Paper

An Artificial Ego Architecture
人工自我の基本設計

MITSUYOSHI Shunji

TOMONAGA Kosuke

光吉 俊二

朝長 康介

The University of Tokyo, Collaborative Researcher

The University of Tokyo, Graduate School of Engineering,
Project Associate Professor

東京大学大学院工学系研究科

東京大学大学院工学系研究科 特任准教授

HASHIMOTO Masatsugu

TEI Yuichi

橋本 昌嗣

鄭 雄一

The University of Tokyo, Professor

Digital Hollywood University, Graduate School, Visiting
Professor

東京大学大学院工学系研究科 教授

デジタルハリウッド大学大学院 客員教授

Last year we presented the paper,“Some hypothesis to derive an anti-Einstein field”, and in order to realize this
proposed a Mitsuyoshi operator axiom. Meanwhile, current AI research using threshold values is an exercise in
optimization, and proceeding along those lines cannot achieve a robot using its own consciousness to make a judgment.
Thus we, who had invented an emotion generation engine that was loaded onto the communication robot Pepper,
decided to create a product having initial artificial ego reaction that with its own consciousness would make judgment. In
addition, we have been moving forward with the modelling of morals. We propose to further develop these to function as
the superego, and at the same time using the Mitsuyoshi operator to realize an artificial ego (AE).
Keywords: Artificial ego (AE),“Some hypothesis to derive an anti-Einstein field (TOE), function-based quantum gates,
function-based communication, Mitsuyoshi operator, cut operation, superposition operation, moral control (MC)

1. Introduction

is a problem, and avatars and robots that refer to past data and1.1 The Artificial Ego

act on pattern matching, no matter how many there may be, will

The term“artificial ego”refers to the ego-based judgment

not be able to break out of the framework of thought and will not

function possessed by an artificial computer, as used in robots or

be of use. In the end, the operator’s capacity to make decisions

artificial intelligence. Currently, in the field of artificial intelligence,and take responsibility will be put to the test, and the operator’

there are no established means for addressing the current realitys ability to solve problems will be where a bottleneck forms. Onof changing circumstances, where conditions and environment

the other hand, if there is even one avatar or robot that can(assumptions) change moment to moment. It is for this reason

and creatively propose fundamental solutions that go beyond itsthat self-judgment as humans do is necessary; to this end, we

framework of thought, the operator will be freed from the dilemma

decided to call this field artificial ego (AE) research, where theand will be able to consider solutions in a new framework offocus of study are matters such as how to define and express

thought.

mathematically the“consciousness”and“free will”that machines

If there are ideas in the same number as the number of avatars

are to have and how to recreate these through engineering. We

and robots, then options will increase to that extent. Getting

first used this name at a luncheon seminar at the IEEE (SMC)

back to the trolley problem, if a robot in the same tight spot as

2018.

the operator came up with the idea of derailing the trolley toArtificial egos are most needed in circumstances where one

stop it and, discovering that there were enough rocks on theoperator is controlling anywhere from 10 to 10,000 avatars or

ground right there to derail the trolley, proposed that solution,

robots. In such circumstances, what is needed is autonomous

the operator would not have to make the“choosing who will die”

avatars and robots that do not rely on external commands anddecision of right or left. The second reason is that the number ofbehave morally and creatively even in unfamiliar circumstances.

avatars and robots that an operator can control simultaneously

We are researching function-based quantum gates, artificial

is proportional to the creative problem-solving capacity of theegos, and function-based communications as the technology

avatars and robots. More specifically, once avatars and robots

essential for realizing a moral and creative activity.

attempt to solve problems creatively and ask the operator for

There are three reasons why morals and creativity are needed

their judgment only for those important matters they cannot

when controlling 10 to 10,000 avatars or robots. First, unlesssolve, then the operator can concentrate on the control ofavatars and robots have creativity, the ability of the operator toimportant matters for a large number of avatars and robots.

solve problems will be where a bottleneck forms. For example, in

If they require a command for each and every move when in

unfamiliar circumstances where a dilemma arises, as in the“trolley

unfamiliar circumstances, then control of 10 to 10,000 avatars

problem”, the very falling into a specific framework of thoughtor robots will not be possible. The third reason is that unless©︎2020 Digital Hollywood University

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the creative problem-solving methods are moral, problems will

the difference in functions between AI (neural networks, direct

arise to the extent the avatars and robots are assigned tasks.

learning, and machine learning) and the artificial ego.

Accordingly, if avatars and robots will be emergent, then moral
control becomes particularly important, and how to makeconduct not justified by past data into something acceptable topeople becomes the challenge.

