called reconfiguration. This dissertation proposes the design of a fast and efficient service restoration with a load shedding method for land-based and ship systems, considering priority of customers and several other system operating constraints. Existing methods, based on centralized restoration schemes that require a powerful central computer, may lead to a single point of failure. This research uses a decentralized scheme based on agents. A group of agents created to realize a specific goal by their interactions is called a Multi-Agent System (MAS). Agents and their behaviors are developed in Java Agent DEvelopment Framework (JADE) and the power system is simulated in the Virtual Test Bed (VTB). The large-scale introduction of Distributed Generators (DGs) in distribution systems has made it increasingly necessary to develop restoration schemes considering DG. The separation of utility causes the system to decompose into electrically isolated islands with generation and load imbalance that can have severe consequences. Automated load shedding schemes are essential for systems with DGs, since the disconnection of the utility can lead to instability much faster than an operator intervention can repair. Load shedding may be the only option to maintain the island when conditions are so severe as to require correction by restoration schemes. Few algorithms have been reported for the problem of maintaining the island, even though load shedding has been reported for power systems using underrequency and under-voltage criteria. This research proposes a new operational strategy for sudden generator-load imbalance due to loss of utility that dynamically calculates the quantity of load to be shed for each island and the quantity of load that can be restored. Results presented in this dissertation are among the first to demonstrate a state-of-the-art MAS for load shedding under islanded conditions and restoration of the shed loads. The load shedding and restoration schemes developed here have behaviors that can incorporate most of the distribution topologies. Achieving service restoration with DG is complicated but new automated switch technologies and communications make MAS a better scheme than existing schemes.

Disasters especially from natural phenomena are inevitable. The affected areas recover from the aftermath of a natural disaster with the support from various agents participating in humanitarian operations. There are several domains of the operation, and distributing relief aids is one. For distribution, satisfying the demand for relief aid is important since the condition of the environment is unfavorable to affected people and resources needed for the victim’s life are scarce. However, it becomes problematic when the logistic agents believed to be work properly fail to deliver the emergency goods because of the capacity loss induced from the environment after disasters. This study was proposed to address the problem of logistic agents’ unexpected incapacity which hinders scheduled distribution. The decrease in a logistic agent’s supply capability delays<br>achieving the goal of supplying required relief goods to the affected people which further endangers them. Regarding the stated problem, this study explored the importance of<br>setting the profile of logistic agents that can survive for certain duration of times. Therefore, this research defines the “survivability” and the profile of logistic agents for surviving the last mile distribution through agent based modeling and simulation. Through simulations, this study uncovered that the logistic exercise could gain survivability with the certain number and organization of logistic agents. Proper formation of organization establish the logistics’ survivability, but excessive size can threaten the survivability.

The thesis introduces an innovative UAV detection system. The commercial UAV market is booming. Meanwhile, the risks and threats from improper UAV usages are also booming. CUAS is to protect the public and facilities. The problem is a lack of an intelligent platform which can adapt many sensors for UAV detection. The hypothesis is that, the system can track the UAV’s movement by applying the multi-agent system (MAS) to UAV route track. The experiment proves that the multi-agent system benefits for the UAV track. <br>

<div>Enhancing the capability to control a tremendous range of physical actuators and sensors, combined with wireless technology and the Internet of Things (IoT), apparel technologies play a significant role in supporting safe, comfortable and healthy living, observing each customer’s conditions. Since apparel technologies have advanced to enable humans to work as a team with the clothing they wear, the interaction between a human and apparel is further enhanced with the introduction of sensors, wireless network, and artificially intelligent techniques. A variety of wearable technologies have been developed and spread to meet the needs of customers, however, some wearable devices are considered as non-practical tech-oriented, not consumer-oriented.</div><div>The purpose of this research is to develop an apparel system which integrates intelligent autonomous agents, human-based sensors, wireless network protocol, mobile application management system and a zipper robot. This research is an augmentation to the existing research and literature, which are limited to the zipping and unzipping process without much built in intelligence. This research is to face the challenges of the elderly and people with self-care difficulties. The intent is to provide a scientific path for intelligent zipper robot systems with potential, not only to help people, but also to be commercialized.</div><div>The research develops an intelligent system to control of zippers fixed on garments, based on the profile and desire of the human. The theoretical and practical elements of developing small, integrated, intelligent zipper robots that interact with an application by using a lightweight MQTT protocol for application in the daily lives of diverse populations of people with physical challenges. The system functions as intelligent automatized garment to ensure users could positively utilize a zipper robot device to assist in putting on garments which also makes them feel comfortable wearing and interacting with the system. This research is an approach towards the “future of fashion”, and the goal is to incentivize and inspire others to develop new instances of wearable robots and sensors that help people with specific needs to live a better life.</div>

