A multi-agent model and architecture for multi-modal knowledge assistance and capitalization
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Date
2004
Authors
Iqbal Hashmi, Zafar
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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.
Description
Master
Keywords
Biological Science , Architecture , Knowledge assistance