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History of Knowledge Representation,[object Object],Rinke Hoekstra,[object Object],Universiteit van Amsterdam and Vrije Universiteit,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],1,[object Object]
Context,[object Object],About me…,[object Object],Knowledge Engineering,[object Object],Ontologies,[object Object],Web Ontology Language (OWL 2),[object Object],Semantic Web,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],2,[object Object]
Overview,[object Object],In the beginning… (400 BC – 1900s),[object Object],Scruffies vs. Neats (1970-ies) ,[object Object],The Dark Ages (1980-ies),[object Object],Engineering Revival (1990-ies),[object Object],The ‘O’ Word (1995 onwards),[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],3,[object Object]
In the beginning…,[object Object],400BC – 1900s,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],4,[object Object]
Aristotle (384 BC – 322 BC),[object Object],Dialectics ,[object Object],reductio ad absurdum,[object Object],Deduction,[object Object],premises  conclusion (Plato),[object Object],Syllogisms,[object Object],Standard logic until the 19th century,[object Object],Categories,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],5,[object Object]
Syllogisms,[object Object],Example,[object Object],Major premise	All mortal things die,[object Object],Minor premise	All men are mortal things,[object Object],Conclusion		All men die ,[object Object],Forms,[object Object],Names,[object Object],Barbara (AAA), Celarent (EAE), …,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],6,[object Object]
Aristotle’s Categories,[object Object],Time,[object Object],pos. relative to events,[object Object],Position,[object Object],condition of rest (action),[object Object],State,[object Object],condition of rest (affection),[object Object],Action,[object Object],production of change,[object Object],Affection,[object Object],reception of change,[object Object],Substance,[object Object],primary vs. secondary,[object Object],Quantity,[object Object],extension,[object Object],Quality,[object Object],nature,[object Object],Relation,[object Object],Place,[object Object],position relative to environment,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],7,[object Object]
Porphyry of Tyre (233–c. 309),[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],8,[object Object]
Brentano (1838-1917),[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],9,[object Object]
Ramon Llull (1232 – 1315),[object Object],Mechanical aids to reasoning,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],10,[object Object]
Scientific Revolution (17th and 18th century),[object Object],Dualism,[object Object],René Descartes (1596 – 1650),[object Object],Body as machine <-> Mind,[object Object],Empiricism,[object Object],John Locke (1632 – 1704),[object Object],Royal Society,[object Object],Engineering,[object Object],Christiaan Huygens (1629 – 1695),[object Object],Blaise Pascal (1623 – 1662),[object Object],07-12-2010,[object Object],11,[object Object],SIKS Course - Knowledge Modelling,[object Object]
John Wilkins (1614 – 1672),[object Object],Universal Character,[object Object],Replace latin,[object Object],Decimal system of measure (~metric),[object Object],Tree with 3 layers,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],12,[object Object]
Gottfried Wilhelm Leibniz (1646 – 1716),[object Object],CharacteristicaUniversalis,[object Object],“Once the characteristic numbers of most notions are determined, the human race will have a new kind of tool, a tool that will increase the power of the mind much more than optical lenses helped our eyes, a tool that will be as far superior to microscopes or telescopes as reason is to vision.”,[object Object],(Leibniz, Philosophical Essays),[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],13,[object Object]
Calculators,[object Object],Pascaline,[object Object],Addition,[object Object],Substraction,[object Object],Stepped Reckoner,[object Object],Multiplication,[object Object],Division,[object Object],Binary System,[object Object],… but Leibniz wanted more,[object Object],Calculus Ratiocinator,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],14,[object Object]
Another Leibniz Quote,[object Object],"If controversies were to arise, there would be no more need of disputation between two philosophers than between two accountants. For it would suffice to take their pencils in their hands, and say to each other: Let us calculate.”,[object Object],Leibniz, Dissertio de Arte Combinatoria, 1666,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],15,[object Object]
Linnaeus (1707-1778) –SystemaNaturae,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],16,[object Object]
… so, what’s new?,[object Object],Syllogisms,[object Object],Rules of valid reasoning,[object Object],Reasoning as Calculation,[object Object],Symbol Manipulation,[object Object],Categories,[object Object],Top-down categories of thought,[object Object],Universal Character/SystemaNaturae,[object Object],Bottom-up inventory of phenomena in reality,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],17,[object Object]
