lec3ai2

3: Symbolic AI – Knowledge Representation: 

3: Symbolic AI – Knowledge Representation Outline Knowledge Representation schemes Structured object representations Semantic networks Frames Production systems Expert systems Learning outcomes Reading

Knowledge: 

Knowledge Knowledge – vital to intelligence 2 types of knowledge Declarative Procedural Also Domain-specific Domain-general

Representing knowledge: 

Representing knowledge Need to get knowledge from (human?) source Represent it in a form usable by a machine Need to represent Facts Relationships between facts Property inheritance All men are mortal Socrates is a man Socrates is mortal Procedural knowledge

Knowledge representation schemes…: 

Knowledge representation schemes… …Need to be: Expressive Different types of knowledge Different levels of knowledge Specific facts Generic information Clear Effective Infer new knowledge from old Efficient Explicit Explanation/justification

Semantic networks: 

Semantic networks isa Collins andamp; Quillian (1969)

Semantic nets - reasoning: 

Semantic nets - reasoning Network=data Reasoning – traverse arcs to identify relationships Collins andamp; Quillian (1969) Sentence verification task Canaries sing – 1310 ms Canaries have wings – 1380 ms Canaries have skin – 1470 ms

Semantic nets - problems: 

Semantic nets - problems Only simple ideas/relationships can be expressed quantification and intentional concepts are hard to represent in this formalism. Some birds fly All the birds sing some of the songs Some of the birds sing all the songs Mike thinks that Jane’s belief that Bernard will like their new home is false.

Frames: 

Frames More structured than semantic nets Nodes replaced by groups of information Frame – ‘slot and filler’ structure Slot – property Filler – value Can rep. Classes of entity or specific instances

Frames : 

Frames THE_STAND INSTANCE_OF: NOVEL AUTHOR: STEPHEN_KING NO_OF_PAGES: 1009 YEAR_PUBLISHED: 1978 ISBN_CODE: 0-340-35895-5 STYLE HORROR: NOVEL INSTANCE_OF: BOOK PURPOSE: ENTERTAINMENT HORROR MEMBER_OF: FICTION STEPHEN_KING INSTANCE_OF: HUMAN SEX: MALE YEAR_BORN: 1947

Problem with multiple inheritance: 

Problem with multiple inheritance NIXON INSTANCE_OF: HUMAN SEX: MALE MEMBER_OF: REPUBLICAN MEMBER_OF: QUAKER QUAKER PACIFIST: YES REPUBLICAN PACIFIST: NO

Production systems: 

Production systems RULE SET if andlt;conditionandgt; then andlt;actionandgt; if andlt;condition1andgt; andamp; andlt;condition2andgt; andamp; andlt;condition3andgt; … then andlt;action1andgt; andamp; andlt;action2andgt; … INFERENCE ENGINE WORKING MEMORY Fact1 Fact2 Fact3 …

Production systems - control: 

Production systems - control Global Forward-chaining (data-driven) Backward-chaining (goal-directed) Local (conflict resolution) Textual order Refractoriness Recency Specificity

Production systems – pros and cons: 

Production systems – pros and cons + ‘Natural’ and ‘plausible’ Record of problem-solving Modular Sensitive to change - Knowledge items not related Can get unwieldy Inflexible syntax

Slide14: 

Children’s subtraction errors: 

Children’s subtraction errors 63 44 21 96 42 44 70 47 37 72 57 20 70 47 30 Children’s errors are due to incorrect strategies rather than incorrect number facts Can model errors by adding/modifying/deleting rules Young andamp; O’Shea (1981)

MYCIN – an expert system: 

MYCIN – an expert system Diagnosis and treatment of bacterial blood infections Consults with Doctor in English Collects info about patient Collects info about lab tests Reasons with set of production rules Can explain reasoning behind decisions Can acquire new knowledge with the aid of TEIRESIAS

Learning Outcomes: 

Learning Outcomes Demonstrate an understanding of issues in knowledge representation Understand different knowledge representation schemes Show an awareness of some of the applications of systems constructed according to these schemes

Reading: 

Reading See list FOR NEXT WEEK, READ: Searle, J. R. (1981). Minds, brains, and programs. Available in: Study pack Boden, M.A. (1990). The philosophy of artificial intelligence. OUP. Haugeland, J. (1997). Mind design II. MIT Press.