Bio-medical Ontologies Maintenance and Change Management

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290 M. Hadzic, M. Chen, and R. Brouwer (2) Service. The multi-agent system is composed of various agents with different but complementary capabilities. The expertise complementarity is a feature that holds the agent society together. Agents are dependant on each other for mutually beneficial actions and accomplishing goals of the overall system. The agents should be able to work together and provide service to one another. The agents that refuse to collaborate should be replaced by agents willing to provide service to others. (3) Commitment. The agents of the system must be completely committed to the overall goal and purpose of the multi-agent system. Some agents may be partially committed and reliance on such agents may be risky. In worst cases, agents may commit to the overall goals and purposes of other malicious multi-agent systems and turn against the multi-agent system they were originally created to work for. The nine identified properties are critical inside as well as outside the multiagent system, such as during the interaction of the multi-agent system with the environment. It is necessary to effectively address these issues and efficiently implement them within the multi-agent system. In our multi-agent system, all nine requirements must be addressed. For example, in regard to the integrity requirement, the information provided to the Intelligent agent by the Information agents should be identical to the information found in the information resource from which this information was retrieved. In the same way, information provided to the Interface agent by the Intelligent agents should be identical to the information found in the database (as well as the information found in the original information resource). In analogous way we can address other security requirements. 4.5 Assemble Individual Agents We have discussed different functions and types of agents, their intelligence, system architecture and security requirements that must be addressed within the system. In this step we bring the different aspects together and create the different agents defined by the previous steps. It is important for each agent to identify required agent components, design the components and assemble them into an unified system i.e. individual agent. For example, these agent components may be Human Interface (to enable interaction with users e.g. interaction between Interface agent and users), Agent Interface (to enable interaction with other agents e.g. interaction between Interface & Intelligent agents and Intelligent & Information agents), Communication component (to enable exchanging and processing messages during agent’s interactions), Task component (to enable the agents to perform tasks assigned to them), Domain component (Total Wellbeing Ontology), Environment knowledge (to describe environment in which the agents perform their functions), History files (past experiences of agents), and so on. It is possible that to achieve variety of agents within a multi-agent in three different ways: (1) using same components but changing the content of these components (2) changing combination of the used components (3) changing both content and combination of the used components.
Completing the Total Wellbeing Puzzle Using a Multi-agent System 291 Interface, Intelligent and Information agents are very different from each other so they can be designed using the third approach. However, the Information agents are very similar to each other for the reason that they perform same tasks but within different domains, as determined by the holarchy to which they belong. They can be designed using the first approach. 5 Conclusion and Future Works The technology breakthrough, the modern way of living and modern societies have not only resulted in comfortable lives but also in increased stress, pressure and fears which in their turn started degrading our health and wellbeing. More than ever, we need to take a holistic approach in studying and controlling our health and wellbeing. We use an evidence-based ontological model that defines the total wellbeing as a function of the physical, mental, emotional, financial, relational and spiritual wellbeing. We have used the TICSA (Types, Intelligence, Collaboration, Security and Assembly) approach to design a multi-agent system for intelligent retrieval, management and use of information related to the six different dimensions of the total wellbeing and their relationships. This system has the potential to expose the evidence that will change the way we understand, control and manage our health. It will support general public in managing their personal wellbeing better and health professionals in adapting their services to address patients’ needs more systematically and effectively. We are in early implantation stage of the system, and our progress will be reported in the forthcoming papers. References 1. Hadzic, M., Chang, E.: Web Semantics for Intelligent and Dynamic Information Retrieval Illustrated Within the Mental Health Domain. In: Chang, E., Dillon, T.S., Meersman, R., Sycara, K. (eds.) Advances in Web Semantics. LNCS, vol. 4891, pp. 260–275. Springer, Heidelberg (2007) 2. Goble, C.: The Grid Needs you. Enlist Now. In: Proceedings of the International Conference on Cooperative Object Oriented Information Systems, pp. 589–600 (2003) 3. Moreno, A., Isern, D.: A First Step Towards Providing Health-care Agent-based Services to Mobile Users. In: Proceedings of the First International Joint Conference on Autonomous Agents and Multi-agent Systems, pp. 589–590 (2002) 4. Huang, J., Jennings, N.R., Fox, J.: An Agent-based Approach to Health Care Management. International Journal of Applied Artificial Intelligence 9(4), 401–420 (1995) 5. Merelli, E., Culmone, R., Mariani, L.: BioAgent - A Mobile Agent System for Bioscientists. In: Proceedings of the Network Tools and Applications in Biology Workshop Agents in Bioinformatics (2002) 6. Ulieru, M.: Internet-enabled Soft Computing Holarchies for e-Health Applications. New Directions in Enhancing the Power of the Internet, 131–166 (2003) 7. Srinivasan, P., Mitchell, J., Bodenreider, O., Pant, G., Menczer, F.: Web Crawling Agents for Retrieving Biomedical Information. In: Proceedings of International Workshop on Agents in Bioinformatics (NETTAB 2002) (2002)
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Amandeep S. Sidhu and Tharam S. Dil
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Preface The molecular biology commu
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Preface VII biomedical systems, and
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X Contents Mining Clinical, Immunol
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2 A.S. Sidhu, M. Bellgard, and T.S.
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Towards Bioinformatics Resourceomes
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2 The New Waves Towards Bioinformat
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2.4 Semantic Web Towards Bioinforma
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A Summary of Genomic Databases: Ove
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Appendix A Summary of Genomic Datab
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Protein Data Integration Problem Am
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Fig. 3. Class Hierarchy of Protein
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Bio-medical Ontologies Maintenance
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Mining Clinical, Immunological, and
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Author Index Apiletti, Daniele 169
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Bio-medical Ontologies Maintenance and Change Management

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