GottlobFrege (1884 – 1924),[object Object],Logic,[object Object],Study of correct reasoning,[object Object],Arithmetics and Mathematics,[object Object],Begriffschrift,[object Object],Formal Language (of Meaning),[object Object],Axiomatic Predicate Logic,[object Object],Calculus,[object Object],Variables, Functions, Quantifiers,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],18,[object Object]
Computers,[object Object],Algorithms,[object Object],Alan Turing (1912 – 1954),[object Object],Processor/Memory Architecture,[object Object],Neumann JánosLajos(1903 – 1957),[object Object],Automatic Theorem Proving,[object Object],Resolution,[object Object],Artificial Intelligence! ,[object Object],But…,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],19,[object Object]
Theorem Proving,[object Object],``… great theorem proving controversy of the late sixties …’’ (Newell, 1982),[object Object],Problematic,[object Object],No human scale  ,[object Object],No organisation,[object Object],No procedures,[object Object],Small, theoretically hard problems,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],20,[object Object]
Scruffies vs. Neats,[object Object],1970ies,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],21,[object Object]
Two Schools (1970ies and onwards),[object Object],Philosophy (Neats),[object Object],Clean, uniform language,[object Object],Knowledge derives from small set of ‘elegant’ first principles,[object Object],Theoretical understanding of reality,[object Object],Cognitive Psychology (Scruffies),[object Object],Cognitively plausible language,[object Object],Knowledge is what’s in our heads,[object Object],Human intelligence and behaviour,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],22,[object Object]
Artificial Intelligence,[object Object],“. . . an entity is intelligent if it has an adequate modelof the world […], if it is clever enough to answer a wide variety of questions on the basis of this model, if it can get additional informationfrom the external world when required, and can perform such tasks in the external world as its goals demand and its physical abilities permit.” ,[object Object],(McCarthy and Hayes, 1969, p.4),[object Object],Frame Problem! ,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],23,[object Object]
Epistemic and Heuristic Adequacy,[object Object],McCarthy & Hayes:,[object Object],Representation vs. Mechanism,[object Object],Epistemic Adequacy,[object Object],Correct representation,[object Object],Logic: axioms,[object Object],Heuristic Adequacy,[object Object],Correct reasoning,[object Object],Logic: calculus,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],24,[object Object]
Heuristic vs. Epistemic views in Psychology ,[object Object],Knowledge is about the how,[object Object],Problem Solving,[object Object], Production Systems,[object Object],Knowledge is about the what,[object Object],Natural Language,[object Object],Memory,[object Object], Semantic Networks,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],25,[object Object]
Information Processing System (IPS),[object Object],Computer as metaphor of the mind,[object Object],“the human operates as an ,[object Object],information processing machine’’,[object Object],			Newell & Simon, 1972,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],26,[object Object]
Production Systems (1),[object Object],Processor,[object Object],Interpreter,[object Object],Elementary Information Processes (EIP),[object Object],Sequence of EIPs a function of symbols in memory,[object Object],Production Rules (Emil Post, 1943),[object Object],if … then …,[object Object],Rule ‘fires’ if interpreter finds a match between condition and symbols in memory,[object Object],Sequential ≠ material implication,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],27,[object Object]
Production Systems (2),[object Object],Adequacy?,[object Object],Correspondence to human reasoning,[object Object],Not ‘clean’ or ‘logical’,[object Object],Escape limitations of theorem provers,[object Object],Local, rational control of problem solving,[object Object],Easily modifiable,[object Object],Drawback: Natural language?,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],28,[object Object]
Semantic Networks (1),[object Object],Natural Language,[object Object],Ground lexical terms in a model of reality,[object Object],Semantic Memory,[object Object],M. Ross Quillian (1966),[object Object],Associative Memory,[object Object],Semantic Networks,[object Object],Graph Based,[object Object],Nodes, planes and pointers,[object Object],subclass, modification, disjunction, conjunction, subject/object,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],29,[object Object]
Semantic Networks (2),[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],30,[object Object]
Semantic Networks (3),[object Object],Adequacy?,[object Object],Correspondence to human memory,[object Object],Response time,[object Object],Property inheritance,[object Object],Extensions,[object Object],Named Attributes (type/token),[object Object],Concepts vs. Examples (instances),[object Object],Jaime Carbonell, 1970,[object Object],Sprawl of variants ,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],31,[object Object]
