Lecture � MIT MAS962

Greg Detre

Tuesday, November 12, 2002

 

Presentation � Erik, ThoughtTreasure

Deb: how straightforward was it to drop ThoughtTreasure into CycL?

grids are basically a set of assertions � when converted into CycL, he just bundled all the coordinates into a single assertion

the hard problem he�s trying to address is story understanding

the make sense rating

there are weights at every level of processing (even down to the lexical level, to signal archaic etc.)

do those weights have to be hard-coded too???

yes, they�re set manually

is there a hope that the mass of interactions between lots of different weights, and at different levels, will just end up robust somehow???

Deb: what�s the resolution of the weights?

they�re just a decimal between 0 and 1

Erik would prefer it to be done by some sort of reasoning or automated process eventually�

the assertions don�t have weights

ThoughtTreasure doesn�t have Cyc-like contexts

he started coding some philosopher belief systems, in the form �A believes X�, but there�s no other major context mechanism

models

his methodology is: construct simulations of the states and events described in the utterance

read: Johnson-Laird (1993), Human and machine thinking � agrees with the model approach

the ThoughtTreasure approach is to use diverse representation schemes to generate lucid representations

how would his grids cope with the table rotated 37deg???

presumably, it would simply try and map the real world story onto the representation-simplification, rather than trying to accurately represent the real world � but that does impose a ceiling on how well it can ever perform (and there�s a quantum leap between these simplifications and representations that can (potentially) scale to real-world complexity)

presumably, his hope is that you could insert a lower level that could build complicated models that could be schematised into ThoughtTreasure form

goals:

can either be binary achievements, or analog

understanding agents:

why this approach?

convenience of modularisation

you can answer any question up to a certain level of granularity

similar to: Karma � X-schemas???

grids:

can it do spatial reasoning with the grids???

distance, relative positions, line of sight/hearing, path-finding

Deb: if Jim and Bob are in an L-shaped room, can they see each other?

ThoughtTreasure will instantiate the room concretely � the answer will depend on how it instantiates things

Deb: you could leave levels of Kuipers� spatial semantic hierarchy unbound

problems he has: how do you dynamically instantiate a grid

could you not circumvent most of these common sense na� physics conundrums by interrogating a semi-realistic 3D physics model???

well, how do you leave things unbound in such a model???

rather than doing a coarser grid, maybe you should use a topology/containment approach (which he already has at the object-level)

Deb: he�s all for multiple representations, if you can move between them

automated + semi-automated acquisition techniques:

e.g. adding grids using Open Mind

can planning + understanding agents be learned?

Brian: does he have a systematic evaluation method?

similar approach to the information-extraction competitions

c. 40 baseline questions for story understanding, that you can ask after more or less every sentence

e.g. what�s the character�s goal, what did he do, what�s his emotional response etc.

if it doesn�t know the answer, it produces nothing

you can ask it more or less anything that it understands syntactically, and that it is able to represent within its story system

however, it�s a very baby syntax, and a very limited repertoire of encoded story-simulations

you also have a combinatoric problem, e.g. if you have five interacting goals

Deb: is there a notion of conceptual primitives (vs derived)?

he asked my question!!! you could list endless inferences like �you sleep lying down�, but you wouldn�t need to if you had a physics/sleep model � are you starting to see some primitives?

Vegas � the Manifesto for Lexicons:

concludes that conceptual primitives don�t work, and advocates a conceptual primitive for every concept

his aim with ThoughtTreasure was to let the primitives emerge from the mass

Deb: what do words mean to ThoughtTreasure � what does a word like �sleep� mean, and what bindings does it have?

sleep might have 5 inflections, linked to the sleep concept node, which will be linked to a bunch of assertions

shrdlu � the lack of modularity of design leads to a lack of ways of thinking of about it

open mind � comes closer to Pustejovsky�s aristotelian categories, because it has the templates, but they�re pretty shallow

how did he decide on the workings of emotional finite state automata???

