1. Knowledge Representation
why bother ?
what is it ?
what do we represent ?
how is it represented ?
Kn Repn strategies
inferencing
example tasks

2. why bother ? intelligence & knowledge
reacting to sensory infm
using tools
communication
learning
human knowledge organisation
the messed up species

3. psychological clues interlinking cognitive limitations
voice – person – mood
sound/smell – memory – reminiscence
vis-ob – properties – ownership
cognitive limitations
levels of infm & retrieval
attention
short-term memory
field dependency

4. physiological clues perceptive pre-processing
brain areas & malfunctions
memory freezing
the elephant's toenail
unknown ownership / name
the speechless monk (Aitchison P.39)

5. who cares? feathers & flight random sorts
chaos, complexity & emergent behaviour

6. why bother ? a language example
The old man the boats.
I saw the racing pigeons flying to Paris.
I saw the Eiffel Tower flying to Paris.
The boy kicked the ball under the tree.
The boy kicked the wall under the tree.
Put the apple in the basket on the shelf

7. what is it ? declarative forms procedural forms inference data facts
processing
retrieval / linking / lumping
inference
encyclopaedia analogy

8. what do we represent ? objects (& their relationships)
events (& sequences)
performance (& cause & effect)
meta kn
extent, priority, strategy, reliability, importance

9. Kn Repn strategies facts & rules logic semantic nets frames scripts
conceptual dependency

10. a simple semantic net
has
yellow

11. general capabilities
inheritance
defaults
demons
perspectives

12. inferencing rule application & deduction generalisation
detecting similarity
measuring differences

13. tasks automatic rule generation IQ tests learning (near miss) planning
agent interaction (conflict & co-operation)
human dialog management