The Appearance of Multiparadigm Programming Languages in the Teaching of Artificial Intelligence

183 Pages·2013·1.42 MB·English

by  Pánovics János

DE TTK
1949
The Appearance of Multiparadigm
Programming Languages
in the Teaching of Arti(cid:28)cial Intelligence
Egyetemi doktori (Ph.D.) ØrtekezØs
PÆnovics JÆnos
Dr. Fazekas GÆbor
TØmavezetfi:
Debreceni Egyetem
TermØszettudomÆnyi Doktori TanÆcs
Matematika- Øs SzÆm(cid:237)tÆstudomÆnyok Doktori Iskola
Debrecen, 2013

DE TTK
1949
The Appearance of Multiparadigm
Programming Languages
in the Teaching of Arti(cid:28)cial Intelligence
Egyetemi doktori (Ph.D.) ØrtekezØs
PÆnovics JÆnos
Dr. Fazekas GÆbor
TØmavezetfi:
Debreceni Egyetem
TermØszettudomÆnyi Doktori TanÆcs
Matematika- Øs SzÆm(cid:237)tÆstudomÆnyok Doktori Iskola
Debrecen, 2013
Ezen ØrtekezØst a Debreceni Egyetem TermØszettudomÆnyi Dokto-
ri TanÆcs Matematika- Øs SzÆm(cid:237)tÆstudomÆnyok Doktori Iskola Szak-
m(cid:243)dszertan programja keretØben kØsz(cid:237)tettem a Debreceni Egyetem
termØszettudomÆnyi doktori (Ph.D.) fokozatÆnak elnyerØse cØljÆb(cid:243)l.
Debrecen, 2013. Æprilis 23.
PÆnovics JÆnos
doktorjel(cid:246)lt
Tanœs(cid:237)tom,hogyPÆnovicsJÆnosdoktorjel(cid:246)lt1999(cid:21)2002k(cid:246)z(cid:246)ttafent
megnevezett Doktori Iskola Informatika programjÆnak keretØben irÆ-
ny(cid:237)tÆsommal vØgezte munkÆjÆt. Az ØrtekezØsben foglalt eredmØnyek-
hezajel(cid:246)lt(cid:246)nÆll(cid:243)alkot(cid:243)tevØkenysØgØvelmeghatÆroz(cid:243)anhozzÆjÆrult.
Az ØrtekezØs elfogadÆsÆt javasolom.
Debrecen, 2013. Æprilis 23.
Dr. Fazekas GÆbor
tØmavezetfi
The Appearance of Multiparadigm
Programming Languages
in the Teaching of Arti(cid:28)cial Intelligence
(cid:201)rtekezØs a doktori (Ph.D.) fokozat megszerzØse ØrdekØben
a matematika- Øs szÆm(cid:237)tÆstudomÆnyok tudomÆnyÆgban
˝rta: PÆnovics JÆnos okleveles programtervezfi matematikus
KØsz(cid:252)lt a Debreceni Egyetem
Matematika- Øs SzÆm(cid:237)tÆstudomÆnyok Doktori IskolÆja
(Szakm(cid:243)dszertan programja) keretØben
TØmavezetfi: Dr. Fazekas GÆbor
A doktori szigorlati bizottsÆg:
eln(cid:246)k: Dr. PÆles Zsolt ......................
tagok: Dr. Fekete IstvÆn ......................
Dr. VÆrterØsz Magda ......................
A doktori szigorlat idfipontja: 2012. mÆrcius 9.
Az ØrtekezØs b(cid:237)rÆl(cid:243)i:
Dr. .................. ......................
Dr. .................. ......................
Dr. .................. ......................
A b(cid:237)rÆl(cid:243)bizottsÆg:
eln(cid:246)k: Dr. .................. ......................
tagok: Dr. .................. ......................
Dr. .................. ......................
Dr. .................. ......................
Dr. .................. ......................
Az ØrtekezØs vØdØsØnek idfipontja: 2014. ................ ... .

