Knowledge engineering
Encyclopedia
Knowledge engineering was defined in 1983 by Edward Feigenbaum
, and Pamela McCorduck
as follows:
At present, it refers to the building, maintaining and development of knowledge-based systems
. It has a great deal in common with software engineering
, and is used in many computer science
domains such as artificial intelligence
, including database
s, data mining
, expert system
s, decision support system
s and geographic information system
s. Knowledge engineering is also related to mathematical logic
, as well as strongly involved in cognitive science
and socio-cognitive
engineering where the knowledge is produced by socio-cognitive aggregates (mainly humans) and is structured according to our understanding
of how human reasoning and logic
works.
Various activities of KE specific for the development of a knowledge-based system:
Being still more art than engineering, KE is not as neat as the above list in practice. The phases overlap, the process might be iterative, and many challenges could appear.
A major concern in knowledge engineering is the construction of ontologies. One philosophical question in this area is the debate between foundationalism
and coherentism
- are fundamental axioms of belief required, or merely consistency of beliefs which may have no lower-level beliefs to justify them?
The paradigm Shift from a transfer view to a modeling view
According to the transfer view the human knowledge required to solve a problem is transferred and implemented into the knowledge base. However this assumes that concrete knowledge is already present in humans to solve a problem. The transfer view disregards the tacit knowledge an individual acquires in order to solve a problem. This is one of the reasons for a paradigm shift towards modeling view. This shift is compared to a shift from first generation expert systems to second generation expert systems.
The modeling view is a closer approximate of reality and perceives solving problems as a dynamic, cyclic, incessant process dependent on the knowledge acquired and the interpretations made by the system. This is similar to how an expert solves problems in real life.
The evolving of Role Limiting methods and Generic Tasks
Role limiting methods are based on reusable problem solving methods. Different knowledge roles are decided and the knowledge expected from each of these roles is clarified. However the disadvantage of role limiting methods is that there is no logical means of deciding whether a specific problem can be solved by a specific role-limiting method.
This disadvantage gave rise to Configurable role limiting methods. Configurable role limiting methods are based on the idea that a problem solving method can further be broken up into several smaller sub tasks each task solved by its own problem solving method.
Generic Tasks include a rigid knowledge structure, a standard strategy to solve problems, a specific input and a specific output.
The usage of Modeling Frameworks
The development of Specification languages and problem solving methods of knowledge based systems.Over the past few years the modeling frameworks that became prominent within Knowledge engineering are Common KADS, MIKE (Model-based and Incremental knowledge engineering) and PROTÉGÉ-II.PROTÉGÉ-II is a modeling framework influenced by the concept of ‘Ontology’.
The influence of Ontology
Ontologies help building model of a domain and define the terms inside the domain and the relationships between them. There are different types of Ontologies including Domain ontologies, Generic ontologies, application ontologies and representational ontologies.
While categorizing knowledge, storing, retrieving and managing information is not only useful for solving problems without direct need of human expertise but also leads to ‘Knowledge Management’ efforts that enable an organization to function efficiently in the long run.
Edward Feigenbaum
Edward Albert Feigenbaum is a computer scientist working in the field of artificial intelligence. He is often called the "father of expert systems."...
, and Pamela McCorduck
Pamela McCorduck
Pamela McCorduck is the author of a number of books concerning the history and philosophical significance of artificial intelligence, the future of engineering and the role of women and technology. She is also the author of three novels. She is a contributor to Omni, New York Times, Daedalus, the...
as follows:
At present, it refers to the building, maintaining and development of knowledge-based systems
Knowledge-based systems
Knowledge based systems are artificial intelligent tools working in a narrow domain to provide intelligent decisions with justification. Knowledge is acquired and represented using various knowledge representation techniques rules, frames and scripts...
. It has a great deal in common with software engineering
Software engineering
Software Engineering is the application of a systematic, disciplined, quantifiable approach to the development, operation, and maintenance of software, and the study of these approaches; that is, the application of engineering to software...
, and is used in many computer science
Computer science
Computer science or computing science is the study of the theoretical foundations of information and computation and of practical techniques for their implementation and application in computer systems...
domains such as artificial intelligence
Artificial intelligence
Artificial intelligence is the intelligence of machines and the branch of computer science that aims to create it. AI textbooks define the field as "the study and design of intelligent agents" where an intelligent agent is a system that perceives its environment and takes actions that maximize its...
, including database
Database
A database is an organized collection of data for one or more purposes, usually in digital form. The data are typically organized to model relevant aspects of reality , in a way that supports processes requiring this information...
s, data mining
Data mining
Data mining , a relatively young and interdisciplinary field of computer science is the process of discovering new patterns from large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics and database systems...
