Agent-based hybrid framework for decision making on complex problems

Electronic commerce and the Internet have created demand for automated systems that can make complex decisions utilizing information from multiple sources. Because the information is uncertain, dynamic, distributed, and heterogeneous in nature, these systems require a great diversity of intelligent techniques including expert systems, fuzzy logic, neural networks, and genetic algorithms. However, in complex decision making, many different components or sub-tasks are involved, each of which requires different types of processing. Thus multiple such techniques are required resulting in systems called hybrid intelligent systems. That is, hybrid solutions are crucial for complex problem solving and decision making. There is a growing demand for these systems in many areas including financial investment planning, engineering design, medical diagnosis, and cognitive simulation. However, the design and development of these systems is difficult because they have a large number of parts or components that have many interactions. From a multi-agent perspective, agents in multi-agent systems (MAS) are autonomous and can engage in flexible, high-level interactions. MASs are good at complex, dynamic interactions. Thus a multi-agent perspective is suitable for modeling, design, and construction of hybrid intelligent systems. The aim of this thesis is to develop an agent-based framework for constructing hybrid intelligent systems which are mainly used for complex problem solving and decision making. Existing software development techniques (typically, object-oriented) are inadequate for modeling agent-based hybrid intelligent systems. There is a fundamental mismatch between the concepts used by object-oriented developers and the agent-oriented view. Although there are some agent-oriented methodologies such as the Gaia methodology, there is still no specifically tailored methodology available for analyzing and designing agent-based hybrid intelligent systems. To this end, a methodology is proposed, which is specifically tailored to the analysis and design of agent-based hybrid intelligent systems. The methodology consists of six models - role model, interaction model, agent model, skill model, knowledge model, and organizational model. This methodology differs from other agent-oriented methodologies in its skill and knowledge models. As good decisions and problem solutions are mainly based on adequate information, rich knowledge, and appropriate skills to use knowledge and information, these two models are of paramount importance in modeling complex problem solving and decision making. Follow the methodology, an agent-based framework for hybrid intelligent system construction used in complex problem solving and decision making was developed. The framework has several crucial characteristics that differentiate this research from others. Four important issues relating to the framework are also investigated. These cover the building of an ontology for financial investment, matchmaking in middle agents, reasoning in problem solving and decision making, and decision aggregation in MASs. The thesis demonstrates how to build a domain-specific ontology and how to access it in a MAS by building a financial ontology. It is argued that the practical performance of service provider agents has a significant impact on the matchmaking outcomes of middle agents. It is proposed to consider service provider agents\u27 track records in matchmaking. A way to provide initial values for the track records of service provider agents is also suggested. The concept of ‘reasoning with multimedia information’ is introduced, and reasoning with still image information using symbolic projection theory is proposed. How to choose suitable aggregation operations is demonstrated through financial investment application and three approaches are proposed - the stationary agent approach, the token-passing approach, and the mobile agent approach to implementing decision aggregation in MASs. Based on the framework, a prototype was built and applied to financial investment planning. This prototype consists of one serving agent, one interface agent, one decision aggregation agent, one planning agent, four decision making agents, and five service provider agents. Experiments were conducted on the prototype. The experimental results show the framework is flexible, robust, and fully workable. All agents derived from the methodology exhibit their behaviors correctly as specified

The next generation of interoperability agents in healthcare

Interoperability in health information systems is increasingly a requirement rather than an option. Standards and technologies, such as multi-agent systems, have proven to be powerful tools in interoperability issues. In the last few years, the authors have worked on developing the Agency for Integration, Diffusion and Archive of Medical Information (AIDA), which is an intelligent, agent-based platform to ensure interoperability in healthcare units. It is increasingly important to ensure the high availability and reliability of systems. The functions provided by the systems that treat interoperability cannot fail. This paper shows the importance of monitoring and controlling intelligent agents as a tool to anticipate problems in health information systems. The interaction between humans and agents through an interface that allows the user to create new agents easily and to monitor their activities in real time is also an important feature, as health systems evolve by adopting more features and solving new problems. A module was installed in Centro Hospitalar do Porto, increasing the functionality and the overall usability of AIDA.This work is funded by National Funds through the FCT-Fundacao para a Ciencia e a Tecnologia (Portuguese Foundation for Science and Technology) within project PEst-OE/EEI/UI0752/2014. PEst-OE means in Portuguese "Strategic Project by National Funds" and "EEI" means "Informatics and Electronic Engineering"