In recent years, there has been a flood of continuously changing information from a variety of web resources such as web databases, web sites, web services and programs. Online Social Networks (OSNs) represent such a field where huge amounts of information are being posted online over time. Due to the nature of OSNs, which offer a productive source for qualitative and quantitative personal information, researchers from various disciplines contribute to developing methods for extracting data from OSNs. However, there is limited research which addresses extracting data automatically. To the best of the author's knowledge, there is no research which focuses on tracking the real time changes of information retrieved from OSN profiles over time and this motivated the present work. This thesis presents different approaches for automated Data Extraction (DE) from OSN: crawler, parser, Multi Agent System (MAS) and Application Programming Interface (API). Initially, a parser was implemented as a centralized system to traverse the OSN graph and extract the profile's attributes and list of friends from Myspace, the top OSN at that time, by parsing the Myspace profiles and extracting the relevant tokens from the parsed HTML source files. A Breadth First Search (BFS) algorithm was used to travel across the generated OSN friendship graph in order to select the next profile for parsing. The approach was implemented and tested on two types of friends: top friends and all friends. In case of top friends, 500 seed profiles have been visited; 298 public profiles were parsed to get 2197 top friends' profiles and 2747 friendship edges, while in case of all friends, 250 public profiles have been parsed to extract 10,196 friends' profiles and 17,223 friendship edges. This approach has two main limitations. The system is designed as a centralized system that controlled and retrieved information of each user's profile just once. This means that the extraction process will stop if the system fails to process one of the profiles; either the seed profile (first profile to be crawled) or its friends. To overcome this problem, an Online Social Network Retrieval System (OSNRS) is proposed to decentralize the DE process from OSN through using MAS. The novelty of OSNRS is its ability to monitor profiles continuously over time. The second challenge is that the parser had to be modified to cope with changes in the profiles' structure. To overcome this problem, the proposed OSNRS is improved through use of an API tool to enable OSNRS agents to obtain the required fields of an OSN profile despite modifications in the representation of the profile's source web pages. The experimental work shows that using API and MAS simplifies and speeds up the process of tracking a profile's history. It also helps security personnel, parents, guardians, social workers and marketers in understanding the dynamic behaviour of OSN users. This thesis proposes solutions for web database processing on data extraction from OSNs by the use of parser and MAS and discusses the limitations and improvements.

Real-Time Optimization (RTO) is a family of techniques that pursue to improve the performance of chemical processes. As general scheme, the method reevaluates the process conditions in a frequent basis and tries to adjust some selected variables, taking into account the plant state, actual operational constraints and optimization objectives. Several RTO approaches have born from the academy research and industrial practices, at the same time that more applications have been implemented in real facilities. Between the main motivations to apply RTO are the dynamic of markets, the seek for quality in the process results and environmental sustainability. That is why the interest on deeply understand the phases and steps involved in an RTO application has increased in recent years. Nevertheless, the fact that most of the existing RTO systems have been developed by commercial organizations makes it difficult to meet that understanding. This work studies the nature of RTO systems from a software point of view. Software requirements for a generic system are identied. Based on that, a software architecture is proposed that could be adapted for specfic cases. Benefits of the designed architecture are listed. At the same time, the work proposes a new approach to implement that architecture as a Multi-Agent System (MAS). Two RTO system prototypes were developed then, one for a well-know academic case study and the other oriented to be used in a real unit. The benefits of the MAS approach and the architecture, for researching on the RTO field and implementation on real plants, are analyzed in the text. A sub-product of the development, a software framework covering main concepts from the RTO ontology, is proposed as well. As the framework was designed to be generic, it can be used in new applications development and extended to very specific scenarios. / Otimização em Tempo Real (OTR) é uma família de técnicas que buscam melhorar o desempenho dos processos químicos. Como esquema geral, o método reavalia frequentemente as condições do processo e tenta ajustar algumas variáveis selecionadas, levando em considera ção o estado da planta, restrições operacionais e os objetivos da otimização. Várias abordagens para OTR t^em surgido da pesquisa acadêmica e das práticas industriais, ao mesmo tempo em que mais aplicações têm sido implementadas em plantas reais. As principais motivações para aplicar OTR são: a dinâmica dos mercados, a busca de qualidade nos resultados dos processos e a sustentabilidade ambiental. É por isso que o interesse em entender as fases e etapas envolvidas em uma aplicação OTR cresceu nos últimos anos. No entanto, o fato de que a maioria dos sistemas OTR em operação foram desenvolvidos por organizações comerciais dificulta o caminho para chegar nesse entendimento. Este trabalho analisa a natureza dos sistemas OTR desde o ponto de vista do software. Os requerimentos para um sistema genérico são levantados. Baseado nisso, é proposta uma arquitetura de software que pode ser adaptada para casos específicos. Os benefícios da arquitetura projetada foram listados. Ao mesmo tempo, o trabalho propõe uma nova abordagem para implementar essa arquitetura: Sistema Multi-Agentes (SMA). Dois protótipos de sistema OTR foram desenvolvidos. O primeiro aplicado num estudo de caso bem conhecido na literatura acadêmica. O segundo voltado para ser usado em uma unidade industrial. Os benefícios da abordagem SMA e da arquitetura, tanto na pesquisa relacionada com OTR, quanto na implementação em plantas reais, são analisados no texto. Um arcabouço de software que abrange os principais conceitos da ontologia OTR é proposto como resultado derivado do desenvolvimento. O arcabouço foi projetado para ser genérico, possibilitando seu uso no desenvolvimento de novas aplicações OTR e sua extensão a cenários muito específicos.