Contents
Acknowledgments 1
1 Introduction 2
2 Overview of Functional Programming 5
2.1 The Lambda Calculus . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
2.2 Functional Approach in Teaching Arti(cid:28)cial Intelligence . . . . . . . . . . 9
2.2.1 Search Algorithms in Di(cid:27)erent Programming Languages . . . . . 13
2.3 Multiparadigm Languages and F# . . . . . . . . . . . . . . . . . . . . . 14
3 Some Implementations of Search Algorithms for Single-Agent Prob-
lems 16
3.1 A Class Hierarchy for Search Algorithms . . . . . . . . . . . . . . . . . . 17
3.2 Various Implementations of Search Algorithms . . . . . . . . . . . . . . 20
3.2.1 The C# Implementation . . . . . . . . . . . . . . . . . . . . . . . 20
3.2.2 The First F# Implementation. . . . . . . . . . . . . . . . . . . . 32
3.2.3 The Second F# Implementation . . . . . . . . . . . . . . . . . . 41
3.2.4 The Third F# Implementation . . . . . . . . . . . . . . . . . . . 46
3.2.5 Comparing the Four Implementations . . . . . . . . . . . . . . . 55
3.3 Implementing Speci(cid:28)c Problems. . . . . . . . . . . . . . . . . . . . . . . 58
3.3.1 Towers of Hanoi . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
3.3.2 Funfair Puzzle . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68
4 Some Implementations of Search Algorithms on Game Trees 94
4.1 A Class Hierarchy for Search Algorithms . . . . . . . . . . . . . . . . . . 95
4.2 Various Implementations of Search Algorithms . . . . . . . . . . . . . . 98
4.2.1 The C# Implementation . . . . . . . . . . . . . . . . . . . . . . . 98
4.2.2 The First F# Implementation. . . . . . . . . . . . . . . . . . . . 106
4.2.3 The Second F# Implementation . . . . . . . . . . . . . . . . . . 112
4.2.4 Comparing the Three Implementations. . . . . . . . . . . . . . . 118
4.3 Implementing Speci(cid:28)c Problems. . . . . . . . . . . . . . . . . . . . . . . 119
5 A New Methodology for Teaching Computer Science 130
5.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130
5.2 Current Program Requirements . . . . . . . . . . . . . . . . . . . . . . . 132
5.3 Some Possible Projects . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134
5.3.1 Project #1: Creating a Reversi Application . . . . . . . . . . . . 134
5.3.2 Project #2: Creating a Library Information System . . . . . . . 140
5.3.3 Further Subjects and Projects. . . . . . . . . . . . . . . . . . . . 141
5.4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142
6 Supporting Programming Contests with the ProgCont Application 143
6.1 About Programming Contests . . . . . . . . . . . . . . . . . . . . . . . . 144
6.2 The Architecture and Operation of ProgCont . . . . . . . . . . . . . . . 146
6.3 OurExperiencewiththeApplicationandPossibilitiesforFutureDevel-
opment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149
7 Summary 156
8. (cid:214)sszefoglalÆs 158
8.1. (cid:218)j m(cid:243)dszertan az informatikaoktatÆsban . . . . . . . . . . . . . . . . . . 159
8.2. MultiparadigmÆsprogramozÆsinyelvekhasznÆlataamestersØgesintelli-
gencia oktatÆsÆban . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161
8.3. Programoz(cid:243) versenyek lebonyol(cid:237)tÆsa a ProgCont alkalmazÆssal . . . . . 164
Bibliography 170
List of Publications 171
Acknowledgments
First of all, I would like to thank my supervisor, Fazekas GÆbor, for his guidance and
encouragement. I am also very grateful for the invaluable help and support given by
VÆrterØsz Magda, who acted like a mentor throughout my whole career. Many thanks
to my colleague and friend K(cid:243)sa MÆrk for all the useful advice he has given me, as
wellasSterbinszkyN(cid:243)raforthebaseideaofthisthesis. Finally, Ithankmyfamilyfor
their support and long-su(cid:27)ering patience.
The work is supported by the T`MOP-
4.2.2/B-10/1-2010-0024 project.
The project is co-(cid:28)nanced by the Eu-
ropean Union and the European Social
Fund.
CHAPTER 1
Introduction
Until recently, programming was about using pure, single-paradigm techniques. How-
ever, nowadays programming languages tend to converge to one another, i.e., features
of one paradigm are appearing in languages based on another paradigm [23, 24]. This
process can be observed primarily in the area of imperative, object-oriented, and func-
tional programming languages. For example, C# or D are based on the imperative C
language, extended with object-oriented and functional language elements. Another
example is CLOS, which is a functional language based on Lisp, with added object-
oriented features. Such languages are called multiparadigm programming languages.
The advantage of these languages is that the programmer may select the paradigm
best suited for solving a particular problem. We may even choose to create di(cid:27)erent
parts of the same program using techniques from di(cid:27)erent programming paradigms.
If a small part of a large application requires high e(cid:30)ciency, imperative code is used,
reusable types are created in an object-oriented way, while in some domains of com-
putation, we choose the functional approach because solutions to problems in these
domains can be expressed in a more succinct way compared to using imperative code.
I believe that multiparadigm languages can be a great help in the education of
computer science. Instructors may show di(cid:27)erent versions of the same algorithm de-
pending on the paradigm used to implement it, and later students may decide which
paradigm to choose in a homework assignment, an exam, or at work, depending on
the problem speci(cid:28)cation and the student’s programming experience. Of course, we
don’tnecessarilyneedtousemultiparadigmlanguagesforthispurpose,wecanalsouse
multiple single-paradigm languages, but this way, we don’t have to teach and students
don’t have to learn yet another language just for coding a particular algorithm.
Duringmyresearch,IexaminedthepossibilityofusingF#asanewmultiparadigm
programming language for coding di(cid:27)erent algorithms in the area of arti(cid:28)cial intelli-
gence (AI). I chose this area for three main reasons. First, I used to be an instructor
of the seminars of the Introduction to Arti(cid:28)cial Intelligence course at the University of
Debrecen [28]. Second, AI and search algorithms, in particular, seemed to be a (cid:28)eld
of computation where we can make use of functional programming because some sub-
stantial parts of these algorithms (like, for example, checking operator preconditions)
are essentially functional. And third, I had a couple of imperative and object-oriented