Intelligent systems for monitoring and preventing in healthcare information systems

Nowadays the interoperability in Healthcare Information Systems (HIS) is a fundamental requirement. The Agency for Integration, Diffusion and Archive of Medical Information (AIDA) is an interoperability healthcare platform that ensures these demands and it is implemented in Centro Hospitalar do Porto (CHP), a major healthcare unit in Portugal. Therefore, the overall performance of CHP HIS depends on the success of AIDA functioning. This paper presents monitoring and prevention systems implemented in the CHP, which aim to improve the system integrity and high availability. These systems allow the monitoring and the detection of situations conducive to failure in the AIDA main components: database, machines and intelligent agents. Through the monitoring systems, it was found that the database most critical period is between 11:00 and 12:00 and the resources are well balanced. The prevention systems detected abnormal situations that were reported to the administrators that took preventive actions, avoiding damage to AIDA workflow

Engineering Intelligent Nanosystems for Enhanced Medical Imaging

Medical imaging serves to obtain anatomical and physiological data, supporting medical diagnostics as well as providing therapeutic evaluation and guidance. A variety of contrast agents have been developed to enhance the recorded signals and to provide molecular imaging. However, fast clearance from the body or nonspecific biodistribution often limit their efficiency, constituting challenges that need to be overcome. Nanoparticle-based systems are currently emerging as versatile and highly integrated platforms providing improved circulating times, tissue specificity, high loading capacity for signaling moieties, and multimodal imaging features. Furthermore, nanoengineered devices can be tuned for specific applications and the development of responsive behaviors. Responses include in situ modulation of nanoparticle size, increased intratissue mobility through active propulsion of motorized particles, and active modulation of the particle surroundings such as the extracellular matrix for an improved penetration and retention at the desired locations. Once accumulated in the targeted tissue, smart nanoparticle-based contrast agents can provide molecular sensing of biomarkers or characteristics of the tissue microenvironment. In this case, the signal or contrast provided by the nanosystem is responsive to the presence or concentration of an analyte. Herein, recent developments of intelligent nanosystems to improve medical imaging are presented

Experimental and simulation analysis for performance enhancement of elliptical savonius wind turbine by modifying blade shapes

Savonius turbines are drag-based rotors which operate due to a pressure difference between the advancing and retreating blades. After going through an exhaustive literature review, it was realized that the Savonius wind turbines are an applicable option at low wind speed areas, where the counterpart of these turbines cannot work efficiently. Nevertheless, the existing design is still under research to make it more applicable in urban areas. Therefore, the research objective was to develop and test an elliptical Savonius wind turbine to improving its performance in terms of power and torque coefficients by modifying blade shapes and overlap ratio. In the beginning, a series of 2D unsteady simulations (CFD-Fluent version 19.1) of the Savonius elliptical turbine has been performed to study the overlap ratio of blades and the effect of the turbulence models. Conventional elliptical Savonius turbine was modified by changing the overlap ratio from the value (OR=0.15) to (OR=0.2) and called as the Model-A. Then, the concave surface of the blade Model-A was modified (as zigzag shape) and called as Model-B. The blade shape of the Model-B was modified by adding bypass channels for each blade to creating new configuration was called the Model-C. The experimental work begins with the manufacturing of the models (A, B and C) of the blade using 3D printing technology. Models were tested by the wind tunnel in Aerodynamic laboratory (UTHM) with four cases of wind velocity. 2D simulation result for Model-A at OR= 0.2, where the increase in maximum power coefficient value obtained was 3.85% and 7.69% compared to overlap ratio (0.15 and 0.1), respectively. The result of the experimental test was obtained the maximum power coefficient (0.296, 0.292, 0.291, and 0.295) at wind velocity (6 m/s, 8 m/s, 9 m/s, and 10 m/s), respectively for Model-B. The Model-C result in the maximum power coefficient (0.28) compared with Model-A (0.26). The 3D unsteady simulation also has been done to visualisation the behaviour of flow around Model-B and it show a good agreement with experimental test results

