An Intelligent System (or Knowledge Based System or KBS) is software that reproduces the behaviour of a human expert performing an intellectual task in a specific area. It is based on the explicit nature of knowledge, which is formalized in different ways. Among these formal models, ontologies are formalized and structured representations of the vocabulary specific to a certain area of study. Ontologies are commonly used with a set of rules which are chained to simulate the reasoning of a human expert. This traditional architecture has drawbacks, associated, mainly, with the difficulties that appear during the knowledge elicitation process from experts; and also with the non-completeness of the formal conceptual model obtained after the elicitation.
In fact, as the knowledge base can be incomplete, there could be problems that this traditional architecture cannot solve. Reasoning and analysis of this incomplete knowledge implies that it is needed to take advantage of the experience acquired from the interventions of human experts when the traditional system does not lead to satisfactory results;
The originality of the works is founded on the proposal of the modular architecture KREM (Knowledge, Rules, Experience and Meta-Knowledge) to deal with the aforementioned drawbacks, to incorporate the capitalization of experience with the goal of improving decision-making.
Because to be effective, decision-making must result from reasoning and analysis of domain knowledge, also taking into account the experience and expertise of decision-makers. As a consequence, it is needed to capitalize them to take advantage of the experience acquired from the interventions of human experts when the traditional system does not lead to satisfactory results.
The use of meta-knowledge to steer the execution of the whole system is also necessary. Meta-knowledge is knowledge about domain knowledge, about rules or about experience. This meta-knowledge can take the form of context, culture or protocols to use this knowledge. Context is information that characterizes a situation in relation to interaction among human-beings, applications and their environment, and can be of four types: identity, place, status or time. Culture meta-knowledge tries to take into account the fact that decisions are made differently depending on the country or culture. And finally protocols may include strategies or problem-solving heuristics for the task to be done (for example, in the case of medical diagnosis, the protocols used by physicians change according to the type of symptoms or the suspected illness).
Therefore, the proposed components of the architecture are:
• The Knowledge component that contains the domain knowledge to operate, by means of different domain ontologies to be developed.
• The Rules component that allows different types of reasoning (monotone, spatial, temporal, fuzzy, or other) depending on the application.
• The Experience component that allows the capitalization and reuse of prior knowledge.
• The Meta-knowledge component, including knowledge about the other three bricks that depends on the problem.
Type and Role of Partner Sought
Type : Companies, Universities or R&D institutions with complementary skills with regards to the research laboratory team
Area of activity : environment, water, medical imaging, satellite imaging, factories of the future, other industrial areas
Tasks to be done : use, integration and application of the models, co-development of new application fields of the developed models
For more information, please contact:
Christiana Siambekou
Phone Number: +30-2107273954
Email: schris@ekt.gr