Hi. Eventually, after over a week and a half, the results for the QOTD for
the Saturday a week and a half ago. Only Patrick answered this one, so
I put both mine and his here.

I found Patrick's answer to be much more enlightning than mine. Anyway, before
answering the question I had no clue as to the answer, and now at least I
do have one :-)

> 
> What ways of Model formation are there in Qualitative Reasoning?
> 


Eyal
====

Model formation in QR means that we try to form some "rules" and histories
for the examined system. This is modeling in the "model based reasoning" sense.
We try to form the exact axioms that describe the system. Note that we start
with a given domain theory, and reduce it to the specific task at hand.

P.12: "Models are created from domain theories, which describe the kinds of
entities and phenomena that can occur in a physical domain. A domain theory
consists of a set of model fragments, each describing a particular aspect of
the domain. Creating a model is accomplished by instrantiating an appropriate
subset of the model fragments."

1. Instantiate every law in the domain theory with the possible objects.
	This way we can avoid quantities mentioned, and in a simple consise
	domain theory, this is practical and simple.

2. Search the space of modeling assumptions (formulas). For each such chosen
	set of assumptions we use the previous method. One way to realize
	this method is using an ATMS to create all the possible modeling
	assumptions combinations.

There are other additional sub-methods that add constraints over the domain
theory, so that the process of model formation will be more tractable.



Patrick
=======

[Little more than a paraphrase of Forbus!]

The compositional modeling approach of Falkenheimer and Forbus holds that 
a domain theory (which describes entities and interactions) is made up of 
model fragments, and model formation is the process of choosing which 
fragments from the domain theory to instantiate.

The simplest approach is to instantiate all fragments.  This has the 
disadvantage of being very resource-intensive, and is impractical for 
large worlds, and not possible when the system is intended simultaneously 
to represent alternate perspectives of the same fragment.  

Better systems search modelling space to find a necessary set of 
fragments to instantiate.  Falkenheimer and Forbus use an algorithm that 
tried to find all legal combinations of fragments that would produce a 
model that could answer a query.  Unfortunately this becomes expensive as 
the size of the model increases, and generally there may be an 
exponential number of such collections of fragments for a problem.

Nayak has a system whereby the domain theory is divided into 'assumption 
classes' each of which has an ordering on models into causal 
approximations.  This produces locally simple but not necessarily 
globally simple models; however, it does operate in polynomial time.

Model formulation is usually done iteratively, moving from more crude 
generalizations to more specific formulations as the need for precision 
or detail increases; currently many models are assembled 'by hand' though 
the hope is that soon it will become a fully automated process.