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studenti:mihita_cvitanovic:knowledge_representation [2012/05/30 15:37] mcvitanovic |
studenti:mihita_cvitanovic:knowledge_representation [2023/06/19 16:21] (trenutno) |
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====== Knowledge Representation ====== | ====== Knowledge Representation ====== | ||
- | - knowledge is implicit, i.e. hidden inside our minds | + | ===== About knowledge representation ===== |
- | - problem- how to share it with others? | + | |
- | - we need to make it explicit. i.e. formalized and, thus, available to everybody | + | Knowledge is **stored in implicit form**, i.e. it is hidden inside our minds. This often creates problems when we want to share our knowledge with other people. We need to find a way to present them our knowledge, which means that we need **to make the knowledge explicit**. Explicit form of knowledge enables us to share the information less ambiguously. This became extremely important when computers started to be used for **knowledge transfer and sharing**. |
+ | Knowledge representation is an interdisciplinary field based on mathematics, philosophy and cognitive science [2]. | ||
+ | |||
+ | Knowledge representation is today mainly considered as a field in **artificial intelligence** [3]. However, other disciplines, such as **education psychology**, also do research on knowledge representation. | ||
+ | |||
+ | ===== Knowledge representation definition ===== | ||
+ | |||
+ | “Knowledge representation is the application of **logic and ontology** to the task of constructing **computable models** for some domain” (J.F. Sowa) | ||
+ | |||
+ | Explanation: | ||
+ | |||
+ | * **Logic** provides the formal structure and rules of inference. | ||
+ | * **Ontologies** are viewed as a shared and common understanding of a domain that can be communicated between people and heterogeneous application systems. | ||
+ | * **Logic and ontology** together provide the formalisation mechanisms required to make expressive models easily sharable and computer aware. Thanks to computational resources, great quantities of knowledge expressed this way can be automated. | ||
+ | ===== Roles of knowledge representation ===== | ||
In their article "what is Knowledge Representation?" [1], authors R. Davis, H. Shrobe, and P. Szolovits argue that the concept of knowledge representation can best be understood in terms of five distinct roles it plays: | In their article "what is Knowledge Representation?" [1], authors R. Davis, H. Shrobe, and P. Szolovits argue that the concept of knowledge representation can best be understood in terms of five distinct roles it plays: | ||
- | - A knowledge representation (KR) is most fundamentally a surrogate, a substitute for the thing itself, used to enable an entity to determine consequences by thinking rather than acting, i.e., by reasoning about the world rather than taking action in it. | + | - A knowledge representation is a **surrogate**: symbols are used to represent external things that cannot be stored in a computer, i.e. physical objects, events, and relationships. Symbols are surrogates for the external things. Symbols and links between them form a model of the external system that can be manipulated to simulate it or reason about it. |
- | - It is a set of ontological commitments, i.e., an answer to the question: In what terms should I think about the world? | + | - A knowledge representation is a **set of ontological commitments**: Ontology is the study of existence. Thus, ontology determines the categories of things that exist or may exist in an application domain. Those categories set the ontological commitments of the application designer or knowledge engineer. |
- | - It is a fragmentary theory of intelligent reasoning, expressed in terms of three components: (i) the representation's fundamental conception of intelligent reasoning; (ii) the set of inferences the representation sanctions; and (iii) the set of inferences it recommends. | + | - A knowledge representation is a **fragmentary theory of intelligent reasoning**: to support reasoning about modelled things in a domain, a knowledge representation must describe their behaviour and interactions. The description constitutes a theory of the application domain. It can be stated, for instance, as explicit axioms or compiled into computable programs. |
- | - It is a medium for pragmatically efficient computation, i.e., the computational environment in which thinking is accomplished. One contribution to this pragmatic efficiency is supplied by the guidance a representation provides for organizing information so as to facilitate making the recommended inferences. | + | - A knowledge representation is a **medium for efficient computation**: besides representing knowledge, an Artificial Intelligence System must encode knowledge in a form that can be processed efficiently by the available computing equipment. Therefore, developments in computer hardware and programming theory have a great influence on knowledge representation. |
- | - It is a medium of human expression, i.e., a language in which we say things about the world. | + | - A knowledge representation is a **medium of human expression**: a good knowledge representation language should facilitate communication between the knowledge engineers who manage knowledge tools and the domain experts who understand the application domain. Domain experts should be able to read and verify the domain definitions and rules written by knowledge engineers. |
+ | ===== Knowledge representation technologies ===== | ||
- | Knowledge representation technologies: | + | Knowledge representation is based on logic, ontology and computation. These components make different implementations of knowledge representation which can be classified as follows: |
* [[studenti:mihita_cvitanovic:knowledge_representation_technologies:logic_based_representation|Logic-based representation]] | * [[studenti:mihita_cvitanovic:knowledge_representation_technologies:logic_based_representation|Logic-based representation]] | ||
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* [[studenti:mihita_cvitanovic:knowledge_representation_technologies:network_representation|Network representation]] | * [[studenti:mihita_cvitanovic:knowledge_representation_technologies:network_representation|Network representation]] | ||
* [[studenti:mihita_cvitanovic:knowledge_representation_technologies:structural_representation|Structural representation]] | * [[studenti:mihita_cvitanovic:knowledge_representation_technologies:structural_representation|Structural representation]] | ||
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===== Bibliography ===== | ===== Bibliography ===== | ||
- [[http://groups.csail.mit.edu/medg/ftp/psz/k-rep.html|R. Davis, H. Shrobe, and P. Szolovits. What is a Knowledge Representation? AI Magazine, 14(1):17-33, 1993]]. Retrieved March 17, 2012. | - [[http://groups.csail.mit.edu/medg/ftp/psz/k-rep.html|R. Davis, H. Shrobe, and P. Szolovits. What is a Knowledge Representation? AI Magazine, 14(1):17-33, 1993]]. Retrieved March 17, 2012. | ||
+ | - [[http://rhizomik.net/html/~roberto/thesis/html/KnowledgeRepresentation.html|Roberto García. A Semantic Web Approach to Digital Rights Management]]. Retreived April 28, 2012. | ||
+ | - [[http://www-formal.stanford.edu/jmc/whatisai/whatisai.html|John McCarthy. What is Artificial Intelligence]]. Retreived April 28, 2012. | ||
===== Read more ===== | ===== Read more ===== | ||
+ | |||
+ | - [[http://www.jfsowa.com/krbook/index.html|J.F. Sowa. "Knowledge Representation. Logical, philosophical and computational foundations".Brooks Cole Publishing Co., 2000]] | ||
+ | - Ronald J. Brachman, Hector J. Levesque. "Readings in knowledge representation". M. Kaufmann Publishers, 1985 | ||
+ | - [[http://www.makhfi.com/KCM_intro.htm|Pejman Makhfi. Introduction to Knowledge Modeling.]] |