วันเสาร์ที่ 5 กุมภาพันธ์ พ.ศ. 2554

JOSHUA and Rule-based Systems Exercises

JOSHUA and Rule-based Systems Exercises
I. Introduction
This is an exercise designed to do two things: it will allow you to
explore the online behavior of a rule-based system in many ways and it
will get you familiar with Joshua, a tool that many people find useful
for building their term project.
The Knowledge Base (The Investment Rules Again)
Following on with the paper exercises you did, in this exercise we'll
use the same rule set to decide among six of the most common
categories of mutual funds. The system assumes that you have $2000 to
invest and can help select among the following possibilities:

• a money-market fund
• an income fund (e.g., bonds)
• an aggressive growth fund
• a mixed growth and income fund (abbreviated "G&I")
• a conservative growth fund
• a tax-free fund
• none (i.e., don't invest)

For ease of reference, the complete set of rules in English is found
at the end of this handout. As before, we have used some formatting
conventions to help make their structure clear. Consider rule 12, for
instance:

12] if Investment Goal = RETIREMENT and
Number Of Years To Retirement < 10
then Category Of Fund = CONSERVATIVE GROWTH .8

Each rule is expressed in terms of an if part (the premise) and a then
part (the conclusion). In rule 12 there are two clauses in the premise
and (as in all of our rules) one in the conclusion.

Each clause in a rule is expressed in terms of an attribute, object,
and its value. As a formatting convention, attributes are written as
phrases with their first letters capitalized (e.g., Investment Goal,
Number Of Years To Retirement, Category Of Fund); values are written
in all capitals (RETIREMENT, 10, CONSERVATIVE GROWTH). The first
clause thus asks whether the attribute Invest Goal has the value
RETIREMENT, or, in smoother English, "the goal for this investment is
to fund your retirement." For ease of reading the object is often
left implicit, e.g., in this case investment goal of user is
retirement.

Putting the whole rule in somewhat better English, it says:
if the goal for this investment is to fund your retirement, and
the number of years until you retire is less than 10,
then the category of fund to select is the conservative growth funds.

In Joshua the rule looks somewhat different; we'll come to that below.
Note in particular that the rule numbers in the handout at the end are
for convenience. Joshua names rules rather than numbers them.

II. Getting Started
You will be using the Allegro Common Lisp interpreter on Athena and
the Joshua knowledge base found on the course web page. We'll start by
familiarizing you with Allegro Common Lisp on Athena and Joshua.
(While it is possible to install all this on a Windows PC, we strongly
recommend against doing that. You can work from a Windows PC by
ssh'ing to athena-x.dialup.mit.edu (via SecureCRT, make sure you
configure the connection to Forward X11 packets,), while running
XWin-32. Both SecureCRT and XWin-32 are available for installation
from http://web.mit.edu/software/win.html)
1. Log onto an Athena machine (athena-x.dialup.mit.edu works if you're
not in an Athena cluster).

2. athena% add acl_v6.2-alisp 6.871
This will attach the Allegro Common Lisp locker for the version we
will be using, and the course locker.

3. Download from the course web page the knowledge base file
invest-josh-kb.custom.lisp.
Put this in your local directory. This will make you a local copy of
the example knowledge base.

4. athena% chmod 700 ~/invest-josh-kb.custom.lisp
This will just make sure that the file is readable.

5. athena% joshua8 &
Depending on server load, this may take awhile. An XEmacs will start
and it will start up a lisp inferior with all the Joshua code in it.
Eventually, you'll see a CL-USER(1): prompt in the XEmacs window (the
one with the *common-lisp* label).

6. CL-USER(1): (clim-env:start-clim-environment)
A small window called Navigator will pop up.
7. In the Navigator window, select Lisp Listener from the Tools menu.
A Lisp Listener window will be raised, and you will see a ⇒ prompt.
(Yes, windows all over the place.)

8. ⇒:joshua syntax yes
This command is necessary to enable the square bracket predication
syntax. If you ever in the future forget to do this before compiling
your project code, you will get an error message concerning a comma
not being inside a backquote.

9. ⇒:edit file ~/invest-josh-kb.custom.lisp
This will open the code in a buffer in your XEmacs window.

