ASSIGNMENT 1  DUE Thursday February 21st
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1. Write a predicate, palindrome, which returns true if a given
list is a palindrome.

?-palindrome([a,b,c,b,a]).
  true
?-palindrome([a,b,c]).
  false


2. Write a predicate, exists, which when given a list L,
   a variable X, and an integer n, binds X  to the nth
   element of the list or to -1 if such an element does not exist.

   For example:

   ?-exists( [a,b,n,c,e], X, 4).

   X=c;
   no

   ?-exists( [a, b, c], A, 5).

   A=-1;
   no


3. Write the predicate, intersection, which computes the set 
theoretic intersection of two lists without duplicates. For example,

   ?-intersection( [a, b, c, a, d], [c, a,c, g], Y).

   returns the list Y=[a,c];
                 no


4.  Write a Prolog procedure to check if a list is in ascending or
    descending order.

    ?ordered([3,4,7]).
     yes

    ?ordered([6,4,2]).
     yes

    ?ordered([2,6,4,9]).
     no


5. Write a Prolog predicate, merge, to merge two sorted lists,
   which are both either ascending or descending.
   (the resulting list is also sorted in the same manner)

   ?merge([2,5,7],[4,5,6,8],M).

    M=[2,4,5,5,6,7,8];

    no


6. 
   This problem is a scheduling problem. The task is to match job applicants
   to a specific job. The requirements for the job are:

   At least three years' experience.
   A Bachelor's and a Master's degree.
   An average of two years per previous position overall to prove stability.
   Willingness to work overtime or to travel. Both are not necessary.
   Very good  or excellent health.

   Use the following data set of applicants as a test bed:

   (a) Name: Jones
       Previous jobs, years on job:
                                CAT --- 5 years
                                IBM --- 4 years
                                CILCO--- 1 year
                                AIONICS---1 year
       Degrees: BS and MS
       Overtime= no, Travel =yes, Health=excellent


   (b) Name: smith
       Previous jobs, years on job:
                             BORDOM ---8 years
       Degrees: BS
       Overtime: yes, Travel: yes, Health: good

   (c) Name: smart_allec
       Previous jobs, years on job:
                                DELCO---1year
                                MOTOROLLA---1 year
                                LOGICON---1 year
       Degrees: BS, MS, PHD
       Overtime: no, Travel: no, Health: very good


7. Implement in Prolog the query answering system given in the book about 
investing based on investor's risk classification, but make the knowledge 
base more complex and instead of having numerous ask 
predicates-one per each independent variable- use a generalized 
ask-predicate to avoid duplication of questions issued to the user.
(decision tree and example is on page 289)

END OF ASSIGNMENT 1
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 ASSIGNMENT 2 

PART 1:
Use a  neural network off the selve package, to build a Multilayered,
feedforward, back propagation neural net for the data set given below.
Inputs are speed and distance and output the amount of turn.
Experimentation will determine the best architecture for the net.
Provide hard copy listing: the architecture, activation functions and learning
algorithm that you used, the weight set after training, the training and
testing data sets that were used, and the training and testing errors of
your best network  model.

PART 2:

You are to use the JFS Fuzzy Logic System to implement a fuzzy controler
which determines the amount of left
or right turn of the automobile driving wheel (in degrees),
in order for the automobile to follow a contour.
The input fuzzy variables are speed of the automobile and
the difference between the distances to the contour between the front
of the automobile and the rear.
Use experimentation to design the most appropriate fuzzy sets and membership functions,
and test accuracy of your system at the end by using the same error function that you used 
in PART 1.


PART 3:  Compare the NN model that you built with the fuzzy model. Which is more accurate? Can you
explain why?


Data set for both parts:
A run by a human driver yielded these sensor measurements:

speed       distance       turn
10             +5           15
50             +5           30
10             +20          40
50             +20          60
15             -5           -15
50             -5           -30
15             -20          -43
50             -20          -65
70		+5	    20
70		+20	    39
70	       -5	    -24
70	       -20	    -55

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