Module 5 Other Knowledge Representation Formalisms

Semantic Nets

KNOWLEDGE REPRESENTATION: 1960’S NETWORKS & MEANING Ross Quillian (1966 and 1968) was among the early AI workers to develop a computational model which represented 'concepts' as hierarchical networks. This model was amended with some additional psychological assumptions to characterise the structure of [human] semantic memory.

KNOWLEDGE REPRESENTATION: 1960’S NETWORKS & MEANING Concepts can be represented as hierarchies of inter- connected concept nodes (e.g. animal, bird, canary) Any concept has a number of associated attributes at a given level ( e.g. animal --> has skin; eats etc.) Some concept nodes are superordinates of other nodes (e.g. animal >bird) and some are subordinates (canary< bird)

KNOWLEDGE REPRESENTATION: 1960’S NETWORKS & MEANING (2) For reasons of cognitive economy, subordinates inherit all the attributes of their superordinate concepts • Some instances of a concept are excepted from the attributes that help [humans] to define the superordinates (e.g. ostrich is excepted from flying) Various [psychological] processes search these hierarchies for information about the concepts represented

KNOWLEDGE REPRESENTATION : 1960’S NETWORKS & MEANING bird can fly, has wings, has feathers salmon lays eggs; swims upstream, is pink, is edible ostrich runs fast, cannot fly, is tall canary can sing, is yellow fish can swim, has fins, has gills animal can breathe, can eat, has skin is-a A Hierarchical Network The figure shows a hierarchical semantic network, where nodes denote names of objects and the (arrowed) links indicate relationship between objects. This is really a taxanomy described using the semantic network formalism. The 'semantic memory' model was amended with some additional psychological assumptions to characterise the structure of [human] semantic memory. Collins and Quillian (1969) proposed that 'concepts' can be represented as hierarchies of inter-connected concept nodes (e.g. animal, bird, canary), and that a concept may have a number of associated attributes at a given level ( e.g. animal --> has skin; eats etc.). The authors also suggested that some of the nodes in the hierarchies may be regarded as superordinate node (e.g. animal >bird) and some are subordinates (canary< bird). @Anupam Basu

NETWORKS & MEANING canary fish Inheritance animal can breathe, can eat, has skin bird can fly, has wings, has feathers salmon lays eggs; swims upstream, is pink, is edible ostrich runs fast, cannot fly, is tall canary can sing, is yellow fish can swim, has fins, has gills is-a Inheritance Specifics can be more detailed Can be overridden --- cannot fly

NETWORKS & MEANING canary fish animal can breathe, can eat, has skin bird can fly, has wings, has feathers salmon lays eggs; swims upstream, is pink, is edible ostrich runs fast, cannot fly, is tall canary can sing, is yellow fish can swim, has fins, has gills is-a Tests on human subjects showed that the subjects recognise propositions lower down the hierarchy (canary is a yellow bird) more readily than propositions higher up the hierarchy (canary has skin).

NETWORKS & MEANING A semantic network is a structure for representing knowledge as a pattern of interconnected nodes and arcs. Nodes in the net represent concepts of entities, attributes, events, values. Arcs in the network represent relationships that hold between the concepts animal can breathe, can eat, has skin bird can fly, has wings, has feathers salmon lays eggs; swims upstream, is pink, is edible ostrich runs fast, cannot fly, is tall canary can sing, is yellow fish can swim, has fins, has gills is-a The figure shows a hierarchical semantic network, where nodes denote names of objects and the (arrowed) links indicate relationship between objects. This is really a taxanomy described using the semantic network formalism. The 'semantic memory' model was amended with some additional psychological assumptions to characterise the structure of [human] semantic memory. Collins and Quillian (1969) proposed that 'concepts' can be represented as hierarchies of inter-connected concept nodes (e.g. animal, bird, canary), and that a concept may have a number of associated attributes at a given level ( e.g. animal --> has skin; eats etc.). The authors also suggested that some of the nodes in the hierarchies may be regarded as superordinate node (e.g. animal >bird) and some are subordinates (canary< bird).

NETWORKS & MEANING C111 C11 C112 C1 C121 C12 Concepts labeled C111 and C112 inherit all the attributes of C11 which, in turn, inherits all the attributes of C1; similarly C121 inherits attributes of C12 and C12 of C1. All arcs are labeled is-a, which relates superordinates (C1) to subordinates (C11, C12) to instances (C111, C112, C121). C1 C1’s attributes C11 C11’s attributes C121 C121’s attributes C112 C112’s attributes C111 C111’s attributes C12 C12’s attributes is-a

The semantics lies not in the structure alone, but also requires the relations animal can breathe, can eat, has skin bird can fly, has wings, has feathers salmon lays eggs; swims upstream, is pink, is edible ostrich runs fast, cannot fly, is tall canary can sing, is yellow fish can swim, has fins, has gills EAT is-a The above network is identical to the previous example, but NOW is interpreted as “Salmon eat fish” and “Fish eat animals”

Semantic Net and Logic is_a is_a person Tom mammal has_part head Would be represented in logic as: is_a(person, mammal), instance(Tom, person), has_part(person, head)

Representation in a Semantic Net Game is_a Spurs G5 3 - 1 Score Loser Winner Norwich How represent predicates with more than two places (e.g. score (Norwich, Spurs, 3 – 1)? Create new node(s) to represent objects contained, or alluded to, in the original semantic net.

A More Complicated Example “John gave Mary the book” Mary John Book Book_69 Gave Event 1 Agent Object Action Instance Recipient

Another Example Build a semantic net that represents the following knowledge: Man(Marcus) Married(Marcus,Madonna) GaveTo(Madonna,Marcus,Measles)

Man Marcus Madonna Measles G17 Give-Action married instance Man Marcus Madonna getter giver Thing given instance Measles G17 Give-Action