Frames (1),[object Object],Criticism from Cognitive Science,[object Object],Frames, Marvin Minsky (1975),[object Object],Scripts, Roger Schank (1975),[object Object],Frames,[object Object],Larger `chunks’ of thought,[object Object],Situations (akin to planes),[object Object],Default values,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],32,[object Object]
Frames (2),[object Object],Frame system,[object Object],Related frames that share the same terminals,[object Object],… different viewpoints on the same situation,[object Object],Knowledge Reuse,[object Object],“Information Retrieval” Network,[object Object],Standard matching procedure,[object Object],Fixed perspective: ,[object Object],situations, objects, processes ,[object Object],(object-oriented design),[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],33,[object Object]
Semantic Networks (3),[object Object],Technical problems,[object Object],Weak inference (inheritance),[object Object],Unclear semantics,[object Object],“What’s in a link?”, Bill Woods (1975),[object Object],“What IS-A is and isn’t”, Ron Brachman (1983),[object Object],Consider the semantics of the representation itself,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],34,[object Object]
Frame (like) Languages,[object Object],Emphasis,[object Object],Interrelated, internallystructuredconcepts,[object Object],Knowledge Representation Language (KRL),[object Object],Bobrow and Winograd (1976),[object Object],Structured InheritanceNetworks,[object Object],Ron Brachman (1979),[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],35,[object Object]
Knowledge Representation Language (KRL),[object Object],Known entity: prototype,[object Object],Description by reusable descriptors,[object Object],Descriptions by comparison to prototype + extension,[object Object],Modes of description:,[object Object],membership, relationship, role (object/event),[object Object],Reasoning:,[object Object],Process of recognition, procedural attachments,[object Object],Inference mechanism determines meaning,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],36,[object Object]
SI Networks,[object Object],KL-ONE (Brachman, 1979; Brachman & Schmolze, 1985),[object Object],Descriptions,[object Object],Role/Filler Descriptions,[object Object],Structural Descriptions,[object Object],Interpretive Attachments,[object Object],Role modality types:,[object Object],inherent, derivable, obligatory,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],37,[object Object]
SI-Network of an Arch,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],38,[object Object]
Epistemological Status,[object Object],Cognitive plausibility Epist. Status,[object Object],Relation to reality?,[object Object],Relation to representation language?,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],39,[object Object]
The Knowledge Level (Allen Newell, 1982),[object Object],“… the crux for AI is that no one has been able to formulate in a reasonable way the problem of finding the good representation, so that it can be tackled by an AI system” ,[object Object],(Newell, 1982, p.3),[object Object],Computer System Level,[object Object],Medium,[object Object],System,[object Object],Processing Components,[object Object],Composition Guidelines,[object Object],Behavior ,[object Object],Independent, but reducible to lower level,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],40,[object Object]
The Knowledge Level (2),[object Object],“There exists a distinct computer systems level, lying immediately above the symbol level, which is characterised by knowledge as the medium and the principle of rationality as the law of behaviour”,[object Object],(Newell, 1982, p. 99),[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],41,[object Object]
The Knowledge Level (3),[object Object],Not a stance,[object Object],viz. the intentional stance(Dennett, 1987),[object Object],No representation at knowledge level,[object Object],(concepts, tasks, goals),[object Object],Knowledge level = knowledge itself!,[object Object],Representation always at the symbol level,[object Object],Knowledge representation,[object Object],Representation of knowledge, not reality,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],42,[object Object]
Brachman’s Triangle Extended,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],43,[object Object],(Hoekstra, 2009),[object Object]
Representation and Language,[object Object],Brachman’s levels in Semantic Nets,[object Object],Primitives of KR languages,[object Object],Requirements,[object Object],neutrality, adequacy, well-defined semantics,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],44,[object Object]
