E: But
B: because I want to do a little bit of organization .
B: Before we get more into details .
B: The organization is going to be that uh
B: the flavor of what 's going on is going to be that uh
B: as we s e sort of going to this detail indeed Keith is going to to worry about the various constructions that people might use
A: Mm - hmm .
B: and Johno has committed himself to being the parser wizard ,
B: so what 's going to happen is that eventually
A: Alright .
B: like by the time he graduates ,
B: OK
B: uh they 'll be some sort of system which is able to take the discourse in context and have outputs that can feed the rest of belief - net .
B: I j wa I I assume everybody knows that ,
B: I just wanna you know , get closure that that 'll be the game then ,
A: Mm - hmm .
B: so the semantics that you 'll get out of the discourse will be of values that go into the various discourse - based decision nodes .
B: And now some of those will get fancier like mode of transportation and stuff
B: so it isn't by any means uh necessarily a simple thing that you want out .
B: So uh if there is an and there is mode of transportation
E: And it there 's a sort of also a split if you loo if you blow this up and look at it in more detail there 's something that comes from the discourse in terms of what was actually just said
E: what 's the utterance go giving us
B: Yeah .
E: and then what 's the discourse history give us .
B: Yeah , well that , well , we 'll have to decide uh how much of th where that goes .
A: Mm - hmm .
E: That 's uh two things then .
E: Mmm .
A: Mm - hmm .
B: an and it 's not clear yet .
B: I mean it could be those are two separate things ,
B: it could be that the discourse gadget itself integrates em as B: which would be my guess
B: that you 'd have to do see in order to do reference and stuff like that um you 've gotta have both the current discourse and the context to say I wanna go back there ,
B: wow , what does that mean
A: Mm - hmm .
B: and uh
E: Mm - hmm
A: Now .
A: Mm - hmm .
B: Alright .
B: So
E: But is th is this picture that 's emerging here just my wish that you have noticed already for symmetry
E: or is it that we get for each each decision on the very bottom we sort of get the sub - E , sub - D , sub - U and maybe a sub - O " O " for " ontology " um meta node
B: I don't know .
E: but it might just
B: It could be .
E: could be
E: so this
B: This is this is getting into the thing I wanna talk about next ,
B: which is s if that 's true uh how do we wanna combine those ?
B: O or when it 's true ?
E: but this eh w wou wou would be nice though that , you know , we only have at most four at the moment um arrows going f to each of the uh bottom decisions .
B: Yeah .
D: Yeah .
E: And four you we can handle .
B: No .
E: It 's too much ?
D: Yeah .
B: Well i i it see i if it 's fou if it 's four things and each of them has four values it turns out to be a big CPT ,
B: it 's not s completely impossi
B: I mean it 's it 's not beyond what the system could solve
B: but it 's probably beyond what we could actually uh write down . or learn .
E: Right , true .
B: Uh but , you know it 's four to the fourth .
B: It 's pretty big .
B: Uh .
C: Two fifty - six ,
C: is that what that
B: Yeah .
B: Yeah , I mean
B: it 's and I don't think it 's gonna g e I don't think it 'll get worse than that by the way ,
B: so le that 's a that 's a good
D: Mmm yeah .
E: But but four didn't we decide that all of these had true or false ?
E: So is it 's four
B: Uh for go there ,
B: but not f but not for C: Yeah .
B: the other one 's three values for endpoint already .
D: Yeah , I mean you need actually three to the five
D: because uh well I mean if if it has four inputs and then it itself has three values
C: Right .
D: so
D: I mean it can get big fast .
E: Um for endpoint ?
E: No it 's it 's sh
B: EV - it 's the EVA .
E: yeah , down here ,
E: but this one only has two .
D: No it still has three ,
B: No .
B: Since ta they will still have three .
D: EVA .
B: Each so you 're uh uh from each point of view you 're making the same decision .
A: Mm - hmm .
B: So from the point of view of the ob of the entity
A: Mm - hmm .
E: Want to view that ,
E: yeah yeah .
E: C sl
E: yeah
B: Yeah .
D: This and also , I mean , the other places where ,
D: like for example consider endpoint view , it has inputs coming from user budget , user thrift
B: Right .
D: so even
B: Those are not necessarily binary .
B: S so we 're we 're gonna have to use some t care in the knowledge engineering to not have this explode .
B: And in fact I think it doesn't in the sense that
B: um
B: Read it ,
B: you know actually with the underlying semantics and stuff I think it isn't like you have two hundred and fifty - six different uh ways of of thinking about whether this user wants to go to some place .
