1. Knowledge Representation why bother ? what is it ? what do we represent ? how is it represented ? Kn Rep n 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 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 data facts procedural forms processing retrieval / linking / lumping inference

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

9. K n Rep n 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