A multi-agent model and architecture for multi-modal knowledge assistance and capitalization
| dc.contributor.author | Iqbal Hashmi, Zafar | |
| dc.date.accessioned | 2014-11-14T07:50:44Z | |
| dc.date.available | 2014-11-14T07:50:44Z | |
| dc.date.issued | 2004 | |
| dc.description | Master | en_US |
| dc.description.abstract | The paradigm shift set by agent-based computing provides powerful tools, techniques, strategies and metaphors that have the potential to significantly improve the way in which people conceptualize and develop different kinds of software. The software community has started to believe that agent-based computing is the next significant breakthrough for the mainstream of software development. Although intelligent agents and multi-agent systems provide many potential advantages and state of the art mechanisms to solve problems, they face many difficult challenges from different aspects like modeling, analysis, designing, interaction, coordination, cooperation, architectures etc. These issues hinder the adoption of technology into the mainstream of computer science. In this thesis we have developed a contrived, multi-step, three phase methodology to address some of the problem issues related to intelligent agents and multi-agent systems and developed a multi-agent system application based on the techniques, strategies and mechanisms developed through out this thesis. In the first phase of our research, firstly, we developed Hybrid Intelligent Autonomous Agent (IAA) model that provides the theoretical framework in defining the specifications for single intelligent autonomous agent architecture. Secondly, we defined, a Hybrid Intelligent Autonomous Agent (IAA) generic architecture based on the hybrid IAA model. Our IAA generic agent architecture can act in a deliberative and reactive manner and it incorporates motivators to mimic human-like behavior. Thirdly, we developed Demand Based Cooperation (DBC) Cooperative Multi-agent System Model. The DBC multi-agent system model is a cooperative multi-agent model that specifies the coordination and cooperation scheme with appropriate communication protocols to lessen the communication and system resources overheads. Fourthly, we developed a content level agent communication language called Knowledge Description Lanaguage (KDL) that adheres to the protocols defined in the DBC multi-agent model. In the second phase of our research firslty, we developed an Intelligent Autonomous Agent (IAA)- oriented Methodology for analysis and designing of agents which is based on the holistic view of agent theory and takes into account the organizational structure, organizational model, cooperative protocols, explicit interaction representation and designing of the multi-agent system architecture. Secondly, we developed an Intelligent Healthcare Knowledge Assistance and Capitalization (IHA) Multi-agent system architecture that is based on the DBC cooperative multi-agent model. In the third and final phase of our research, we developed the IHA system for multi-agent system which brings together all the techniques, methods and strategies defined in this thesis. We conducted a qualitative and quantitative evaluation of the work presented in this thesis. Qualitative evaluation was conducted for Hybrid IAA model, Hybrid IAA generic architecture, DBC multi-agent model, Intelligent Autonomous Agent (IAA)-oriented methodology, and KDL while quantitative evaluation was conducted for IHA multi-agent system. Evaluation results for Hybrid IAA model showed that the proposed model is more realistic, intelligent, mimics human behavior and provides more cognitive and flexible control than the BDI model. The Hybrid IAA generic architecture was evaluated against PRS and DECAF architectures and results showed that the Hybrid IAA has a number of extra characteristics which makes it a better choice by overcoming problems found in PRS and DECAF in terms of better scheduling, message definition standards, flexible communication mechanisms, mimicking human behavior, planning and re-planning, short response time and simple initialization. The DBC multi-agent model showed positive results in the reduction of communication overhead among multi-agents against other multi-agent models. Evaluation of KDL showed that it is better in terms of richness of knowledge description, extensibility, ease of expressiveness, reasoning complexity and goal-oriented representation over other agent communication languages such as KIF and LARKS. The results of the evaluation for the IAA-oriented methodology showed how it overcame the problems and provided a better strategy for the analysis and design of agent compared to GAIA in terms of organizational structure, multiagent architecture, organization model, plans and pureness of its agent orientation. We conducted a quantitative evaluation of the IHA multi-agent system which showed high reliability of the system, and high Recall and Precision values. We found that reliability and efficiency became high because of the division of knowledge index, division of ontology, its autonomous/concurrent nature, and the distributed locations of agents. In conclusion, our research on the modeling, designing and development of the intelligent agents and the multi-agent systems designing, modeling and development is an exciting one, leading towards generation of new and innovative techniques for the advancement of agent technology. | en_US |
| dc.identifier.uri | http://hdl.handle.net/123456789/499 | |
| dc.language.iso | en | en_US |
| dc.subject | Biological Science | en_US |
| dc.subject | Architecture | en_US |
| dc.subject | Knowledge assistance | en_US |
| dc.title | A multi-agent model and architecture for multi-modal knowledge assistance and capitalization | en_US |
| dc.type | Thesis | en_US |
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