B: Alright .
B: So we we just have to figure out what the regularities are and and code them .
B: But um What I was gonna suggest next is maybe we wanna work on this a little longer
B: but I do want to also talk about the thing that we started into now of
B: uh
B: well it 's all fine to say all these arrows come into the si same place
B: what rule of combination is used there .
B: So th yes they so these things all affect it ,
A: Mm - hmm .
A: Right .
B: how do they affect it ?
B: And belief - nets have their own beliefs about uh what are good ways to do that .
B: So is it it 's it 's clearer n clear enough what the issue is ,
D: Right .
B: right ?
B: So do we wanna switch that now or we wanna do some more of this ?
E: R basically w we just need to sort of
E: in order to get some closure on this figure out how we 're gonna get this picture sort of uh completely messy .
B: Well , here he here 's one of the things that that I th you sh
B: you no ,
B: I don't know how easy it is to do this in the interface
B: but you it would be great if you could actually just display at a given time uh all the things that you pick up ,
B: you click on " endpoint " ,
B: OK
E: Mm - hmm .
B: and everything else fades
B: and you just see the links that are relevant to that .
B: And I
B: does anybody remember the GUI on this ?
C: Uh d I would almost say the other way to do that would be to open u or make you know N - many belief - nets
C: and then open them every time you wanted to look at a different one
E: Mm - hmm .
C: vers
E: It 's probably pretty easy do it to do it in HTML ,
C: cuz uh
E: just C: Yeah , but
E: Uh
D: HTML ?
E: Yeah I have each of these thing each of the end belief - nets be be a page and then you click on the thing
E: and then li consider that it 's respective ,
D: OK .
B: Yeah the well the b
E: but
B: anyway so uh it clear that even with this if we put in all the arrows nobody is gonna be able to read the diagram .
C: Yeah .
B: Alright ,
B: so e we have to figure out some eh eh uh basically display hack or something to do this
B: because
B: anyway I I let me consi suggest that 's a s not a first - order consideration ,
B: we have two first - order considerations
B: which is what are the uh influences A ,
B: A ,
B: and B how do they get combined mathematically ,
B: how do we display them is an issue ,
B: but
B: um
C: I don't , yeah I just don't think this has been designed to support something like that .
D: Yeah .
D: Yeah , I I mean , it might soon , if this is gonna be used in a serious way like java base then it might soon be necessary to uh start modifying it for our purposes .
B: Right .
B: Yeah , and Um I that seems like a perfectly feasible thing to get into ,
B: but um we have to know what we want first .
B: OK , so why don't you tell us a little bit about decision nodes and what what the choices might be for these ?
D: So
D: Ah , sorry .
D: I guess that 's
C: You can technically wear that as you 're talking .
D: Yeah , it 's right , I guess I can do that .
A: Darn .
B: Put it in your ,
B: yeah .
D: I guess this board works fine .
D: So um recall the basic problem which is that um you have a belief - net and you have like a lot of different nodes all contributing to one node .
D: Right ?
D: So as we discussed specifying this kind of thing is a big pain
D: and it 's so will take a long time to write down
D: because for example if these S have three possibilities each and this has three possibilities then you know you have two hundred and forty - three possibilities
D: which is already a lot of numbers to write down .
D: So what um helps us in our situation is that these all have values in the same set ,
D: right ?
D: These are all like saying EV or A ,
D: right ?
D: So it 's not just a generalized situation like
D: I mean basically we wanna just take a combination of D: we wanna view each of these as experts
D: ea who are each of them is making a decision based on some factors
D: and we wanna sort of combine their decisions
D: and create you know , um sorta weighted combination .
E: Hmm .
E: ROVER , the ROVER decision .
D: The what decision ?
E: ROVER .
E: All of their outputs combined to make a decision .
A: Hmm .
D: Yeah .
D: Yeah .
D: So the problem is to specify the uh so the conditional property of this given all those ,
D: right ?
D: That 's the way belief - nets are defined ,
D: like each node given its parents ,
D: right ?
D: So um that 's what we want ,
D: we want for example P of um
D: let 's call this guy Y
D: and let 's call these X - one , X - two XN ,
D: right .
D: So we want probability that Y equals , you know , for example um E
D: given that these guys are
D: I 'll just refer to this as like X um hat or something ,
D: uh the co like all of them ?
D: Given that for example the data says you know , A , V , A , E , or something
D: right ?
B: Yep .
D: So we would like to do this kind of combination .
