1. 25 | International Journal of Computer Systems, ISSN-(2394-1065), Vol. 02, Issue: 01, January, 2015
International Journal of Computer System (ISSN: 2394-1065), Volume 02, Issue 01, January, 2015
Available at http://www.ijcsonline.com/
A New Concept on Thinking Machines (Cyber Personality)
Indrajit Sinha, Dr. Kanhaiya Lal
Computer Science and Engineering,
Birla Institute of Technology Mesra,
Birla Institute of Technology Patna Campus,
Near Patna Airport, India-800014
Abstract
This paper deals in introducing a new concept on thinking machines. Although research on understanding emotional
intelligence has already started this paper provides a model where the entire personality can be implemented in a
machine such that the machine behaves like a particular individual. In other words one man for one machine. It
introduces a new model for implementing personality in a machine, in other words cyber personality.
Keywords: Cyber Personality, Artificial Intelligence, Turing Machine, Natural Language Processing, Emotional
Intelligence and Expert Systems.
I. INTRODUCTION
“A chatbot is a computer program designed to simulate
an intelligent conversation with one or more human users
via auditory or textual methods, primarily for engaging
in small talk. The primary aim of such simulation has been
to fool the user into thinking that the program's output has
been produced by a human (the Turing test).”[1],[2].
Cleverbots are a modified version of chatbots. ”Unlike
other chatterbots, Cleverbot's responses are not
programmed. Instead, it learns from human input”[6].
Most machines so formed to think, can basically take
information from humans and store them in a database.
The way this is done has simply developed through the
ages but in this article I am going to present an idea in
which a machine will not only store data but will also be
able to think and make logical decisions of its own.
“Elbot is a chatterbot created by Fred Roberts. “[4].”
Jabberwacky is a chatterbot created by British
programmer Rollo Carpenter.”[5].”ELIZA is a computer
program and an early example of primitive natural
language processing.”[8]. “A.L.I.C.E. (Artificial
Linguistic Internet Computer Entity), also referred to
as Alicebot, or simply Alice, is a natural language
processing chatterbot.”[7].
However my paper also involves applying a better
mode of linguistics which is “the scientific study of
languages”[9].Linguistics involves certain characteristics.
The minimalist program “is a major line of inquiry
developing under generative grammar”.[10].Phrase
structure “are a way to define a given language‟s
syntax”[11].Syntax on the other hand “is the study of
principles and processes by which sentences are
constructed in a particular language”[12].This whole thing
is designed using a sentence diagram which is “a pictorial
representation of the grammatical structure of a
sentence.”[13]. “Human beings are specialized in creative
thinking but limited in ability to deal with large amount of
data. Statistical and empirical methods can help discover
some underlying rules.”[24].All these concepts are applied
in an expert system. The use of expert system is common
for building the Turing machine. As expert system falls in
the domain of artificial intelligence there is a constant
strive to make it behave more like humans. The field of
Artificial Intelligence goes as it is stated that “it attempts
not just to understand but also to build intelligent
entities.”[21]. This is where my research steps in where
the psychological effects of emotions is considered. In
other words emotional intelligence is considered as a
factor. “The study of emotion (as one form of the state of
mind) started more than a century ago, and today, much
has been learned about the physiological and
psychological aspects of emotion. The introduction of
signal processing techniques for more quantitative
emotion studies started more recently.”[23]. I have also
considered ideas, wisdom and thoughts to be particular
traits to define a particular personality of a specific person.
“Personality is an individual‟s…unique pattern of traits
and, it is the organized whole (system), that is constituted
of parts or elements (subsystems), and separated somehow
from an environment with which it interacts” [25].Here
these traits have been taken as separate forms of data in
separate sections discussed later in this paper.
II. PREVIOUS WORK
1. Virtual Personalities: A Neural Network Model
of Personality by Stephen J. Read and Lynn C.
Miller published in “Personality and Social
Psychology Review” in2002, Vol.6, No.4, 357-
369.
2. Developing Brain Computer Interface Using
Fuzzy Logic by Mandeep Kaur and Poonam
Tanwar published in “International Journal of
Information Technology and Knowledge
Management” in July-December 2010, Volume 2,
pp. 429-434.
However both have certain disadvantages:-

2. Indrajit Sinha et al A New Concept on Thinking Machines (Cyber Personality)
26 | International Journal of Computer Systems, ISSN-(2394-1065), Vol. 02, Issue: 01, January, 2015
1. The previously mentioned work of Stephen J.
Read and Lynn C. Miller did not include
learning, feedback control-loops and emotional
reactions.
2. The previously mentioned work of Mandeep
Kaur and Poonam Pandey acknowledges the
difficulty in recognizing emotions.
III. METHODOLOGY
A. Predicate Calculus Used
“To make such a machine it should have the following
characteristics.