Intelligent medical robot society

Any treatment on long or short term duration and/or complexity begin to involve more and more complex hardware and software pieces of equipment. Most of them begin to have various degree of mobility. Although the medical staff has enough trouble in handling them some times. In this paper we propose a complex robot society to deserve a medical center. The evolution of human computer interface and of the complex expert systems with medical application drive us to idea that a dedicated medical society of intelligent agents can be created

CAMMD: Context Aware Mobile Medical Devices

Telemedicine applications on a medical practitioners mobile device should be context-aware. This can vastly improve the effectiveness of mobile applications and is a step towards realising the vision of a ubiquitous telemedicine environment. The nomadic nature of a medical practitioner emphasises location, activity and time as key context-aware elements. An intelligent middleware is needed to effectively interpret and exploit these contextual elements. This paper proposes an agent-based architectural solution called Context-Aware Mobile Medical Devices (CAMMD). This framework can proactively communicate patient records to a portable device based upon the active context of its medical practitioner. An expert system is utilised to cross-reference the context-aware data of location and time against a practitioners work schedule. This proactive distribution of medical data enhances the usability and portability of mobile medical devices. The proposed methodology alleviates constraints on memory storage and enhances user interaction with the handheld device. The framework also improves utilisation of network bandwidth resources. An experimental prototype is presented highlighting the potential of this approach

Application of Intelligent Multi Agent Based Systems For E-Healthcare Security

In recent years, availability and usage of extensive systems for Electronic Healthcare Record (EHR) is increased. In medical centers such hospitals and other laboratories, more health data sets were formed during the treatment process. In order to enhance the standard of the services provided in healthcare, these records where shared and can be used by various users depends on their requirements. As a result, notable issues in the security and privacy where obtained which should be monitored and removed in order to make the use of EHR more effectively. Various researches have been done in the past literature for improving the standards of the security and privacy in E-health systems. In spite of this, it is not completely enhanced. In this paper, a comprehensive analysis is done by selecting the existing approaches and models which were proposed for the security and privacy of the E-healthcare systems. Also, a novel Intelligent-based Access Control Security Model (IBAC) based on multi agents is proposed to maintain and support the security and privacy of E-healthcare systems. This system uses agents in order to maintain security and privacy while accessing the E-health data between the users.Comment: 6 pages, 3 figures, 1 table, journa

Robots to the Rescue: A Review of Studies on Differential Medical Diagnosis Employing Ontology-Based Chat Bot Technology

Access to medical care is a global issue. Technology-aided approaches have been applied in addressing this. Interventions have however not focused on medical diagnosis as a fully automated procedure and available applications employ mainly text-based inputs rather than conversation in natural language. We explored the utility of ontology-based chatbot technology for the design of intelligent agents for medical diagnosis through a systematic review of the most recent related literature. English articles published in 2011-2016 returned 233 hits which yielded 11 relevant articles after a 3-stage screening. Findings showed that the creation of expert systems had been the focus of many the studies which utilize the physician-system-patient framework with system training based mostly on expert knowledge for designing web- or mobile phone-based applications that serve assistive purposes. Findings further indicated gaps in the design and evaluation of more effective systems deployable as standalone applications, for example, on an embodied robotic system. The need for technology supporting the physical examination part of diagnosis, connection to data sources on patients’ vitals and medical history are also indicated in addition to the need for more qualitative work on natural language-based interaction. The system should be one that is continuously learning. Future works should also be directed towards the building of more robust knowledge base as well as evaluation of theory-based diagnostic methodological option