, expert system
Expert system
In artificial intelligence, an expert system is a computer system that emulates the decision-making ability of a human expert. Expert systems are designed to solve complex problems by reasoning about knowledge, like an expert, and not by following the procedure of a developer as is the case in...
s, decision support system
Decision support system
A decision support system is a computer-based information system that supports business or organizational decision-making activities. DSSs serve the management, operations, and planning levels of an organization and help to make decisions, which may be rapidly changing and not easily specified in...
s and geographic information system
Geographic Information System
A geographic information system, geographical information science, or geospatial information studies is a system designed to capture, store, manipulate, analyze, manage, and present all types of geographically referenced data...
s. Knowledge engineering is also related to mathematical logic
Logic
In philosophy, Logic is the formal systematic study of the principles of valid inference and correct reasoning. Logic is used in most intellectual activities, but is studied primarily in the disciplines of philosophy, mathematics, semantics, and computer science...
, as well as strongly involved in cognitive science
Cognitive science
Cognitive science is the interdisciplinary scientific study of mind and its processes. It examines what cognition is, what it does and how it works. It includes research on how information is processed , represented, and transformed in behaviour, nervous system or machine...
and socio-cognitive
Socio-cognitive
Socio-cognitive or sociocognitive describes integrated cognitive and social properties of systems, processes, functions, models, as well as can indicate the branch of science, engineering or technology, such as socio-cognitive research, socio-cognitive interactions.This term is especially used when...
engineering where the knowledge is produced by socio-cognitive aggregates (mainly humans) and is structured according to our understanding
Understanding
Understanding is a psychological process related to an abstract or physical object, such as a person, situation, or message whereby one is able to think about it and use concepts to deal adequately with that object....
of how human reasoning and logic
Logic
In philosophy, Logic is the formal systematic study of the principles of valid inference and correct reasoning. Logic is used in most intellectual activities, but is studied primarily in the disciplines of philosophy, mathematics, semantics, and computer science...
works.
Various activities of KE specific for the development of a knowledge-based system:
- Assessment of the problem
- Development of a knowledge-based system shell/structure
- Acquisition and structuring of the related information, knowledge and specific preferences (IPK model)
- Implementation of the structured knowledge into knowledge bases
- Testing and validation of the inserted knowledge
- Integration and maintenance of the system
- Revision and evaluation of the system.
Being still more art than engineering, KE is not as neat as the above list in practice. The phases overlap, the process might be iterative, and many challenges could appear.
Knowledge engineering principles
Since the mid-1980s, knowledge engineers have developed a number of principles, methods and tools to improve the knowledge acquisition and ordering. Some of the key principles are:- There are different:
- types of knowledge each requiring its own approach and technique.
- types of experts and expertise, such that methods should be chosen appropriately.
- ways of representing knowledge, which can aid the acquisition, validation and re-use of knowledge.
- ways of using knowledge, so that the acquisition process can be guided by the project aims (goal-orientedGoal-orientedThe concept of goal orientation was developed to describe variability in dispositional or situational goal preferences that an individual implicitly sets for him/herself in achievement situations. GOs assist in providing a motivational framework for how individuals perceive, interpret, and judge...
).
- Structured methods increase the efficiency of the acquisition process.
- Knowledge Engineering is the process of eliciting Knowledge for any purpose be it Expert system or AI development
Views of knowledge engineering
There are two main views to knowledge engineering:- Transfer View – This is the traditional view. In this view, the assumption is to apply conventional knowledge engineering techniques to transfer human knowledge into artificial intelligence systems.
- Modeling View – This is the alternative view. In this view, the knowledge engineer attempts to model the knowledge and problem solving techniques of the domain expert into the artificial intelligence system.
A major concern in knowledge engineering is the construction of ontologies. One philosophical question in this area is the debate between foundationalism
Foundationalism
Foundationalism is any theory in epistemology that holds that beliefs are justified based on what are called basic beliefs . This position is intended to resolve the infinite regress problem in epistemology...
and coherentism
Coherentism
There are two distinct types of coherentism. One refers to the coherence theory of truth. The other refers to the coherence theory of justification. The coherentist theory of justification characterizes epistemic justification as a property of a belief only if that belief is a member of a coherent...
- are fundamental axioms of belief required, or merely consistency of beliefs which may have no lower-level beliefs to justify them?
Overview of Trends in Knowledge Engineering
Some of the trends in Knowledge Engineering in the last few years are discussed in this section.The text below is a brief overview of paper "Knowledge Engineering: Principles and methods" authored by Rudi Studer,V.Richard Benjamins and Dieter Fensel.The paradigm Shift from a transfer view to a modeling view
According to the transfer view the human knowledge required to solve a problem is transferred and implemented into the knowledge base. However this assumes that concrete knowledge is already present in humans to solve a problem. The transfer view disregards the tacit knowledge an individual acquires in order to solve a problem. This is one of the reasons for a paradigm shift towards modeling view. This shift is compared to a shift from first generation expert systems to second generation expert systems.