Real-Time Optimization (RTO) is a family of techniques that pursue to improve the performance of chemical processes. As general scheme, the method reevaluates the process conditions in a frequent basis and tries to adjust some selected variables, taking into account the plant state, actual operational constraints and optimization objectives. Several RTO approaches have born from the academy research and industrial practices, at the same time that more applications have been implemented in real facilities. Between the main motivations to apply RTO are the dynamic of markets, the seek for quality in the process results and environmental sustainability. That is why the interest on deeply understand the phases and steps involved in an RTO application has increased in recent years. Nevertheless, the fact that most of the existing RTO systems have been developed by commercial organizations makes it difficult to meet that understanding. This work studies the nature of RTO systems from a software point of view. Software requirements for a generic system are identied. Based on that, a software architecture is proposed that could be adapted for specfic cases. Benefits of the designed architecture are listed. At the same time, the work proposes a new approach to implement that architecture as a Multi-Agent System (MAS). Two RTO system prototypes were developed then, one for a well-know academic case study and the other oriented to be used in a real unit. The benefits of the MAS approach and the architecture, for researching on the RTO field and implementation on real plants, are analyzed in the text. A sub-product of the development, a software framework covering main concepts from the RTO ontology, is proposed as well. As the framework was designed to be generic, it can be used in new applications development and extended to very specific scenarios. / Otimização em Tempo Real (OTR) é uma família de técnicas que buscam melhorar o desempenho dos processos químicos. Como esquema geral, o método reavalia frequentemente as condições do processo e tenta ajustar algumas variáveis selecionadas, levando em considera ção o estado da planta, restrições operacionais e os objetivos da otimização. Várias abordagens para OTR t^em surgido da pesquisa acadêmica e das práticas industriais, ao mesmo tempo em que mais aplicações têm sido implementadas em plantas reais. As principais motivações para aplicar OTR são: a dinâmica dos mercados, a busca de qualidade nos resultados dos processos e a sustentabilidade ambiental. É por isso que o interesse em entender as fases e etapas envolvidas em uma aplicação OTR cresceu nos últimos anos. No entanto, o fato de que a maioria dos sistemas OTR em operação foram desenvolvidos por organizações comerciais dificulta o caminho para chegar nesse entendimento. Este trabalho analisa a natureza dos sistemas OTR desde o ponto de vista do software. Os requerimentos para um sistema genérico são levantados. Baseado nisso, é proposta uma arquitetura de software que pode ser adaptada para casos específicos. Os benefícios da arquitetura projetada foram listados. Ao mesmo tempo, o trabalho propõe uma nova abordagem para implementar essa arquitetura: Sistema Multi-Agentes (SMA). Dois protótipos de sistema OTR foram desenvolvidos. O primeiro aplicado num estudo de caso bem conhecido na literatura acadêmica. O segundo voltado para ser usado em uma unidade industrial. Os benefícios da abordagem SMA e da arquitetura, tanto na pesquisa relacionada com OTR, quanto na implementação em plantas reais, são analisados no texto. Um arcabouço de software que abrange os principais conceitos da ontologia OTR é proposto como resultado derivado do desenvolvimento. O arcabouço foi projetado para ser genérico, possibilitando seu uso no desenvolvimento de novas aplicações OTR e sua extensão a cenários muito específicos.

