TEACH NETSTART Aaron Sloman Oct 1996
An introduction to the use of the Pop-11 database package: how to use it
to create simple networks, and then write procedures that operate on
those networks.
Note: this exercise could more easily be done in Prolog. However it
introduces mechanisms in Pop-11 that are in some ways more flexible.
CONTENTS - (Use <ENTER> g to access required sections)
-- The Pop-11 database package
-- The main procedures provided in the package
-- The example problem
-- Information about weights of objects
-- Computing unknown weights
-- Objective for the program
-- How should the information be stored?
-- Alternative representations
-- -- The compound fact technique.
-- -- The atomic fact technique
-- Using the "atomic fact" technique
-- A list of atomic facts
-- Interrogating the database
-- Checking whether an object is compound or atomic
-- Replacing an undef value using remove and add
-- Using foreach to print out only information about weights
-- Computing the weight of an object from its parts
-- -- A procedure to find the parts
-- -- Adding up the weights of the parts
-- -- Adding up the weights of the parts
-- Further exercises
-- A procedure to build the display from the database-- The Pop-11 database package ----------------------------------------
The Pop-11 database provides a simple mechanism for storing information
in the form of a list of lists. Each list is an item of information.
There are facilities for adding, removing, or searching for stored
items. The items can contain any information whatsoever, but it is
usually convenient to treat each item (a list) as expressing a fact
about some object, or a relationship between two or more objects, in
much the same way as items in a Prolog database do.
Because information items are stored in the form of lists, the Pop-11
pattern matcher can be used to facilitate searching for them, and
retrieving their components. The matcher is described in
HELP * MATCHES, TEACH * MATCHES, TEACH * MATCHARROW-- The main procedures provided in the package ------------------------
The following database facilities which are all summarised in TEACH
POPCORE, and described more fully in other teach files listed below.
add(<item>);
Puts <item> into database
remove(<pattern>);
Removes the first item matching pattern from database. If there
isn't one it triggers a mishap message.
flush(<pattern>);
Removes ALL items matching <pattern> from database, if they
exist
present(<pattern>) -> boole
Searches the database for an item matching pattern. Returns TRUE
or FALSE, and in the first case sets variables in the pattern.
lookup(<pattern>);
Like present, but causes a mishap if the item not found
foreach <pattern> do <actions> endforeach
foreach <pattern> in <list> do <actions> endforeach
Iterates over database, or list
forevery <patternlist> do <actions> endforevery
forevery <patternlist> in <list> do <actions> endforevery
Iterates over combinations of database items. The body is
executed once for every possible way of consistently binding
all the variables in the <patternlist>
it
A variable whose value is set whenever something is found in the
database. The value is the item found.
alladd(<list_of_items>);
Adds all the patterns to database
allremove(<list_of_patterns>);
Applies remove to each pattern in the list. A mishap results if
any of them fails to match any database item.
allpresent(<list_of_patterns>) -> boole
Checks that a combination of patterns can be consistently
instantiated in the database
which(<variables>,<list_of_patterns>) -> <list_of_values>;
Finds items satisfying all the patterns and returns a list of the
values of the corresponding pattern <variables>. forevery is a
generalisation of this.
There are several Pop-11 library packages that are built on top of the
database, including a number of "expert system" shells, of which the
most complex is LIB NEWPSYS (described in HELP NEWPSYS). Simpler shells
are available in LIB PSYS, LIB PRODSYS, LIB EMYCIN, LIB EPROSPECT
and LIB ESHELL. The last three are described in TEACH EXPERTS.
What follows illustrates a subset of the database techniques that are
used in building those systems and others.
WARNING: because the database uses the Pop-11 pattern matcher, and the
matcher does not work on lexically scoped variables or section
variables, all the pattern variables must be declared locally or
globally using "vars". NOT "lvars". (Later we'll show how to use the
pattern prefix "!" to make it unnecessary to declare local pattern
variables using "vars". This extension is available from the Pop-11
library at Birmingham.)
-- The example problem ------------------------------------------------
An example will be given showing how to store information about a
hierarchically structured object, and how to use the information in the
database to make inferences about parts of the object. For simplicity
we'll assume that the information provided is of two kinds.
1. For each object either it is "atomic" or it has parts.
2. Every object has a label, its name.
3. Every object has a weight.
4. Every non-atomic object has a weight that is simply the sum of
the weights of the parts of that object.
Thus if object A has parts B and C and no others, and the weights of the
parts are 2 and 3 (we'll ignore units, such as grams, or ounces, for
now), then the weight of A is 5. In this case, if we know the weights of
any two of the objects we can infer the weights of the third, using the
equation
weight(A) = weight(B) + weight(C)
To illustrate the problem suppose we are dealing with an object called
A, made of parts B, C and D, where B is composed of E and F, C is
atomic, D has parts G and H, E is atomic and F has parts I and J.