The modeling view is a closer approximate of reality and perceives solving problems as a dynamic, cyclic, incessant process dependent on the knowledge acquired and the interpretations made by the system. This is similar to how an expert solves problems in real life.
The evolving of Role Limiting methods and Generic Tasks
Role limiting methods are based on reusable problem solving methods. Different knowledge roles are decided and the knowledge expected from each of these roles is clarified. However the disadvantage of role limiting methods is that there is no logical means of deciding whether a specific problem can be solved by a specific role-limiting method.
This disadvantage gave rise to Configurable role limiting methods. Configurable role limiting methods are based on the idea that a problem solving method can further be broken up into several smaller sub tasks each task solved by its own problem solving method.
Generic Tasks include a rigid knowledge structure, a standard strategy to solve problems, a specific input and a specific output.
The GT approach is based on the strong interaction problem hypothesis which states that the structure and representation of domain knowledge is completely determined by its use
The usage of Modeling Frameworks
The development of Specification languages and problem solving methods of knowledge based systems.Over the past few years the modeling frameworks that became prominent within Knowledge engineering are Common KADS, MIKE (Model-based and Incremental knowledge engineering) and PROTÉGÉ-II.PROTÉGÉ-II is a modeling framework influenced by the concept of ‘Ontology’.
The influence of Ontology
Ontologies help building model of a domain and define the terms inside the domain and the relationships between them. There are different types of Ontologies including Domain ontologies, Generic ontologies, application ontologies and representational ontologies.
While categorizing knowledge, storing, retrieving and managing information is not only useful for solving problems without direct need of human expertise but also leads to ‘Knowledge Management’ efforts that enable an organization to function efficiently in the long run.
See also
- Knowledge representationKnowledge representationKnowledge representation is an area of artificial intelligence research aimed at representing knowledge in symbols to facilitate inferencing from those knowledge elements, creating new elements of knowledge...
- Knowledge retrievalKnowledge retrievalKnowledge Retrieval seeks to return information in a structured form, consistent with human cognitive processes as opposed to simple lists of data items...
- Knowledge managementKnowledge managementKnowledge management comprises a range of strategies and practices used in an organization to identify, create, represent, distribute, and enable adoption of insights and experiences...
- Knowledge level modelingKnowledge level modelingKnowledge level modeling is the process of theorizing over observations about a world and, to some extent, explaining the behavior of an agent as it interacts with its environment....
- Knowledge acquisitionKnowledge acquisitionKnowledge acquisition is a method of learning, first proposed by Aristotle in his seminal work "Organon". Aristotle proposed that the mind at birth is a blank slate, or tabula rasa...
- Knowledge tagging
- Cognitive scienceCognitive scienceCognitive science is the interdisciplinary scientific study of mind and its processes. It examines what cognition is, what it does and how it works. It includes research on how information is processed , represented, and transformed in behaviour, nervous system or machine...
- Collaborative innovation network
- Connectionist expert systemConnectionist expert systemConnectionist expert systems are artificial neural network based expert systems where the ANN generates inferencing rules e.g., fuzzy-multi layer perceptron where linguistic and natural form of inputs are used. Apart from that, rough set theory may be used for encoding knowledge in the weights...
- Decision support systemDecision support systemA decision support system is a computer-based information system that supports business or organizational decision-making activities. DSSs serve the management, operations, and planning levels of an organization and help to make decisions, which may be rapidly changing and not easily specified in...
- Epistemology
- Logico-linguistic modelingLogico-linguistic modelingLogico-linguistic modeling is a method for building knowledge-based systems with a learning capability using Conceptual Models from Soft systems methodology, modal predicate logic and the Prolog artificial intelligence language.- Overview:...
- Meta-knowledge
- Ontology (information science)
- Tacit knowledgeTacit knowledgeTacit knowledge is knowledge that is difficult to transfer to another person by means of writing it down or verbalising it. For example, stating to someone that London is in the United Kingdom is a piece of explicit knowledge that can be written down, transmitted, and understood by a recipient...
- SystemicsSystemicsIn the context of systems science and systems philosophy, the term systemics refers to an initiative to study systems from a holistic point of view...
- Expert systems
External links
- Data & Knowledge Engineering - Elsevier Journal
- Knowledge Engineering Review, Cambridge Journal
- The International Journal of Software Engineering and Knowledge Engineering- World Scientific
- IEEE Transactions on Knowledge and Data Engineering
- Expert Systems: The Journal of Knowledge Engineering - Wiley-Blackwell