B: Alright , so
B: um
B: Is that uh
B: I yeah , I just wanna make sure everybody is with us before he goes on .
A: I think so , yeah .
B: It 's it 's cl e is is it clear what he wants to compute ?
D: Right .
A: Mm - hmm .
D: So , right .
D: So Basically um what we don't wanna do is to for every single combination of E and V and A and every single letter E , s give a number
D: because that 's obviously not desirable .
A: Mm - hmm .
D: What we wanna do is find some principled way of um saying what each of these is
D: and we want it to be a valid probability distribution ,
D: so we want it to um add up to one ,
D: right ?
D: So those are the two things that we uh need .
A: Hmm .
D: So what uh I guess , what Jerry suggested earlier was basically that we , you know view these guys as voting
D: and we just take the uh we essentially take um averages ,
D: right ?
D: So for example here two people have voted for A ,
D: one has voted for V ,
D: and one has voted for E ,
D: so we could say that the probabilities are , you know , probability of being E is one over four , because one person voted for E out of four
D: and similarly , probability of
D: so this is probability of E
D: s and then probability of A given all that is um two out of four
D: and probability of V is one out of four .
D: Right ?
D: So that 's step that 's the uh yeah that 's the that 's the basic uh thing .
D: Now
E: Um
E: Yeah .
D: Is that all OK ?
E: And that one outcome , that 's
B: What ?
E: it 's X X - one voted for A
E: X - two voted for V
A: Mm - hmm .
E: and so forth ?
B: Y right .
E: Yeah .
B: Yep .
D: Yeah .
E: That 's the outcome .
B: S so this assumes symmetry and equal weights and all this sort of things , which may or may not be a good assumption ,
A: Mm - hmm .
B: so that
A: Right .
D: Yeah .
D: Yeah .
D: So step two is um
D: right .
D: So we 've assumed equal weights
D: whereas it might turn out that you know , some w be that for example , what the um the actual the uh verbal content of what the person said , like what uh what might be uh somehow more uh important than the uh
C: X - one matters more i than X - two or
D: Right .
D: Sure , so we don't wanna like give them all equal weight
D: so currently we 've been giving them all weight one fourth
D: so we could replace this by uh W - one , W - two , W - three , and W - four
D: right ?
A: Hmm .
D: And in order for this to be a valid probability distribution for each um X - hat , we just need that the W 's sum to one .
D: So they can be for example , you know
D: you you could have point one , point three , point two , and point four , say .
E: That 's one .
D: And that 'd be one .
D: So that um also seems to work fine .
D: And uh
C: So I jus just to make sure I understand this , so in this case um we would still compute the average ?
D: You 'd compute the weighted average ,
D: so the probability of E would be uh
C: OK , so C: so it 'd be so in this case the probability that Y equals A would be uh <comment> W one times A: Point three .
C: or A or C: let 's see ,
C: one full quarter times point one
D: Not one quarter ,
D: so these numbers have been replaced with point one , point three , point two , and point four .
A: No .
D: So you can view these as gone .
C: OK .
D: Probability of
C: OK .
D: Yeah .
D: Yeah .
D: OK .
D: So ,
D: alright .
D: So this is uh step two .
D: So the next possibility is that um we 've given just a single weight to each expert ,
D: right ,
D: whereas it might be the case that um in certain situations one of the experts is more uh reliable and in certain situations the other expert is more reliable .
D: So the way this is handled is by what 's called a mixture of experts ,
D: so what you can have is
D: you augment these diagrams like this
D: so
D: you have a new thing called " H " ,
D: OK ?
D: This is a hidden variable .
D: And what this is is it gets its input from X - one , X - two , X - three , and X - four ,
D: and what it does is it decides which of the experts is to be trusted in this particular situation .
D: Right ?
D: And then these guys all come here .
D: OK .
D: So this is sightly uh more complicated .
D: So what 's going on is that um this H node looks at these four values of those guys
D: and it decides in given these values which of these isn't likely to be more reliable or most reliable .
D: So H produces some you know , it produces a number ,
D: either one , two , three , or four , in our situation ,
D: right ?
D: Now this guy he looks at the value of H
D: say it 's two ,
D: and then he just selects the uh thing .
D: That 's all there is to say , I guess about it .
E: Mm - hmm .
D: Right , so you can have a mixture that
D: Right .
A: So so the function of the thing that comes out of H is very different from the function of the other inputs .
A: It 's driving how the other four are interpreted .
A: OK .
D: Yeah .
D: Yeah .