A knowledge base of a particular individual with a
stored record of its specific thoughts ideas and knowledge
which is certainly not in all fields.
1. It should have a self-learning dictionary and a sentence
construction grammar program.
2. The thinking process is to use previous knowledge of
response of humans to general common questions and
refer to dictionary and grammar to create own several
answers for each common question such that same
answer is not given twice.
3. Inference to questions can be done by comparing the
sentences with equivalence laws like:-
a. Idempotency
PVP=P
P&P=P
b. Associativity
(PVQ)VR=PV(QVR)
(P&Q)&R=P&(Q&R)
c. Commutativity
PVQ=QVP
P&Q=Q&P
P<->Q=Q<->P
d. Distributivity
P&(QVR)=(P&Q)V(P&R)
PV(Q&R)=(PVQ)&(PVR)
e. De Morgans‟Law
~(PVQ)=~P&~Q
~(P&Q)=~PV~Q
f. Conditional Elimination
P->Q=~PVQ
g. Bi Conditional Elimination
P<->Q=(P->Q)&(Q->P)
4. They can then follow the inference rules :-
a. Modus Ponens
P and P->Q=>Q
b. Chain Rule
P->Q and Q->R=>P->R
c. Substitution
PV~P=>QV~Q
d. Simplification
P&Q=>P
e. Conjunction
P and Q=>P&Q
f. Transposition
P->Q=>~Q->~P “[14],[15],16],17],[18],19].
B. X-Bar Theory
“The X-bar theory revolves around a binary X-bar tree in
which:-
There are three general types of nodes: X, X(bar)
and XP.
Each node has at most two branches.
Leaves are words.
In English specifiers enter XP nodes from one
side; complements enter X(bar) nodes from the
other. The direction from which specifiers and
complements enter is language specific.
The kind of phrase that can serve as a specifier for
a particular kind of XP or complement for a
particular kind of X(bar) depends on the occupant
of the head position X.
This theory presents a general schema for the construction
of English grammar:-
Specifiers: - A word or phrase brought in from the
left which adds a description or forms a part of a noun,
verb or preposition is called a specifier.
Complements: - A word or phrase coming in from
the right which forms a part of a noun, verb or preposition
is called a complement.
The XP at the top is the maximal projection of the
phrase.
The X at the bottom is the head node or head of the
phrase.”[20].
IV. PROPOSED MODEL OF CYBER PERSONALITY
Figure 1. Proposed Model of Cyber Personality

3. Indrajit Sinha et al A New Concept on Thinking Machines (Cyber Personality)
27 | International Journal of Computer Systems, ISSN-(2394-1065), Vol. 02, Issue: 01, January, 2015
A.I Program Interface:-
The A.I Program Interface is the section that is seen by
the user actually. The rest is hidden from the user. It acts
as the input/output interface for the full program.
Feed Input System:-
The Feed Input System is that system where the input
is directly taken from the above mentioned interface. It is
used generally when new data entry has to be made or a
new record has to be created.
Timer:-
The Timer is a section that has a set of predefined time
periods that determines how much the system should wait
before sending a response to the user. This is done to make
the user feel that the reply is given by a human who is
taking time to type the reply.
Inference Engine:-
The Inference Engine is the part that does the actual
thinking and analysis. It does take the help of other
sections here but connecting all logical results to form a
complete result that makes sense and can be used to send
the output is done here.
Knowledge Base:-
The Knowledge Base is the section that will hold the
databases to different records for references. It is the main
information storage part of the program.
Virtual Personality:-
The Virtual Personality will hold the details of the
personality of a specific person such that it will make the
machine think like him/her. It will have its own
departments to store the character‟s ideas, memories and
knowledge in a format comprehendible by the program.
Memory Base:-
The Memory Base is one of the departments of the
Virtual Personality section that will hold the description of
each event as separate records.
Ideas & Thoughts:-
The Ideas & Thoughts department of the Virtual
Personality section will contain the definition of each idea
of the character in different topics or fields as different
records.
Worldly Knowledge:-
The Worldly Knowledge is a department that will have
separate records for details of each piece of knowledge
that the character so created will have in various fields of
topics.
Psychology Comparison System:-
The Psychology Comparison System will be used by
the Inference Engine to compare the user input and replies
with stored data to understand the user and make a
temporary profile of him/her for reference to create
suitable replies.
Human Nature Database:-
The Human Nature Database is a part of the
Knowledge Base. It has a database of psychological
records that stores the relation between human behavior
and the type and pattern of response given by human to
different verbal stimuli.
Language Database:-
The Language Database is the key to proper analysis
here. This is the section that will produce results that will
help to understand the statements of the user used in
communication. It has two sections Dictionary and
Sentence Inference Engine.