The object then has a structre that can be displayed using the
"showtree" library.
;;; first load the library
uses showtree
;;; Then give it a list showing the structure
showtree([ A [B [E] [F [I] [J]]] [C] [D [G] [H]]]);
-- Information about weights of objects -------------------------------
Suppose that in addition to that topological information we were also
given weights of all the atomic components, then we could derive the
weights of all others using simple addition. E.g. suppose the weights
of the atomic components were:
[E 2] [C 3] [I 4] [J 5] [G 6] [H 7]
The information giving known weights could be displayed using showtree,
as follows:
showtree([A [B [E_2] [F [I_4] [J_5]]] [C_3] [D [G_6] [H_7]]]);
(You will now have two VED files showing tree diagrams. You can quit
them as normal by moving the VED cursor into them and using the quit
command.)
In this example we have joined the label and the number using the
underscore character `_` in order to make the diagram produced by
showtree neater. It would be possible to use [E 2] instead
of [E_2], for example, but the diagram would then sprawl out more.
showtree([A [B [E 2] [F [I 4] [J 5]]] [C 3] [D [G 6] [H 7]]]);
-- Computing unknown weights ------------------------------------------
Given the above information about the weights of the atomic components
it would be possible to propagate weights up the tree and assign weights
to all the compount components. E.g. the weight of A would be 27, the
weight of D would be 13.
It is also possible in principle to propagate weights down the tree.
Suppose that the weights of C and H were omitted, but the weights of A
and D were given. I.e. the complete assignment given would then be:
[A 27] [E 2] [D 13] [I 4] [J 5] [G 6]
It would again be possible to work out the weights of everything else.
However, if too much information is provided, it will be redundant, or
possibly even inconsistent, such as the following assignments:
[I 4] [J 5] [F 13]
-- Objective for the program ------------------------------------------
We wish to develop a program that can propagate weights either up or
down the tree, and detect inconsistent assignments.
Given information about
o The structure of a hierarchically structured object
o The weights of a subset of the parts
Then:
o Compute the weight of the whole system and of any parts.
o If it turns out that the information is inconsistent, report that
fact.
-- How should the information be stored? ------------------------------
In almost every problem there are alternative ways of storing the same
information. Some ways support more efficient processing. Some make the
program easier to understand and debug, or easier to extend or interface
with other programs. Some ways make it easier to input information for
the program to operate on, though it is usually not difficult to create
a program that transforms information that is easy to "input" into a
format that is easy to compute.
In this example we shall ignore all issues concerning efficiency of
processing and simply go for a clear and simple representation that
illustrates the capabilities of the database.
-- Alternative representations ----------------------------------------
To illustrate some of the choices, we could either put all the
information about each object into one list to be added to the database
(i.e. one list per object), or we could separate the information into
individual facts and store those facts as separate list items.
Call the first the compound fact technique the second the atomic
fact technique.
Suppose we consider an object composed of the parts A to J, with the
topology specified above, and weights corresponding to the assignment:
[A 27] [E 2] [D 13] [I 4] [J 5] [G 6]
--- ---
Where the non-atomic items are underlined.
-- -- The compound fact technique.
We could collect together all the information known about each object in
turn and create an information molecule. An example would be the
information about A, namely that its label is A, its total weight 27 and
its parts are B, C and D. All that could be stored as one fact added
to the database, i.e.
add([name A weight 27 parts [B C D]]);
For an object whose weight was unknown we can use the word "undef"
instead of a number, as in:
add([name F weight undef parts [I J]]);
This method has the advantage that as soon as you have ANY information
about an object you already have ALL the information about the object
quickly accessible.
A disadvantage is that if you have to change part of the information
about an item you may have to reconstruct the whole thing. Also, in
order to retrieve any item of information you have to build a pattern
that will match the whole compound fact structure.
-- -- The atomic fact technique
This stores a lot of separate information about each object. For example
the information about A might be broken down into
[object A ]
[weight A 27 ]
[parts A [B C D]]
The last could be broken down further into
[part A B]
[part A C]
[part A D]
So that instead of the pattern [part A ?parts] retrieving all the
information about the parts of A in one go, we would need to instantiate
the pattern [part A ?part] three times.
Besides having advantages and disadvantages opposite to those of the
compound fact strategy, the atomic strategy also has the disadvantage
that the list of items in the database will be very long, which could
slow down access because of the time taken to traverse larger list. In
some cases this may be compensated for by the simpler pattern matching
required.
-- Using the "atomic fact" technique ----------------------------------
In what follows we'll use the atomic fact technique, except that the
parts list will not be broken down. The reader may wish to experiment
with an alternative method later.
We'll also start with the simpler problem of propagating weights up the
tree starting from known weights for the "leaf" nodes, i.e. the
simplest components C, E, I, J, G and H.