10. Select buffer from the Compile other submenu of the ACLFile menu in XEmacs

11. Watch the status bar at the bottom of XEmacs for the message
Compiling... done.. At this point, return to your Lisp Listener
window.

12. Now you can try asking what category of fund someone should invest
in. Just type the following command:
⇒ (ask [category-of-fund ben-bitdiddle ?x] #'print-answer-with-certainty)
You are of course free to inquire about people other than Ben
Bitdiddle, our canonical test subject.
See notes at the end of the handout for how to handle errors and the debugger.

III. Using Joshua: Predicates and Predications
Every fact in Joshua's database is called a predication. A predication
a list enclosed by square brackets. For example:
[FATHER-OF JOHN MARY]

might mean that JOHN is the father of MARY. We define predicates (what
we have called "attributes" in class) using the define-predicate
macro. To define a simple predicate, all we have to do is this (as
you'll see below, the prompt character for Joshua is a right-arrow):

⇒ (define-predicate father-of (father child))

The first argument to the macro is the name of the predicate, and the
second is an argument list. There is an optional third argument to the
macro, which is a list of types for the predicate to inherit from.
This is an advanced feature you don't have to know about right now,
but if you are interested, you can see by examining the code that
accompanies this problem set how predicates that have certainty
factors are defined, inheriting from a base class that provides
certainty factor support.
To undefine a predicate, simply execute this command:
⇒ (undefine-predicate 'father-of)


IV. Using Joshua: TELL-ing things
The first and most simple thing you can do with Joshua is to tell it
facts. Take, for example the following code:
⇒(tell [HAS-HEALTH-INSURANCE BEN-BITDIDDLE YES])

We can also tell things that are justified by certainty factors, like so:
⇒(tell [HAS-LIFE-INSURANCE BEN-BITDIDDLE YES] :justification
'((user-input 0.8)))

Note that we can replace the 0.8 with any certainty factor we choose,
and that the symbol USER-INPUT is just a notation to let us to know
where the justification comes from; you can write anything there.
UNTELL-ing things is also possible, for example:
⇒ (untell [HAS-LIFE-INSURANCE BEN-BITDIDDLE YES])

(Some people have reported that UNTELL can get stuck in an infinite
loop; we're trying to track down that bug.)


V. Using Joshua: Seeing what it knows
⇒:show joshua database
True things
[HAS-LIFE-INSURANCE BEN-BITDIDDLE YES]
[HAS-HEALTH-INSURANCE BEN-BITDIDDLE YES]
False things

"None"
So we see that Joshua knows three facts right now. In the Lisp
Listener, you can middle click on any one of them to get an
explanation, along the lines of the HOW command in MYCIN, of how
Joshua inferred that fact. You can also access this explanation by
issuing the following command:
⇒ :explain predication [HAS-HEALTH-INSURANCE BEN-BITDIDDLE YES]
You'll get output that looks like this:
[HAS-HEALTH-INSURANCE BEN-BITDIDDLE YES] is true It is a PREMISE

This is a rather simple explanation, because we TELL-ed (told) this
fact to Joshua at top level in the Lisp Listener. Explanations of the
results of the investment advisor code will be more interesting.

VI. Using Joshua: ASK-ing things
The most simple form of ASK is illustrated below:
⇒ (ask [HAS-HEALTH-INSURANCE ?x ?y] #'print-query)

This command simply runs through the database and executes the
function print-query on every predication it finds that matches the
pattern. Note that ?x and ?y are logic vari¬ables that match anything
and that are not necessarily equal. The output of the command in this
example is:
[HAS-HEALTH-INSURANCE BEN-BITDIDDLE YES]

If I were to have told Joshua additionally that ALYSSA-P-HACKER
doesn't have health insurance, we'd have seen the following output:
[HAS-HEALTH-INSURANCE BEN-BITDIDDLE YES]
[HAS-HEALTH-INSURANCE ALYSSA-P-HACKER NO]

Interestingly enough, we can have ASK call any function that we want
on database pred¬ications that match the pattern. What if we were to
issue the following command:
⇒ (ask [HAS-HEALTH-INSURANCE ?who ?value]
#'(lambda (backward-support)
(if (eq ?value 'yes) (format t " ~A has health insurance." ?who)
(format t " ~A does not have health insurance." ?who))))