In recent years, there has been a ood of continuously changing information from a variety of web resources such as web databases, web sites, web services and programs. Online Social Networks (OSNs) represent such a eld where huge amounts of information are being posted online over time. Due to the nature of OSNs, which o er a productive source for qualitative and quantitative personal information, researchers from various disciplines contribute to developing methods for extracting data from OSNs. However, there is limited research which addresses extracting data automatically. To the best of the author's knowledge, there is no research which focuses on tracking the real time changes of information retrieved from OSN pro les over time and this motivated the present work. This thesis presents di erent approaches for automated Data Extraction (DE) from OSN: crawler, parser, Multi Agent System (MAS) and Application Programming Interface (API). Initially, a parser was implemented as a centralized system to traverse the OSN graph and extract the pro- le's attributes and list of friends from Myspace, the top OSN at that time, by parsing the Myspace pro les and extracting the relevant tokens from the parsed HTML source les. A Breadth First Search (BFS) algorithm was used to travel across the generated OSN friendship graph in order to select the next pro le for parsing. The approach was implemented and tested on two types of friends: top friends and all friends. In case of top friends, 500 seed pro les have been visited; 298 public pro les were parsed to get 2197 top friends pro les and 2747 friendship edges, while in case of all friends, 250 public pro les have been parsed to extract 10,196 friends' pro les and 17,223 friendship edges. This approach has two main limitations. The system is designed as a centralized system that controlled and retrieved information of each user's pro le just once. This means that the extraction process will stop if the system fails to process one of the pro les; either the seed pro le ( rst pro le to be crawled) or its friends. To overcome this problem, an Online Social Network Retrieval System (OSNRS) is proposed to decentralize the DE process from OSN through using MAS. The novelty of OSNRS is its ability to monitor pro les continuously over time. The second challenge is that the parser had to be modi ed to cope with changes in the pro les' structure. To overcome this problem, the proposed OSNRS is improved through use of an API tool to enable OSNRS agents to obtain the required elds of an OSN pro le despite modi cations in the representation of the pro le's source web pages. The experimental work shows that using API and MAS simpli es and speeds up the process of tracking a pro le's history. It also helps security personnel, parents, guardians, social workers and marketers in understanding the dynamic behaviour of OSN users. This thesis proposes solutions for web database processing on data extraction from OSNs by the use of parser and MAS and discusses the limitations and improvements. / Taibah University

The ability to solve problems creatively has been crucial for the adaptation and survival of humans throughout history. In many real–life situations, cognitive processes are not isolated. Humans are social, they communicate and form groups to solve daily problems and make decisions. Therefore, the final output of cognitive processes can come from multi–brains in groups rather than an individual one. This multi–brain output can be largely different from the output that an individual person produces in isolation. As a result, it is essential to include team–level processes in cognitive models to make a more accurate description of real– world cognitive processes in general and problem solving in particular. This research aims to answer the general question of how working in a team affects creative problem solving. For doing that, first, we propose a computational model for multi-agent creative problem solving. Then, we show how the model can be used to study the factors that are involved in creativity in teams and potentially will suggest answers to questions such as, ‘how team size is related to creativity’.

<p dir="ltr">In multiplayer games, a collection of self-interested players aims to optimize their individual cost functions in a non-cooperative manner. The cost function of each player depends not only on its own actions but also on the actions of others. In addition, players' actions may also collectively satisfy some global constraints. The study of this problem has grown immensely in the past decades with applications arising in a wide range of societal systems, including strategic behaviors in power markets, traffic assignment of strategic risk-averse users, engagement of multiple humanitarian organizations in disaster relief, etc. Furthermore, with machine learning models playing an increasingly important role in practical applications, the robustness of these models becomes another prominent concern. Investigation into the solutions of multiplayer games and Nash equilibrium problems (NEPs) can advance the algorithm design for fitting these models in the presence of adversarial noises. </p><p dir="ltr">Most of the existing methods for solving multiplayer games assume the presence of a central coordinator, which, unfortunately, is not practical in many scenarios. Moreover, in addition to couplings in the objectives and the global constraints, all too often, the objective functions contain uncertainty in the form of stochastic noises and unknown model parameters. The problem is further complicated by the following considerations: the individual objectives of players may be unavailable or too complex to model; players may exhibit reluctance to disclose their actions; players may experience random delays when receiving feedback regarding their actions. To contend with these issues and uncertainties, in the first half of the thesis, we develop several algorithms based on the theory of operator splitting and stochastic approximation, where the game participants only share their local information and decisions with their trusted neighbors on the network. In the second half of the thesis, we explore the bandit online learning framework as a solution to the challenges, where decisions made by players are updated based solely on the realized objective function values. Our future work will delve into data-driven approaches for learning in multiplayer games and we will explore functional representations of players' decisions, in a departure from the vector form. </p>