Let's assume we have the same topology as above, with the weights
assignment:
[C 3] [E 2] [I 4] [J 5] [G 6] [H 7]
We could represent that in a diagram with the following command, using
"?" to represent weights still unknown.
showtree([A_? [B_? [E_2] [F_? [I_4] [J_5]]] [C_3] [D_? [G_6] [H_7]]]);
-- A list of atomic facts ---------------------------------------------
We need a list of atomic facts representing all the above information
about the object A and its tree of parts. Having created such
a list we can assign that list to the variable database, and then
interrogate and update it. Create a procedure called setup_parts
to do that. It takes no inputs, returns no results, but as a side
effect initialises or re-initialises the database. We represent unknown
weights using the word "undef".
define setup_parts();
[
[object A]
[weight A undef]
[parts A [B C D]]
[object B]
[weight B undef]
[parts B [E F]]
[object C]
[weight C 3]
[parts C []]
[object D]
[weight D undef]
[parts D [G H]]
/* ... and so on ... please complete this list... */
[object G]
[weight G 6]
[parts G []]
[object H]
[weight H 7]
[parts H []]
/* ... and so on ... please complete this list... */
] -> database;
enddefine;
/*
You can test that procedure by calling it and then printing out the
database using the pretty-print arrow "==>"
setup_parts();
database ==>
*/
Try that when you have completed the procedure setup_parts.
Note that we have represented atomic objects by giving them an empty
parts list. It would have been possible instead of have assertions like
[atomic C]
[atomic H]
However, it is often much simpler to have a uniform representation for
all objects. Then the fact that something is atomic could be derived, as
shown below.
-- Interrogating the database -----------------------------------------
The following are examples of uses of the database procedures.
Here is how you could find the weight associated with C
vars weight; ;;; declare a pattern variable
present([weight C ?weight]) =>
** <true>
;;; Find the value of the variable weight
weight =>
** 3
Compare finding the weight of A
present([weight A ?weight]) =>
** <true>
weight =>
** undef
Note that a side-effect of using present is that the pattern variable
gets set. We can also use "it" to access the last database item matched,
e.g.:
it =>
** [weight A undef]
Find and print out the weights associated with parts E, F and G.
-- Checking whether an object is compound or atomic -------------------
We can use the database procedure present (pronounced like the adjective
in "John was present", not like the verb in "present arms").
define atomic(object) -> boole;
vars parts; ;;; a pattern variable
if present([parts ^object ?parts]) then
if parts == [] then true else false endif -> boole
else
mishap('No information about parts', [^object])
endif
enddefine;
/*
setup_parts();
;;;Some tests for atomic
atomic("A") =>
atomic("C") =>
atomic("bomb") =>
*/
Try those tests with the database you have created.
NOTE:
The requirement to use "vars" for pattern variables is unfortunate.
If a local "vars" declaration for a particular is omitted, obscure
errors can result, and there are other problems. At Birmingham we
have an autoloadable library which defines a pattern prefix "!" which
can be used immediately to the left of a list expression defining a
pattern containing "?" and "??" variables, which allows those variables
to be declared as "lvars", i.e. lexically scoped within the procedure.
So the above procedure could, instead be defined thus:
define atomic(object) -> boole;
;;; declare pattern variable parts as lvars
lvars parts;
if present( ! [parts ^object ?parts]) then
if parts == [] then true else false endif -> boole
else
mishap('No information about parts', [^object])
endif
enddefine;
This procedure takes an object, represented by its label, and then
searches the database to see if there is information about the object's
parts. If so it checks whether the list of parts is empty.
Compile that and check that the above tests still work.
It would have been possible to define atomic slightly differently, using
the procedure lookup, which is like present, but whereas present returns
a boolean result, lookup returns no result, and when it does not find
a matching item it causes an error:
define atomic(object) -> boole;
lvars parts;
lookup(! [parts ^object ?parts]);
parts == [] -> boole
enddefine;
Try compiling that version and compare its behaviour on the tests.
Yet another version would be
define atomic(object) -> boole;
present([parts ^object []]) -> boole
enddefine;
This one does not give an error if there is no matching item in the
database. Instead it merely returns false.
Also for non-atomic objects this one will be less efficient, because
if given the argument "A" then, having failed to match the pattern
[parts A []]
against
[parts A [B C D]]
it will continue till the end of the database, searching for the
nonexistent pattern. So this version is not recommended.
Exercise:
Define a procedure called weight_of, which uses lookup to find the
weight of an object. Its behaviour should be like this:
weight_of("A") =>
** undef
weight_of("C") =>
** 3
Hint: the pattern given to lookup can contain a pattern variable
(remember to declare it with "vars", not "lvars"). The value assigned to
the variable by lookup can be returned as the result of the procedure.
define weight_of(object) -> w;
... fill in the missing portion ...
enddefine;
-- Replacing an undef value using remove and add ----------------------
The weight associated with F is undef. We can see from the information
provided that it should be 9. So we can remove the old value and add a
new one.