We get the following response from the system:
ALYSSA-P-HACKER does not have health insurance.
BEN-BITDIDDLE has health insurance.
One more fun thing to do is to try this:
⇒ (ask [HAS-HEALTH-INSURANCE ?x ?y]#'print-answer-with-certainty)

Now we can see the certainty factors:
[HAS-HEALTH-INSURANCE ALYSSA-P-HACKER NO] 1
[HAS-HEALTH-INSURANCE BEN-BITDIDDLE YES] 0.8


VII. Using Joshua: Defining rules
Look at the following rule definition from the example code:
(defrule full-insurance-coverage (:backward :certainty 1.0 :importance 97)
if [and [HAS-LIFE-INSURANCE ? who YES]
[HAS-HEALTH-INSURANCE ? who YES]]
then [ADEQUACY-OF-INSURANCE-COVERAGE ?who ADEQUATE])
defrule is a defining form that makes rules. Its first argument is the
name of the rule and its second is a list of keywords. Possible
keywords include :backward, for backward chaining rules, and :forward
for forward chaining rules. You can't use both at the same time. The
:certainty keyword specifies that the next element of the list is the
rule's certainty factor. The :importance keyword specifies that the
next element of the list is the rule's importance, which is used to
artificially control which rules are tried first. A higher importance
value means that the rule is tried before rules that have lower
importance values. In general you can ignore the importance keyword
and number; it's simply evidence that Joshua has more mechanism than
needed for this problem set.
The remainder of the form is the body of the rule. if and then are
fixed tokens that precede the if and then rule clauses, respectively.
Logic variables are bound for the duration of the rule, so ?who in the
if clause must be the same as ?who in the then clause.
This is a backward chaining rule and so it triggers when we ASK things
of Joshua. If we were to:
⇒ (ask [ADEQUACY-OF-INSURANCE-COVERAGE BEN-BITDIDDLE ADEQUATE
#'print-answer-with-certainty)

Since we know [HAS-LIFE-INSURANCE BEN-BITDIDDLE YES] and
[HAS-HEALTH-INSURANCE BEN-BITDIDDLE YES], we can conclude the
following:
[ADEQUACY-OF-INSURANCE-COVERAGE BEN-BITDIDDLE ADEQUATE] 0.8

Note that there would be no output if we could not conclude the fact
we are asking for from what is in the database. Why is the certainty
factor 0.8? Let's see what Joshua knows:
⇒:show joshua database

Joshua now knows 3 facts:
True things
[ADEQUACY-OF-INSURANCE-COVERAGE BEN-BITDIDDLE ADEQUATE]
[HAS-LIFE-INSURANCE BEN-BITDIDDLE YES]
[HAS-HEALTH-INSURANCE BEN-BITDIDDLE YES]

False things
"None"
Let's have Joshua explain how it concluded that Ben's coverage was adequate:
⇒ :explain predication [ADEQUACY-OF-INSURANCE-COVERAGE BEN-BITDIDDLE ADEQUATE]

Recall that middle clicking on [ADEQUACY-OF-INSURANCE-COVERAGE
BEN-BITDIDDLE ADEQUATE]
in the Lisp Listener will yield the same output:

[ADEQUACY-OF-INSURANCE-COVERAGE BEN-BITDIDDLE ADEQUATE] is true
It was derived from rule FULL-INSURANCE-COVERAGE
[HAS-HEALTH-INSURANCE BEN-BITDIDDLE YES] is true
It is an USER-INPUT
[HAS-LIFE-INSURANCE BEN-BITDIDDLE YES] is true
It is a PREMISE

The certainty factor of 0.8 arises because 0.8 was the minimum
certainty factor in the AND clause in the rule's premise. The
certainty factor of the rule itself was 1.0, so the conclusion's
certainty is 0.8.
VIII. Seeing what Joshua is doing
You can enable tracing in Joshua by doing the following command:
⇒ :enable joshua tracing all