C: So H passes a vector on to the next node ?
D: It could .
C: It could ?
C: A vector of the weights as the se
D: Yeah , it could
C: oh .
D: Sorry ?
A: Well a vector with three zero 's and one one ,
A: right ?
C: Oh it 's basically to tell the bottom node which one of the situations that it 's in
C: or which one of the weighting systems
D: Right , so I mean the way you desc
C: W I was just , if you wanted to pay attention to more than one you could pass a w a weighting s system though too ,
C: couldn't you ?
C: OK .
A: Um Does H have to have another input to tell it alpha , beta , whatever , or is the A: that 's determined by what the experts are saying ,
A: like the type of situ
A: OK .
A: Hmm .
A: OK .
A: OK .
A: I mean It it just seems that like without that that outside input that you 've got a situation where , you know , like if if uh X - one says no ,
A: you know , a low value coming out of X - on
A: or i if X - one says no then ignore X - one ,
A: you know ,
A: I mean that seems like that 'd be weird ,
D: Yeah , well could be things like if X - two and X - three say yes then i ignore X - one also .
A: right ?
A: Oh , OK .
A: OK .
A: Alright , right .
C: Oh The situations that H has , are they built into the net
C: or
C: OK , so they they could either be hand coded or learned or
C: OK .
D: Yeah .
C: Based on training data ,
C: OK .
D: Yeah .
D: Yes .
C: So you specify one of these things for every one of those possi possible situations .
C: Oh yeah .
D: Yeah .
D: Um Well , I mean to learn them we need data ,
D: where are we gonna get data ?
D: Well I mean we need data with people intentions ,
D: right ?
A: Right , right .
D: Which is slightly tricky .
D: Right .
A: Uh - huh .
D: Mm - hmm .
D: But what 's the data about
D: like , are we able to get these nodes from the data ?
A: Like how thrifty the user is ,
A: or do we have access to that ?
A: Mm - hmm .
A: Oh right .
A: Oh good .
D: Yeah .
A: OK .
A: Mm - hmm .
A: Mm - hmm .
A: OK .
D: Yeah , but that 's my question ,
D: like how do we I mean , how do we have data about something like um um endpoint sub - E ,
D: or endpoint sub uh you know s S ?
C: Well , basically you would say , based on in this dialogue that we have which one of the things that they said eh whether it was the entity relations or whatever was the thing that determined what mode it was ,
D: Mmm .
D: Mmm .
C: right ?
D: So this is what we wanna learn .
D: Yep .
D: Right .
D: Hmm .
D: Yeah .
D: I don't think ,
D: well you have a D: can you bring up the function thing ?
D: Um w where is the thing that allows you to sort of
C: That 's on the added variable ,
C: isn't it ?
D: Oh function properties ,
D: is that it ?
D: Hmm , I guess not .
D: Yeah , that 's
A: No .
D: Right .
D: OK .
D: And um it so e either it 'll allow us to do everything
D: which I think is unlikely ,
D: I think more likely it 'll allow us to do very few of these things
D: and in that case we 'll have to um just write up little things that allow you to um create such CPU 's on your own in the java base format .
D: Yeah .
D: Yeah .
D: Yeah , I was assuming that 's what we 'd always do
D: because
D: yeah I was assuming that 's what we 'd always do ,
D: it 's
D: Right .
D: Yeah .
C: Ah .
C: Well in terms of java base I think it 's basically what you see is what you get in
C: I don't
C: yeah ,
C: I would be surprised if it supports anything more than what we have right here .
A: So
A: Yeah .
A: Yeah .
A: By the way um uh just talking about uh about that general end of things
A: uh is there gonna be data soon from what people say when they 're interacting with the system and so on ?
A: Like , I mean , what kind of questions are being given being asked ?
A: Cuz A: OK .
A: Yeah yeah .
A: OK .
A: OK .
A: Fey , you mean .
A: OK .
A: OK .
A: O OK .
A: OK .
A: I 'm just wondering , because in terms of , you know ,
A: I mean
A: uh w
A: the figure I was thinking about this figure that we talked about ,
A: fifty constructions or whatever
A: that 's uh that 's a whole lot of constructions
A: and um you know , I mean one might be f fairly pleased with getting a really good analysis of five maybe ten in a summer
A: so , I mean I know we 're going for sort of a rough and ready .
A: Mm - hmm .
A: Mm - hmm .
A: OK .
A: OK .
A: I mean , I I I I was uh I was talking about the , you know , if you wanted to do it really in detail