Just to make sure, start by re-initialising the database.
setup_parts();
We can remove whatever information is stored about the weight of F,
using the fact that "=" in a pattern will match any item. (See
HELP * MATCHES).
remove([weight F =]);
That complains if nothing matches the pattern. So you can use the
following if you don't want an error message in such cases:
flush([weight F =]);
Then we can add the new weight
add([weight F 9]);
now print out the contents of the database:
database ==>
Notice that the last thing added is always at the front of the database.
So the order of items can keep changing, and a program should not assume
that they are there in any particular order.
-- Using foreach to print out only information about weights ----------
If you don't want to print out the whole database, but wish to show
all the information about weights, you can do this:
foreach [weight = =] do it => endforeach;
which will print out
** [weight F 9]
** [weight A undef]
** [weight B undef]
** [weight C 3]
etc.
Exercise:
1. Try modifying the foreach command to print out information about all
the objects whose weight is undef. You will need to use a pattern
containing a variable.
2. Try printing out the parts information about all objects
-- Computing the weight of an object from its parts -------------------
So far we have seen how to change the weight of an object "manually"
using remove and add. Now consider how a program could compute the
weight of an object. Let's start with the case where we assume that the
object has parts whose weights are already known.
In order to work out the weight of a compound object, we have to
1. obtain a list of its parts
2. find the weights of the individual parts
3. add up the weights.
Steps 2 and 3 could be combined into a single loop which computes a
running total as it finds the weights.
Before reading on you could try defining a procedure called parts_of
that takes an object label as input and returns a list of the parts.
-- -- A procedure to find the parts
This is almost completely trivial (especially with the use of "!",
which allows the output lvars variable list to be used as a pattern
variable, so that it is set by the matcher.)
define parts_of(object) -> list;
lookup(! [parts ^object ?list])
enddefine;
/*
;;; tests for parts_of
parts_of("A") =>
parts_of("C") =>
parts_of("speech")=>
*/
-- -- Adding up the weights of the parts
In case you had not managed to define the procedure weight_of this is
how it could go
define weight_of(object) -> w;
lookup(![weight ^object ?w]);
enddefine;
-- -- Adding up the weights of the parts
Try completing this procedure by replacing all occurrences of "..."
define add_weights_parts(object) -> total;
lvars parts, weight, item, total = 0;
... -> parts;
for item in parts do
... -> weight;
... -> total
endfor
enddefine;
When you have completed this procedure try it out on the following tests
/*
;;; some tests for add_weights_parts
;;; set up the database
setup_parts();
add_weights_parts("D") =>
add_weights_parts("A") =>
*/
The last example may produce an error, showing that you need to check
whether a part really has a weight.
Here is a possible definition of the procedure
define add_weights_parts(object) -> total;
lvars parts, weight, item, total = 0;
parts_of(object) -> parts;
for item in parts do
weight_of(item) -> weight;
if isnumber(weight) then
weight + total -> total
else
mishap('Object has no weight', [^item ^weight])
endif;
endfor
enddefine;
-- Further exercises --------------------------------------------------
Define a procedure update weight, which takes an object, and if it has
an undef weight, computes its weight, then removes the undef weight
information and adds the computed weight.
Define a procedure that updates the weights of all undef objects as far
as it can using the known weights of objects.
Generalise that procedure so that it can compute the weight of an object
from the weight of its parent and the weights of its siblings.
Write a procedure that propagates all known weights up and down the
network checking for consistency as it goes.
... to be continued ....
-- A procedure to build the display from the database -----------------
Define a procedure that takes the weight information in the network and
builds up a list to give to showtree
It could work something like this, assuming you give it a start node.
First a utility procedure
define new_label(object) -> label;
;;; given an object create a string consisting of the object
;;; an underscore and the weight or `?`
lvars weight;
weight_of(object) -> weight;
if isnumber(weight) then object >< '_' >< weight
else object >< '_?'
endif -> label;
enddefine;
/*
;;; test cases
new_label("A") =>
new_label("C") =>
*/
define build_display_tree(object) -> tree;
lvars parts, part, label;
parts_of(object) -> parts;
new_label(object) -> label;
if parts == [] then
[^label] -> tree
else
;;; get trees for all the parts and combine them
[%
label,
for part in parts do build_display_tree(part) endfor
%] -> tree
endif;
enddefine;
/*
;;; Test for build_display_tree
setup_parts();
build_display_tree("A") ==>
showtree( build_display_tree("A") );
*/
... to be continued ... suggestions welcome ....
--- $poplocal/local/teach/netstart
--- Copyright University of Birmingham 1996. All rights reserved. ------