Watch what happens when we ask the same question as before. Assume we
have UNTELL-ed the conclusion; if we hadn't, the rule would not have
been triggered at all.
⇒ (ask [ADEQUACY-OF-INSURANCE-COVERAGE BEN-BITDIDDLE ADEQUATE]
'print-answer-with-certainty)
> Asking predication [ADEQUACY-OF-INSURANCE-COVERAGE BEN-BITDIDDLE ADEQUATE]
> Trying backward rule HEALTH-INSURANCE-COVERAGE (Goal... )
[ADEQUACY-OF-INSURANCE-COVERAGE BEN-BITDIDDLE VALUE]
> Asking predication [HAS-HEALTH-INSURANCE BEN-BITDIDDLE NO]
> Exiting backward rule HEALTH-INSURANCE-COVERAGE
> Trying backward rule LIFE-INSURANCE-COVERAGE (Goal... )
[ADEQUACY-OF-INSURANCE-COVERAGE BEN-BITDIDDLE VALUE]
> Asking predication [HAS-LIFE-INSURANCE BEN-BITDIDDLE NO]
> Exiting backward rule LIFE-INSURANCE-COVERAGE
> Trying backward rule FULL-INSURANCE-COVERAGE (Goal... )
[ADEQUACY-OF-INSURANCE-COVERAGE BEN-BITDIDDLE VALUE]
> Asking predication [HAS-LIFE-INSURANCE BEN-BITDIDDLE YES]
> Succeed in Asking Predication [HAS-LIFE-INSURANCE BEN-BITDIDDLE YES]
> Asking predication [HAS-HEALTH-INSURANCE BENDITDIDDLE YES]
> Succeed in Asking Predication [HAS-HEALTH-INSURANCE BEN-BITDIDDLE YES]
> Succeeding backward rule FULL-INSURANCE-COVERAGE
> Justifying: [ADEQUACY-OF-INSURANCE-COVERAGE BEN-BITDIDDLE
ADEQUATE]
<--Rule: FULL-INSURANCE-COVERAGE
> Looking for more backward rule matches FULL-INSURANCE-COVERAGE
(Goal... )[ADEQUACY-OF-INSURANCE-COVERAGE BEN-BITDIDDLE ADEQUATE]
> Exiting backward rule FULL-INSURANCE-COVERAGE
> Succeed in Asking Predication
[ADEQUACY-OF-INSURANCE-COVERAGE BEN-BITDIDDLE ADEQUATE]

[ADEQUACY-OF-INSURANCE-COVERAGE BEN-BITDIDDLE ADEQUATE] 1.0

To turn off this feature, use:
⇒ :disable joshua tracing all

IX. Things to note while running the example code
In response to any question, you are allowed to type the following
characters. Typing Control+Shift+R prints what rule is running. Typing
Control+Shift+W is like asking WHY in MYCIN; it explains what the
system is trying to accomplish by asking the current question and
running the current rule. Typing Control+Shift+H prints a help message
that reminds you of what these keys do.
Each of these key combinations will also print out a message
containing the legal answers (or a description like "a number"). Any
possible answer it prints out is mouse sensitive, so try just clicking
on the answer you want. The question prompt also provides completions,
so try just typing enough characters for your response so be
unambiguous, and then hitting the space bar.
Try executing the following command to see a graph of rule calling
relationships:
⇒ :graph rules category-of-fund
If you want to write this graph to a file, try the following:
⇒ :graph rules category-of-fund :to file foo.ps

X. Using Joshua: Further Reading
For more information about Joshua, see the Joshua Users Guide and the
Joshua Reference Manual, both of which are posted on the course web
page.
XI. Exercise 0: Make sure you can run Joshua
The first part of the assignment is to make sure you can run Joshua
using the instructions we have given you. Do it today! See the course
staff immediately if there is any problem whatsoever; we will do our
best to assist you. Please do not wait to try Joshua on Athena. As the
due date for this assignment draws near, our ability to help you will
be lessened.
XII. Exercise 1: Run the following examples using the knowledge base
you loaded above.
Try the following example. The user, CLYDE:
is 42 years old.
has health and life insurance.
has a current savings balance of $20,000.
earns a monthly salary of $3,000.
is not covered by a pension plan, but does have an IRA.
has one child, age 12, who does not have a scholarship or a trust fund,
is not eligible for school loans, and would like to attend a school with
expensive tuition.
does not currently own a house, but would like to.
Recall that you begin the consultation by executing the following
command at the top level of the Lisp Listener:
⇒ (ask [CATEGORY-OF-FUND CLYDE ?X] #'print-answer-with-certainty)
Prepare a transcript of the dialog, and list the answer(s). For each
answer, use Joshua's Explain Predication feature to find out HOW the
answer was derived. Save this transcript and turn it in. The easiest
way to do this is with the command :Copy Output History <filename>
which will copy everything that has appeared in the buffer so far to
<filename>. You need only do this once, at the end of the problem set,
then edit the file so it contains only the material you are to turn
in. If you want to be cautious, however, do it periodically with
different file names so you can be sure not to lose any work.