Epistemological Level,[object Object],Missing level,[object Object],Knowledge-structuring primitives,[object Object],“The formal structure of conceptual units and their interrelationships as conceptual units (independent of any knowledge expressed therein) forms what could be called an epistemology.”,[object Object],(Brachman, 1979, p.30),[object Object],Two interpretations,[object Object],Adequacy of Language for some level,[object Object],Representation at a level,[object Object],e.g. Logical primitives as concepts,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],45,[object Object]
Optimism,[object Object],Modern Knowledge Representation,[object Object],Representation of expert knowledge,[object Object],Performance over Plausibility,[object Object],Modern Languages,[object Object],Defined semantics,[object Object],Clear epistemological status,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],46,[object Object]
The Dark Ages,[object Object],1980ies,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],47,[object Object]
Practical Applications (1980s),[object Object],Expert Systems,[object Object],Production Rules,[object Object],Rules of thumb,[object Object],Relatively clear status,[object Object],Memory in IPS of secondary importance,[object Object],Severe problems,[object Object],Scalability,[object Object],Reusability,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],48,[object Object]
MYCIN and GUIDON (William Clancey, 1983),[object Object],MYCIN: medical diagnosis,[object Object],GUIDON: medical tutoring,[object Object],“transfer back” expert knowledge,[object Object],Problematic,[object Object],No information about how the rule-base was structured: design knowledge,[object Object],“Compiled Knowledge”,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],49,[object Object]
Role of Knowledge in Problem Solving,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],50,[object Object]
Knowledge Types,[object Object],Order of rules: problem solving strategy,[object Object],Structure in knowledge,[object Object],Common causes before unusual ones,[object Object],Justification: domain theory,[object Object],Identification rules,[object Object],Causal rules,[object Object],World fact rules ,[object Object],Domain fact rules,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],51,[object Object]
Convergence?,[object Object],Heuristic vs. Epistemological Adequacy,[object Object],Two approaches,[object Object],Different formalisms,[object Object],Same types of knowledge,[object Object],Two solutions,[object Object],Components (Clancey),[object Object],Knowledge Structuring (Brachman),[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],52,[object Object]
Problems,[object Object],Knowledge Acquisition Bottleneck (Feigenbaum, 1980),[object Object],The difficulty to correctly extract relevant knowledge from an expert into a knowledge base,[object Object],Interaction Problem (Bylander and Chandrasekaran, 1987),[object Object],Different types of knowledge cannot be cleanly separated,[object Object],Problem for reuse,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],53,[object Object]
ENGINEERING REVIVAL,[object Object],1990s,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],54,[object Object]
Knowledge Acquisition,[object Object],Ensure,[object Object],Quality,[object Object],Reuse,[object Object],Ad hoc methodologies,[object Object],Engineering,[object Object],Knowledge modelling vs. extraction,[object Object],Implementation guided by specification,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],55,[object Object]
CommonKADS(Wielinga et al., 1992, van Heijst et al., 1997),[object Object],Knowledge Level Model,[object Object],Independent of KR language,[object Object],Solution to the KA Bottleneck?,[object Object],Limited Interaction Hypothesis,[object Object],Solution to the Interaction Problem?,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],56,[object Object]
Reuse,[object Object],Role limiting (US),[object Object],Direct reuse,[object Object],Index symbol level representations,[object Object],Detailed blueprints,[object Object],Skeletal Models (Europe),[object Object],Reuse of `understanding’,[object Object],Knowledge-level ‘sketches’,[object Object],Library of reusable knowledge components,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],57,[object Object]
Knowledge Types (1),[object Object],Control Knowledge,[object Object],Task Knowledge,[object Object],Inference Knowledge,[object Object],Problem Solving Methods (Breuker & van de Velde, 1994),[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],58,[object Object]
Knowledge Types (2),[object Object],Domain Knowledge,[object Object],Index PSM’s for reuse  Epistemology,[object Object],Generic domain theory,[object Object],What an expert system ‘knows’ about:,[object Object],ONTOLOGY,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],59,[object Object]
Functional Perspective (Hector Levesque, 1984),[object Object],Descend to the Symbol Level?,[object Object],Knowledge Base,[object Object],Abstract datatype,[object Object],Competencies,[object Object],Set of TELL/ASK queries,[object Object],Capabilities of KB,[object Object],Function of queries/answers, assertions,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],60,[object Object]
