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PhD research subject
Verification and Validation of Knowledge-Based Program Supervision Systems
Program supervision (PS) consists in the automation of the use of an existing program library, independently of any individual application. PS systems are in general intended to work without (or with little) human interaction, and in a varying environment. Therefore, the development of PS systems requires a reliable methodology, comprising verification and validation (V&V) techniques. Verification of knowledge-based systems has been usually limited to syntactic verifications based on the implementation language, mostly rule bases. PS is a well-defined task. It includes features from the generic tasks of planning and parametric design.
We distinguish the following elements in the specification of a knowledge-based system: task definition, problem-solving method, and domain model. Our verification approach is based on the PS ontology and on the requirements that both the task and problem-solving method enforce on the domain knowledge of a particular application.
A knowledge model of PS allows us to identify the properties that the knowledge base has to verify with respect to the intended use of the embodied knowledge in the task, with more significant semantics than the properties based on the syntax of the implementation language. The implementation of the verification tool for the knowledge base will be based on the properties identified in this way. The verification of the problem-solving method, on the other hand, can help to the detection of the requirements on the knowledge base necessary to relate the problem-solving method to the task. For this purpose, the KIV tool has been recently used in some examples. The main characteristic of our model-based approach resides in exploiting the knowledge on the task, and in the meaningfulness of the verified properties.
Verification and Validation of Knowledge-Based Program Supervision Systems
Program supervision (PS) consists in the automation of the use of an existing program library, independently of any individual application. PS systems are in general intended to work without (or with little) human interaction, and in a varying environment. Therefore, the development of PS systems requires a reliable methodology, comprising verification and validation (V&V) techniques. Verification of knowledge-based systems has been usually limited to syntactic verifications based on the implementation language, mostly rule bases. PS is a well-defined task. It includes features from the generic tasks of planning and parametric design.
We distinguish the following elements in the specification of a knowledge-based system: task definition, problem-solving method, and domain model. Our verification approach is based on the PS ontology and on the requirements that both the task and problem-solving method enforce on the domain knowledge of a particular application.
A knowledge model of PS allows us to identify the properties that the knowledge base has to verify with respect to the intended use of the embodied knowledge in the task, with more significant semantics than the properties based on the syntax of the implementation language. The implementation of the verification tool for the knowledge base will be based on the properties identified in this way. The verification of the problem-solving method, on the other hand, can help to the detection of the requirements on the knowledge base necessary to relate the problem-solving method to the task. For this purpose, the KIV tool has been recently used in some examples. The main characteristic of our model-based approach resides in exploiting the knowledge on the task, and in the meaningfulness of the verified properties.
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William Van Woensel,Samson W. Tu,Wojtek Michalowski,Syed Sibte Raza Abidi,Samina Abidi, José Ramón Alonso,Alessio Bottrighi,Marc Carrier, Ruth Edry,Irit Hochberg,Malvika Rao,Stephen P. Kingwell,
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Jorge Munoz-Gama, Niels Martin,Carlos Fernandez-Llatas, Owen A Johnson,Marcos Sepúlveda,Emmanuel Helm, Victor Galvez-Yanjari,Eric Rojas,Antonio Martinez-Millana, Davide Aloini,Ilaria Angela Amantea, Robert Andrews,
A. Mañas-García,I. González-Valverde, E. Camacho-Ramos, A. Alberich-Bayarri,J. A. Maldonado,M. Marcos,M. Robles
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