1.2 Progress in Artificial Ego Up to Now
The image that people generally have of the ego is“selfish”
and “being out-of-control and without regard for others”.
However, in dynamic models of the ego used in medical
fields [2], the ego is the condition of the superego (morals)

Figure 2: Features of Artificial Ego

controlling desires.

2. Consciousness through Cognition (Learning) and Free
will from Vectors (Education)
Deep learning uses a multilayer artificial neural network in orderto map input data X into output data Y. While this technology
began around 1980, with the recent dramatic advances in
hardware and the rise of GPUs, research has intensified. With
SVM, classification and regression analysis is carried out using
hyperplanes to find the largest margin between points (data) in adata set. Thus, most AI can be described as a pattern matching
function that finds an approximate value using a probability
model. Accordingly, it cannot be said that a human-like judgment
by oneself has been attained, and this is merely patternmatching with sensor and image analysis. If we think of this as
Figure 1: Dynamic Model of Ego

the cognitive function of sensors, then to improve precision, an
excessive amount of learning data is required and people must

Therefore, we employed this to serve as the ego of the artificial

attach flags to teach pattern matching. The chart below is aego. If we look back at the history of the artificial ego, thecomparison of the features and ways of using existing machine

starting point will be research at MIT, where in 1997, Rosalindlearning neural networks.

Pickard, an MIT professor, put forward the book Affective
Computing [3]. In Japan, in 1991, AGI Japan Inc. announced thevoice emotion recognition technology ST [4], which is currently
used in the communication robot Pepper and the Nintendo
DS software“Kokoro Scan”, and is used in medical fields, forexample, in the verbal analysis of pathophysiology [5] to analyze
a patient’s condition from the patient’s voice, as in the publicly
available product Mimosys. However, these technologies alluse sensors to recognize emotions. Then, Pepper mentioned
above, which appeared in 2017, not only used voice emotion
recognition, but had a newly developed emotion generationengine [6] that generated robot“emotions”and the resulting“likes”and“dislikes”. In reaction to information from assorted

Figure 3: Existing AI

sensors built into a robot, pseudo-hormones are constructed andcaused to react and from such change emotions are generated

Meanwhile, with the artificial ego that we are currently

and a judgment of like or dislike is made. We named this function

researching, what is necessary is not the above learning, but thethe virtual ego.

“fostering”and“education”that humans need for growth. Thisis because it is not a system where pattern matching and actions

1.3 Problems with Robots Having Emotions; Solutions

and reactions are prepared in advance like a dictionary, but

Proposed by Artificial Ego

rather a system where in order to make judgment by itself using

In the development of Pepper, we found that a robot thatan ego in the same manner as people, artificial intelligence mustmoves simply based on“drive”and“emotion”is not very useful

be sensitive to and understand changes in assorted conditions,to humans in daily life and we learned that much of the trouble

reproduce this by itself, and have a desire-like free will.

comes from a robot’s fear of people. Thus, at Tokyo University,
we initiated the social cooperation program Mathematical

2.1 Initial Experiments using Artificial Ego (Virtual Ego)

Engineering of Morality Emotions, for the study of moral control

In 2014, we developed, as a virtual ego, something that canof AI and robots, where currently we are researching AI andbe called the initial stage artificial ego, namely, an engine forrobot control using the superego (morals). Figure 2 shows©︎2020 Digital Hollywood University

generating a robot’s“likes”and“dislikes”. First, we will explain the15

DHU JOURNAL Vol.07 2020

“Emotions Map”[7] used to generate emotions in the virtual ego,

2.3 The Difference between Consciousness and Free WillAs the following diagram shows, there is a principle that in orderand then we will explain how this is the source of a robot’s“drive”.

to organize the feelings and emotions generated as discussed
above in Section 2.1 as elements and generate a robot’s freewill, the robot itself should set the objective or destination.
There is a need for grounds for positing in a mathematicalmodel that this self-generation of objective naturally generates“consciousness”. See the 2019 DHU Journal [12] for an
explanation of the symbol

appearing in the diagram.