Knowledge Based Systems,[object Object],Architecture,[object Object],Specialised KR languages,[object Object],Specialised Services,[object Object],Performance guarantees,[object Object],Domain Theory ,[object Object],Identification, Classification,[object Object],KL-ONE like languages… ,[object Object],Control Knowledge,[object Object],Rules…,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],61,[object Object]
The return of logic (Levesque & Brachman, 1987),[object Object],Classification as logical inference,[object Object],Exact semantics,[object Object],Trade-off,[object Object],Expressive power,[object Object],Computational efficiency,[object Object],Restricted Language Thesis,[object Object],“… general purpose knowledge representation systems should restrict their languages by omitting constructs which require non-polynomial (or otherwise unacceptably long) worst-case response times for correct classification of concepts.” (Doyle & Patil, 1991),[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],62,[object Object]
Description Logics (Baader & Hollunder, 1991),[object Object],KL-One, NIKL, KL-Two, LOOM, FL, KANDOR, KRYPTON, CLASSIC …,[object Object],Quest,[object Object],Expressive,[object Object],Sound & Complete,[object Object],Decidable,[object Object],KRIS, SHIQ, SHOIN, SROIQ, …,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],63,[object Object]
… and the rest?,[object Object],Domain Theory ,[object Object],Causal Knowledge,[object Object],Naïve Physics,[object Object],Qualitative Reasoning (J. de Kleer, K.D. Forbus, B. Bredeweg, …),[object Object],Strategic Knowledge,[object Object],Logic-based approaches,[object Object],Prolog, Datalog, etc..,[object Object],… no principled effort.,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],64,[object Object]
The ‘O’ Word,[object Object],1995 and onwards,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],65,[object Object],Oh no! ,[object Object],Not that again!,[object Object]
Pop Quiz,[object Object],What is an ontology?,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],66,[object Object]
Ontology,[object Object],“Ontology or the science of something and of nothing, of being and not-being of the thing and the mode of the thing, of substance and accident”,[object Object],G.W. Leibniz,[object Object],“… ontology, the science, namely, which is concerned with the more general properties of all things.”,[object Object],Immanuel Kant,[object Object],The nature of being,[object Object],Aristotle’s categories,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],67,[object Object]
Knowledge Representation (Davis, Shrobe, Szolovits, 1993),[object Object],Surrogate,[object Object],Set of ontological commitments,[object Object],through language and domain theory,[object Object],Fragmentary theory of intelligent reasoning,[object Object],sanctions heuristic adequacy,[object Object],Medium for pragm. efficient computation,[object Object],way of formulating problems (Newell),[object Object],Medium of human expression,[object Object],``Universal Character’’(Wilkins, Leibniz, … and Stefik, 1986),[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],68,[object Object]
Ontology Definitions,[object Object],Knowledge Management,[object Object],An explicit (knowledge level) specification of a conceptualization (a.o. Gruber, 1994),[object Object],Knowledge Representation,[object Object],An explicit (symbol level) specification of a conceptualisation,[object Object],Philosophy,[object Object],A formal specification of an ontological theory,[object Object],07-12-2010,[object Object],SIKS Course - Knowledge Modelling,[object Object],69,[object Object]

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Notas del editor

  1. Aristotle says that &apos;on the subject of reasoning&apos; he &apos;had nothing else on an earlier date to speak of’Logic seems to have emerged from dialectics; the earlier philosophers made frequent use of concepts like reductio ad absurdum in their discussions, but never truly understood the logical implications.Reduction ad absurdum: disprove a proposition by following its implications logically to an absurd consequence.
  2. Primary Substance (particulars), Secondary Substance (universals)Position -&gt; SittingState -&gt; Armed, Shod
  3. Trunk: variant of porphyry’s treeLeafs on the right: questionsLeafs on the left: keyed to rotating disk for generating answersWas a very friendly guy
  4. aggressively greedy, or grasping
  5. Computational view, influenced by LullPioneer in Symbolic LogicNumbers: Pythagoras, describe reality with numbers
  6. Procreativeorgans: stamen (stamina/stamens) : differentia between genera
  7. Formal language : FregeSyllogisms of Aristotle are limited: no variables, functions, quantifiers. No disjunction or conjunction
  8. … but that isn’t all
  9. Hier zit de heuristic adequacy al in!
  10. IPS: processor interacts with environment (effector, receptor), stores information in memoryProcessor consists of elementary information processes (eip) and an interpreter
  11. A frame system for the same cube, in different situations
  12. Interpretive attachments are procedural!
  13. Logical level -&gt; to give formal semantics to semantic networks