Dictionary:-
The Dictionary will simply be a digital dictionary that
will contain meanings of various words. It will have a self
–learning property to enter meanings of new words and
keep itself updated with time.
Sentence Inference Engine:-
The Sentence Inference Engine is the section that will
be used to decipher the meanings of each sentence used by
the user in communication whose result shall be used to
create an appropriate reply. This section will use the X-
BAR THEORY to achieve this.
Temporary Thought:-
The Temporary Thought section is actually the section
that is later used when Present event section is considered
at a later part. It helps to create a temporary data based on
fuzzy logic data on emotional intelligence. It is used to
check the attitude and ultimately the belief in present
scenario of the user because “Beliefs have a special status
in that they are foundational in forming attitudes and
perceived norms and are the only inroad to changing
attitudes, perceived norms and, ultimately, intention.”[26].
Present Event:-
The Present Event stores the present reply of user for
analysis of his/her emotions.
V. PROPOSED ALGORITHM
1. The AI Program Interface is used to take input
from user.
2. This input statement is taken to the Feedback
Input System.
3. The Feedback Input System sends the statement
to Knowledge Base to check for existence of
predefined sample.
4. A sample of reply is stored in Present Event
section for later purpose.
5. The Knowledge Base compares the sample within
its database and sends a success or failure result.
6. In case of a successful hit, an appropriate
predefined sample answer is sent to the Feedback
Input System.
7. On receiving a success result follow from step 30
onwards.
8. In case of a failed hit, the Knowledge Base sends
the statement to the Language Database.
9. The Language Database checks for common
words and meanings by referring to the
Dictionary.
10. The sentence is then analyzed for constraint
meaning in the Sentence Inference Engine using
the X-BAR THEORY already discussed.
11. A complete report is made by the Language
Database and sent to the Knowledge Base.
12. The Knowledge Base uses this report to compare
with stored records in the Human Nature Database
to make an analysis on the nature and attitude of

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28 | International Journal of Computer Systems, ISSN-(2394-1065), Vol. 02, Issue: 01, January, 2015
the user. This result can be used to form a suitable
reply.
13. The result formed is sent to the Feedback Input
System.
14. On receiving a miss report the Feedback Input
System sends the statement and the result from the
Knowledge Database to the Inference Engine.
15. The Inference Engine goes through the report sent
by the Feedback Input System using Equivalence
Laws and Inference Rules.
16. If the report on the nature of the user given by the
Knowledge Base is sufficient then jump to step
18.
17. If the report on the nature of the user given by the
Knowledge Base is not sufficient then use the
Psychology Comparison System to compare the
report with a set of predefined records.
18. Form a result and store it in the Human Nature
Database.
19. Send the result to the Virtual Personality.
20. The Virtual Personality section compares the
report received with records from the Memory
Base for a match.
21. It stores the match/mismatch result and further
compares the report with the records stored in
Thoughts and Ideas section.
22. It again stores the result and compares the
original report with the records of Worldly
Knowledge database.
23. It takes the result from this section and then forms
a report based on the results collected from the
three sections.
24. If the report formed gets a suitable pattern to be
stored in one or more of the three sections then
new records are entered and stored in the
respective sections.
25. The report thus formed is sent back to the
Inference Engine.
26. The Inference Engine sends the report to the
Language Database to form a suitable reply. The
report is formatted using Equivalence Laws and
Inference Rules by the Inference Engine.
27. The Language Database uses its Sentence
Inference Engine to create a meaningful sentence
(again using the X-(BAR) THEORY) and
consulting the Dictionary for words and their
meanings.
28. The answer formed is sent back to the Inference
Engine.
29. The Inference Engine sends the result to the
Feedback Input System.
30. The Feedback Input System sends the result to
AI Program Interface after a predefined period set
by the timer.
31. The AI Program Interface displays the output to
the user and takes for reply from the user.
32. The reply is sent to the Feedback Input System
which sends the reply to the Knowledge Base.
33. The Knowledge Base uses the facilities of
Language Database to determine the result.
34. Repeat steps 19 to 24.
35. Take data from Temporary mood and consider
data from Present event module to form a better
analysis.
36. If result is a statement related to the systems
statement, the answer is stored in the Knowledge
Base else returned to the Feedback Input System.
37. If the answer is stored the Feedback Input System
informs the Inference Engine which starts forming
a new chat or wait for user‟s response based on a
predefined set timer.
VI. MATHEMATICAL PROOF
Lemma 1. IN INPUT,
Figure 2. Input sample using X-BAR Theory
We take P as “Hi”, Q as “how are” and R as “you”.
Now using Equivalence Laws: -
PV(Q&R)->(PVQ)&(PVR) (Distributivity Law)
Let (PVQ) = S and (PVR) = D
Therefore,
PV(Q&R)->S&D
Using Inference Rules: -
PV(Q&R)->S (Since, P&Q->P,Simplification
Law)
Thus Resultant is => S
Which means => PVQ?