Also try the following example. The user, DUDLEY:
is 70 years old.
does not have health insurance.
does have life insurance.
has a current savings balance of $20,000.
earns a monthly salary of $3,000.
is covered by a pension plan.
has no children.
currently owns a home.

For DUDLEY as well, prepare a transcript of the dialog, and list the
answer(s). For each answer, use Joshua's Explain Predication feature
to find out HOW the answer was derived. Print these things out and turn
them in.

XIII. Exercise 2: Practice in Knowledge Engineering
Try the following example. The user, ETHYL:
has health and life insurance.
has a current savings balance of $20,000.
earns a monthly salary of $3,000.
is covered by a pension plan.
has one child, age 23.
is age 68.
owns a home.
If you examine the dialog carefully, you'll see that the system asks
about College Tuition. But with the only (and hence youngest) child
aged 23, rule 46 would indicate that there are no children headed for
college. So why does it ask about tuition?
See if you can determine why. Use Joshua's tracing mechanism to help
you determine how the system is reasoning at that point. Try drawing a
diagram that shows the tree structure produced by the backward
chaining; this may help you see the logic being used and see the
problem.
Then see if you can fix the problem. One good approach is to modify the
rule that causes the problem. Another is to try introducing a new
rule. Specify a solution along both routes. Comment on both solutions.
Is one better than the another, in the sense of following the "spirit"
of knowledge engineering and rule-writing?
You may want to try implementing your solutions by augmenting the
program's knowl¬edge base. You can test whether they work and test
their sensitivity and robustness to various inputs. Turn in your
explanation and answers to the questions, and your solution to the
problem we are seeing. If you drew a diagram or wrote some Joshua
code, show that as well.
XV. Exercise 3: Looking at Rules
Take a look at the rule goal-invest-spare-cash. What strikes you about
it? How does the rule compare to the other rules in the knowledge
base? Why is this rule a good or bad example of knowledge engineering?
Support your answer with information from the lectures and the
readings. What is the rule trying to conclude? Can you think of a
better way to do it? Turn in your answers to the questions. Please be
concise.

What To When Something Breaks
For example, suppose you find the system responding to you like this:


When you find the Lisp listener window reacting like this, use your
mouse to select the first ABORT (the one that says Return to Lisp
Listener). This will put you back to the top level of the listener and
you can start again. Keep in mind that Joshua keeps its database, so
that questions about an individual answered in the run interrupted
above will still be there. As a result the system does not re-ask
those questions; it continues from whatever the next question is.

Some times you get thrown back into the Xernacs window, with a list of
choices that looks something like:


When this happens you reply using :continue (that is, colon-continue)
and one of the numeric choices. Usually the correct choice is the one
that says Restart CLIM Lisp listener. In the example above, it's #8 so
you would type :continue 8. Then you can go back to the Lisp listener
window and continue working.


THE KNOWLEDGE BASE


RULES ABOUT: adequacy of Basic Insurance Coverage

1] if Have Health Insurance = NO
then Basic Insurance Coverage = INADEQUATE 1.0

2] if Have Life Insurance = NO and
Should Have Life Insurance = YES
then Basic Insurance Coverage = INADEQUATE 1.0

3] if Have Health Insurance = YES and
Have Life Insurance = YES
then Basic Insurance Coverage = ADEQUATE 1.0


RULES ABOUT: whether you Should Have Life Insurance

4] if Married = YES or
Have Children = YES
then Should Have Life Insurance = YES 1.0


RULES ABOUT: which Category Of Fund to choose

10] if Basic Insurance Coverage = INADEQUATE
then Category Of Fund = NONE 1.0

11] if Current Savings < 6 * Monthly Salary
then Category Of Fund = MONEY MARKET 1.0

