Grad A: Alright , so I 'm - I should read all of these numbers ?
Professor B: OK .
Grad E: Piece of paper ? I could borrow ?
Grad A: Oh yeah .
Professor B: OK , so uh i um I don't know whether Ami 's coming or not um but I think we oughta just get started .
Grad E: Nancy is uh currently in Berkeley but not here ?
Grad C: Nancy 's still stick ?
Professor B: Don't know . Anyway
Grad E: OK .
Professor B: Oh , so there you go . Anyway , so my idea f for today and we can uh decide that that isn't the right thing to do was to at spend at least part of the time trying to eh build the influence links , you know which sets of things are uh relevant to which decisions and actually I had uh specific s suggestion to start first with the path ones . The database ones being in some sense less interesting to us although probably have to be done and so to do that so there 's and the idea was we were gonna do two things
Grad C: Is your mike on ?
Professor B: Ah . Oh right , well . Yeah . We were gonna do two things one of which is just lay out the influence structure of what we think influences what
Grad D: That 's funny .
Professor B: and then as a uh separate but related task uh particularly Bhaskara and I were going to try to decide what kinds of belief nodes are needed in order to um do what we what we need to do . Once so but du we should sort of have all of the uh basic design of what influences what done before we decide exactly how to compute it . So I didn't did you get a chance to look at all yet ?
Grad D: Yeah , I looked at some of that stuff .
Professor B: Great . OK so let 's start with the uh belief - nets , the general influence stuff and then we 'll then we 'll also at some point break and talk about the techy stuff .
Grad E: Well I think one could go there 's I think we can di discuss everything . First of all this I added , I knew from sort of basically this has to be there right ? Um
Professor B: Oh are you gonna go there or not ? Yeah , so one i
Grad E: Given given uh uh not transverse the castle , the decision is does the person want to go there or is it just
Professor B: Right , true . Does have to be there . And I 'm sure we 'll find more as we go that
Grad E: And Hmm ? So Go - there in the first place or not is definitely uh one of the basic ones . We can start with that . Interesting effect . Um Is this basically true or false or maybe we 'll get
Professor B: Well Grad D: Which one ?
Grad E: what ?
Grad A: " Go there " .
Grad E: m right .
Professor B: so there is this question about
Grad E: Here we we actually get just probabilities ,
Professor B: Yeah .
Grad E: right for each down here .
Professor B: When we 're yeah when we 're done . So so
Grad E: Hmm .
Professor B: the the reason it might not be true or false is that we did have this idea of when so it 's , you know uh current @ @ and so forth and so on or not at all ,
Grad E: Mm - hmm .
Professor B: right ? And so that a decision would be do we want that so you could two different things you could do , you could have all those values for Go - there or you could have Go - there be binary and given that you 're going there when .
Grad E: When . How .
Professor B: Yeah and so forth .
Grad E: Why ,
Professor B: So I 'll let
Grad E: yeah .
Professor B: we 'll see .
Grad E: Hmm ?
Grad A: I mean it seems that you could um uh it seems that those things would be logically independent like you would wanna have them separate or binary , Go - there and then the the possibilities of how to go there because Professor B: OK , that 's let 's start that way .
Grad A: because , you know it might be easy to figure out that this person is going to need more film eventually from their utterance but it 's much more complex to query when would be the most appropriate time .