This means resultant has “Hi” and “how are”.
Lemma 2. IN OUTPUT,
Here the “I am” or R is missing.
Thus using Inference Rules: -

5. Indrajit Sinha et al A New Concept on Thinking Machines (Cyber Personality)
29 | International Journal of Computer Systems, ISSN-(2394-1065), Vol. 02, Issue: 01, January, 2015
P&Q
->(P&R)&Q (P becomes P&R Simplification rule used
in reverse to bring in the missing link R)
Using Equivalence Laws: -
->P&(R&Q) (Associativity Law)
Now on replacing variables with constraints we
get: -
Hi, I am fine.
(Note: „,‟ is given after observing user‟s format and “.”
Is given in place of “?”)
Hence the user gets a suitable reply.
Figure 3. Output sample using X-BAR Theory
VII. CONCLUSION AND FUTURE SCOPE OF THE WORK
This paper presents a new concept on implementing
the complete personality of a human inside a computer
such that it will not only reply using proper statements but
it will also have memories of that particular person. Hence
it will think like a person and perceive emotions of others
as that person would do.
This concept has added advantages over previous
mentioned works as it includes learning, feedback control-
loops, and emotional reactions and has the facility for
development of identification of different emotions.
However for future work there is the possibility to
make pseudo code along with fuzzy tables of emotions to
further this research as it is stated by Lorini and Francois
that “Indeed, in order to build artificial agents with the
capability of recognizing the emotions of a human user, of
anticipating the emotional effects of their actions on the
human, of affecting the user‟s emotions by the
performance of actions directed to his emotions (e.g.
actions aimed at reducing the human‟s stress due to his
negative emotions, actions aimed at inducing positive
emotions in the human), we must endow such agents with
an adequate model of human emotions.”[22].
ACKNOWLEDGMENT
I would like to acknowledge my institute Birla Institute
of Technology Mesra, Patna Campus for providing me the
infrastructure to implement our research. I also want to
acknowledge my parents and my brother whose constant
support helped me through the difficult times.
REFERENCES
[1]. http://en.wikipedia.org/wiki/Chatbot
[2]. http://en.wikipedia.org/wiki/Chatterbot
[3]. http://en.wikipedia.org/wiki/Artificial_intelligence
[4]. http://en.wikipedia.org/wiki/Elbot
[5]. http://en.wikipedia.org/wiki/Jabberwacky
[6]. http://en.wikipedia.org/wiki/Cleverbot
[7]. http://en.wikipedia.org/wiki/Artificial_Linguistic_Internet_Co
mputer_Entity
[8]. http://en.wikipedia.org/wiki/ELIZA
[9]. http://en.wikipedia.org/wiki/Linguistics
[10]. http://en.wikipedia.org/wiki/Minimalist_syntax
[11]. http://en.wikipedia.org/wiki/Phrase_structure_rules
[12]. http://en.wikipedia.org/wiki/Syntax
[13]. http://en.wikipedia.org/wiki/Sentence_diagram
[14]. http://en.wikipedia.org/wiki/Propositional_calculus#Inference
_rule
[15]. http://en.wikipedia.org/wiki/Propositional_calculus
[16]. http://en.wikipedia.org/wiki/Logical_equivalence
[17]. http://en.wikipedia.org/wiki/Predicate_logic
[18]. http://en.wikipedia.org/wiki/Rule_of_inference
[19]. http://en.wikipedia.org/wiki/List_of_rules_of_inference
[20]. Artificial Intelligence by Patrick Henry Winston
[21]. Artificial Intelligence by Elaine Rich, Kevin Knight and
Shivashankar B Nair
[22]. Emiliano Lorini, Francois Schwarzentruber,”A logic for
reasoning about counterfactual emotions,” Elsevier Artificial
Intelligence 175,pp. 814-847,2011.
[23]. Mandeep Kaur, Poonam Pandey,”Developing brain computer
interface using fuzzy logic,” International Journal of
Information Technology and Knowledge Management,
Volume 2,No. 2, pp. 429-434, July-December 2010.
[24]. Hai Zhuge,”Interactive semantics,” Elsevier Artificial
Intelligence 174, pp. 19-204, 2010.
[25]. Stephen J. Read, Lynn C. Miller,”Virtual:Personalities: A
neiral network model of personality,”Personality and Social
Psychology Review,Volume 6, No. 4, pp. 357-369,2002.
[26]. Mark G. Orr,Roxanne Thrush,David C. Plaut,”The theory of
reasoned action as parallel constraint satisfaction: Towards a
dynamic computation model of health behavior,”PLOS One,
e62490, Volume 8, Issue 5, May 2013.