Ortony�Collins model of emotions � it�s missing some, though they�re to be found elsewhere in the ontology

given the domains he�s chosen to focus on, is it at the stage where it could read and learn from children�s stories???

it will produce a parse of a text � you can then try and generalise from those, somehow (though it hasn�t been implemented yet)

so I spose the answer is, �kind of�

there�s an information-extraction feature that outputs NL information into its own KR format

choice of representation:

Lavecque � �lucid� (logic): for every predicate, for every possible sequence of arguments, you have to know whether they�re true (given finite universe of symbols)

completely unambiguous, corresponds to a single model in logic

e.g. a complete 3D model of something, or in logic the closed world assumption

Push: lucid doesn�t have to be very concrete

but it does have to be fully-specifiable, right???

a lot of problems came up using non-lucid representations, e.g. in logical AI (huge problems of theorem-proving combinatorial explosions blowing up with non-lucid representation)

also, you have the problem with the frame-problem � for it to be a lucid representation of something that involves time, you have to a have a full specification of state for that entire time period

automated augementation of you�re the representations he has

trying to build new planning agents from corpus-based project (reading stories)

difficult parts: sequences, loops, conditioned-gotos, goal, links to lexical entries

new representations:

what about introducing a na� physics model?

currently, all of that�s implemented as procedural knowledge

but if you want to invert that procedural knowledge, to abduction (where you know the conclusion, and part of the middle, and you want to fill in some more assumptions etc.), he doesn�t know how

the declarative versions of the planning agents which he built to try and solve this problem aren�t as rich

Deb: for abduction, can�t you just enumerate all the different state paths that could have got you there?

combinatorial explosion

Hobbes � Tacitus � logical story understanding � incorporates a metric for doing abduction to minimise the number of links

you could use Bayesian rules to narrow that search � it seems analogous to the techniques used in speech recognition (again, it�s just nodes with directed links)

Deb: does the machine have a goal?

the goal is to find the highest make-sense rating though, isn�t it???

the goal is implicit in the mechanisms, isn�t it???

you need there to be more than one goal, and a choice of actions, in order for it to be meaningfully a goal

Push: if the machine can measure whether it�s making progress, it can have a goal

he wrote Daydreamer 15 years ago� multiple goals, meta-goals, executive functions, connected to emotional data structures

Deb: fast car vs fast road � modularity of concepts, modifying each other in different ways � if you haven�t come across one combination before, is there any mechanism for dealing with that

Pustejovsky is factoring the complexity, rather than just trying to encode facts willy-nilly

Deb: likes procedural knowledge

how do you deal with contradiction???

e.g. animals often speak in children�s stories

Lenat, �12 dimensions of context space� (quite recent)

different from Cyc context

e.g. region, temporal, etc.

specify the context by twiddling those parameters

Push: he wouldn�t have been able to come up with that without just ploughing through loads of assertions

Questions

Mueller

rich, but brittle???

what does TT do that CyC doesn�t???

grids, scripts, different/simpler encoding, multi-lingual

how is it going to scale??? learn???

how does it deal with contexts???

see above � it doesn�t really

how flexible are the grids???

what do you hope to gain from being bi-lingual???

started out as a translation system

reminds you to stay general/cross-linguistic???

y, helped him find the appropriate level of generality

IBM funds this, right??? how???

Project

is he happy for 1-D space???

how did he envisage investigating the space vs time cross-over???

is he not worried that the effects noted by Boroditsky�s experiments are particular to the human brain, and that we might need all sorts of idiosyncratic baggage to replicate them???

is there any reason to think that they would result from almost any space+time representation???

what does he hope to achieve by replicating them??? is he interested in showing some sort of biological plausibility???

how does he feel about using connectionist/hybrid representations???

which prepositions does he want to start with??? how many??? is there a sort of critical mass of prepositions you can use in your spatial communications???

I suggested near, then front/back:

�I could focus on the cross-over from representing space to representing time. The best way that I�ve come up with of doing this would be to have the objects approaching at different speeds. I think this would still be possible within a one-dimensional world, which is why I chose near/soon as my central proposition, with front/coming as potentially a secondary proposition, to investigate.

I think that investigating the temporal effects would be more likely to work, and might be potentially more interesting. However, I suspect that the most interesting effects, like the ego- vs time-moving representations, would require a pretty advanced cognitive architecture to be seen. Indeed, they must be contingent to some degree on the particular way in which the human brain represents space, time and movement, and I can�t yet see how to strip away the extraneous factors to model them. If we were investigating time in a two-dimensional world, then it might eventually also be possible to consider horizontal vs vertical linguistic conceptions of time as well.�

he said:

�I just looked at your proposal. First comment is that I had asked for only one page -- that helps force you to focus more than you have here. I think of your two final ideas, the second is better. We can talk sometime next week about how to make it a practical project. Lera's suggestion is to look at 'ahead' and 'behind' as a good starting point for time-space conversion.�

Allen

is this is the major NL book???

can you really differentiate between general knowledge and knowledge of a specific situation???

Admin

next week:

cognitive science

theory theory (Josh Tanenbaum)