12] if Investment Goal = RETIREMENT and
Number Of Years To Retirement < 10
then Category Of Fund = CONSERVATIVE GROWTH .8

13] if Investment Goal = RETIREMENT and
Number Of Years To Retirement > 10 and
Number Of Years To Retirement < 20
then Category Of Fund = G&I .8

14] if Investment Goal = RETIREMENT and
Number Of Years To Retirement > 20
then Category Of Fund = AGGRESSIVE .8

15] if Investment Goal = CHILDREN'S EDUCATION and
Age Of Oldest Child < 7
then Category Of Fund = G&I .8

16] if Investment Goal = CHILDREN'S EDUCATION and
Age Of Oldest Child > 7
then Category Of Fund = CONSERVATIVE GROWTH .8

17] if Investment Goal = HOME OWNERSHIP
then Category Of Fund = G&I .9

18] if Investment Goal = CURRENT INCOME
then Category Of Fund = INCOME .9

19] if Investment Goal = INVEST SPARE CASH and
Risk Tolerance = LOW
then Category Of Fund = CONSERVATIVE GROWTH .9

20] if Investment Goal = INVEST SPARE CASH and
Risk Tolerance = MEDIUM
then Category Of Fund = G&I .8

21] if Investment Goal = INVEST SPARE CASH and
Risk Tolerance = HIGH
then Category Of Fund = AGGRESSIVE .8

22] if Investment Goal = INVEST SPARE CASH and
Risk Tolerance = MEDIUM and
Tax Bracket = HIGH
then Category Of Fund = TAX-FREE .9


RULES ABOUT: what your Life Stage is

23] if Your Age > 65
then Life Stage = RETIRED .8

24] if Your Age <= 65
then Life Stage = NOT-RETIRED .8


RULES ABOUT: what Investment Goal to select

31] if Pension = NO and
Individual Retirement Account = NO
then Investment Goal = RETIREMENT 1.0

32] if Have Children = YES and
Children Headed For College = YES and
Children's Education Already Funded = NO
then Investment Goal = CHILDREN'S EDUCATION .8

33] if Own Home = NO and
Want Home = YES
then Investment Goal = HOME OWNERSHIP .8

34] if Life Stage = RETIRED
then Investment Goal = CURRENT INCOME .9

35] if Have Pension = YES
then Has Retirement Vehicle = YES 1.0

36] if Has IRA = YES
then Has Retirement Vehicle = YES 1.0

37] if Own Home = YES or Want Home = NO, and
Pension = YES or Individual Retirement Account = YES, and
Have Children = NO or Children's Education Already Funded
= YES, and
Life Stage = NOT-RETIRED
then Investment Goal = INVEST SPARE CASH .8


RULES ABOUT: what your Risk Tolerance is

41] if Enjoy Gambling = YES
then Risk Tolerance = HIGH .8

42] if Budgeting Very Important = YES
then Risk Tolerance = LOW .8

43] if Worry About Money At Night = YES
then Risk Tolerance = LOW .8

44] if Budget But Splurge Sometimes = YES
then Risk Tolerance = MEDIUM .8


RULES ABOUT: whether you have Children Headed For College

45] if Have Children = YES and
Age Of Youngest Child < 16
then Children Headed For College = YES 1.0

46] if Have Children = YES and
Age Of Youngest Child >= 16
then Children Headed For College = NO 1.0

47] if Have Children = NO
then Children Headed For College = NO. 1.0


RULES ABOUT: whether Children's Education Already Funded


51] if Have Children = YES
College Tuition Level = CHEAP
then Children's Education Already Funded = YES 1.0

52] if Have Children = YES
Children Have Scholarship = YES
then Children's Education Already Funded = YES 1.0

53] if Have Children = YES
Children Eligible For Loans = YES
then Children's Education Already Funded = YES 1.0

54] if Have Children = YES
Children Have Trust Fund = YES
then Children's Education Already Funded = YES 1.0

55] if Have Children = YES
Children Have Scholarship = NO and
Children Eligible For Loans = NO and
Children Have Trust Fund = NO
then Children's Education Already Funded = NO. 1.0

--
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