1. Introduction to AI & AI Principles (Semester 1) WEEK 5 (07/08) John Barnden Professor of Artificial Intelligence School of Computer Science University of Birmingham, UK

2. Further Difficulties with Language, 6 (review) uWhat look like definite references may actually be indefinite or general, or may fail to refer to anything at all, or may be incorrect. l Susan’s brother is helping her. This is OK even if Susan has several brothers, at least in suitable contexts. l The dog is an intelligent mammal. This would often/normally be a statement about dogs in general. l The square root of minus one doesn’t exist. l The man in the corner actually turned out to be a woman.

3. Further Difficulties with Language, 7 u“Quantification” is usually restricted even when there is no explicit restriction. l When Tom came into the room, everyone laughed. Probably means everyone in the room, with the further restriction of probably excluding Tom. Similar points would have applied if the sentence had said five people laughed. l Did someone drop a pen? Taken literally, the answer must be YES whatever the situation immediately at hand!

4. “pen” example contd. Did someone drop a pen? uFurther problems I thought of: l “pen” can mean an enclosure in which to keep animals, or a female swan, or …; it is also an abbreviation for “penitentiary”; it is also a verb meaning “enclose”. l “drop” as a verb can mean “abandon”. l The question is not about the past in general, but some contextually-determined limited period. uFurther problems U thought of: l “drop” is also a noun. As either a noun or verb it is vague. l The question is not only getting at a yes/no answer but also implicitly wants to know who dropped a pen. In fact, the “yes” may even be assumed by the speaker, so the implicit question may be the only one in effect. l Re “a”: is the question about a specific pen the speaker knows about, or about any pen (as in “Does someone have a pen?”). (Tell me if I’ve forgotten a suggestion U made.)

5. Further Difficulties with Language, 8 uEllipsis: omitting a bit of an utterance because of parallelism with some other bit. l Veronica donated a cake and Tom a bottle of wine. l Suzie chose chocolate ice-cream and Tim strawberry. l Suzie chose chocolate ice-cream. And Tim? Strawberry.

6. Further Difficulties with Language, 9 uMetonymy: referring to something indirectly, by referring to something related to it. l Other passports this way. l Peter likes Bach. Probably means he likes the music of Bach. l Plato is on the top shelf. l John boiled the kettle. l I’m parked in the corner. Probably means my car is! l That car wanted to overtake the lorry. l The ham sandwich is ready for his coffee. l England won. l That area of San Francisco has decided to rebuild. l John’s on the left of the picture.

7. Further Difficulties with Language, 10 uMetaphor: talking about something as if it were something else, typically of a qualitatively different type. l The department is a dictatorship. l Ralph is a pig. l We’re galloping towards Easter. l Easter’s rushing towards us. l In the depths of her mind she knew he was right. l Joy ran through him. l The variable jumps from 1 to 100. l The program dumps a lot of rubbish on the screen. l Managerialism is creeping into academia. l This list will run over the end of the slide if I don’t hold my horses!

8. Further Difficulties with Language, 11 uSpeech as opposed to text introduces extra problems, notably: l Ambiguity and variability of the acoustic signal as regards what basic sounds are present. l Word boundaries – where? l Extra info such as intonation.

9. Language as Representation Scheme uWe use language to represent the world in our communications … u… an perhaps even within our minds, to some extent … uSo why shouldn’t an AI system use human language as a way of internally representing things? uThe above problems get in the way, so people have developed artificial representation schemes (logic, semantic networks, frames, …) … u… but—CAUTION STUDENTS—those problems are also symptoms of the amazing flexibility and economy of human language. uNo artificial scheme yet developed has comparable power.

10. WHY IS EVERYDAY AI CHALLENGING? (continued)

11. Non-Language Examples In following slides … uInterpreting highly ambiguous shapes, e.g. in hand drawings. Seeing what’s in this room. uMoving around and performing actions. uPlanning actions. uMaking a cup of tea/coffee/cocoa.

12. Vision Needs in AI uSeeing what objects are around, where they are, how they’re moving, etc. … to some degree … uThat degree being dependent on the system’s purposes. uSeeing what the “affordances” (basically, possibilities of manipulation) of objects are, even if the objects can’t be specifically identified. uSome special things: l Recognizing faces. l Recognizing facial expressions, hand gestures, body movements. l Reading text, mathematical formulas, diagrams, etc.

13. Seeing What’s in (e.g.) this Room uDifficulty of seeing where/what even the basic surfaces and edges are: very noisy, corrupted signal. uProblem made more complex by shadows, reflections, transparency, distortion, texture, uneven lighting. uAmbiguity of component shapes—is it a wheel? Is it a head? Is it an orange? No … it’s … uOcclusion of objects. uSeeing objects from different angles. uJointed objects (e.g., people!) being in different configurations. uSoft and/or irregular objects such as clothes, crumpled paper.

14. Moving Around and Performing Actions uRemembering a “mental map” of some sort and knowing where oneself is in such a map. Keeping track of movements. Recognizing landmarks. uCreating such a map. uMoving arms, etc. to reach objects efficiently and safely. uGrasping (etc.) objects safely.