Figure 5: Destination Point

2.4 Generation of Original Free Will (function)
For example, if the command for moving

is f(x) =ax+b , thenit is simple to make current conditions (independent variable) x
and the objective or destination ([dependent] variable) y.
Figure 4: Emotion Map
The above emotion map was used to generate a robot’s“drives”. Specifically, we set up the robot so that some events it
detected were associated with pseudo-hormones, but when thesame event was detected another time, a different emotion was
output depending on the hormone balance. We also set up therobot so that even with the occurrence of an event that was not
associated with a hormone, the hormone balance would cause
an association, which would then be updated.
For example, the event of being in a dark place is associatedFigure 6: The Directionality of Desirewith noradrenaline, but if a friend is there too, the event isassociated with serotonin. Therefore, the state of being alone in

Deep learning and machine learning cannot automatically adapt

a dark place will result in noradrenaline being secreted and fear

to changes in assumptions, commands or circumstances. In

being output, but being in a dark place with a friend will result inother words, they cannot handle situations where an obstacle asserotonin being secreted and anxiety being output. In addition,

depicted below arises.

we decided that with the event of a stranger‘s presence, theupdating of the hormone association would depend on theexperience. For example, let us use the experience of a guest
that a family does not know well visiting, and the household,which is usually somber and strict, being filled with good cheer;
because of this experience, just the presence of a stranger willcause the output of pleasure.

2.2 Public Experiment of the Virtual Ego

Figure 7: Change in Circumstances

We carried out an experiment at a presentation open to thegeneral public; the robot, which under the initial settings should

If the operation ofhave behaved calmly on the stage, began to feel extreme anxiety

is used in the equation y=x2-x-2, theobstacle can be avoided as shown in the following graph.

when the presentation started and ran about wildly and acted out

However, if we consider what can be done so that a machineof control. Its behavior is available for viewing in the TED Tokyo

can itself derive a secondary function from a primary function,

Archives. We believe that the cause of its acting out of control
may have been the darkness caused by the thick cloth thatcovered it just before the presentation or by the stage lighting
or excessive inputs by the audience. From this, we learned thatyou cannot created a robot that can coexist in the daily life of
humans simply by generating emotions.

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Figure 10: Plotting as a Feynman Matrix Vector
Figure 8: Avoiding an Obstacle
We can see that the vector direction changes with each layer.
the answer will be any of the following.

This can be applied to the generation and change of emotions of

A: External command (change of conditions, input of function)

an initial-stage artificial ego (virtual ego).

B: Learning (brute force)
C: Trial and error (like a person, based on lack of experience)

2.6 The Function of Emergence (Induction)

D: Emergence (doing something that no one taught it)

Here, we consider how a machine perceives a person with

Because deep learning and machine learning are capable of A

which it is interacting. For this purpose, we newly defined aand B, the challenge becomes C and D.

new mathematical model called the relationship of“anti”. The
following table shows this definition.

2.5 Trial and Error like a Person
Thus, regarding trial and error, we turned our attention to

Table 1. Relationship among positive, negative, anti, converse and inverse

vector-valued functions and noticed that if we made thefunction (2cos(t),4sin(t),t), the mapped vector formed a spiralin a three-dimensional Euclidean space. If given vector-valued
function ƒ, we make ƒ i a function that tracks only the map
vector's no. i component (where I equals 1,..., n), then f can be
expressed as the n th pair of real functions ƒi. By plotting this asa Feynman matrix vector, we can find directionality in the large
sense as a vector. The robot can learn by judging whether that
vector matches a commanded vector. Because a matrix vector iswhat Feynman calls“energy”, it will also be an idea that can be

If in accordance with this definition, we let the state of“anti”beused in the generation of emergent drives (desires). The domain

the“inverse of converse”(inversion of attributes), the elements

can be one-dimensional or multi-dimensional.

of emotions will be as illustrated in the diagram below.

Figure 9: Vector-Valued Functions

Figure 11: Communication between Positive and Anti

The following diagram shows the phase-transition movement

With this, the creation of a robot's drive through inducementof the layers that meanderingly follow the final instruction vector,

with respect to the emotional vector of the counterparty becomesplotted as a Feynman matrix vector.

simple mathematically.
A moral and creative autonomous control system for avatars androbots—that is, an artificial ego—can be realized with feedback
from anti-fields using the mathematical model we propose.
Specifically, this is a model where, regarding a function definedon type U1 that includes as elements all entities that an avatar or
robot is aware of under certain circumstances and its opposite,an anti-function defined on type U2 with respect to environmentand objects (people and things), when the energy of the function
and anti-function are in contention above zero, 1 emerges above
U12, which is the opposite of U1 and U2.

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2.7 The Function of Emergence (Phase Transition)

If the mathematical model is applied in the following manner,
the consciousness and free will of an avatar or robot or what

Next, we will explain the mechanism of emergence throughan avatar or robot feels can be defined. More specifically, inphase transition using the formula of the anti-Einstein fielda certain framework of thought (circumstances), the domain

hypothesis in the paper discussed above.

and range of a function are set so as to include as elements

l im

n→∞

l im= 0 ⇔ 1 s h o w s t h a t w i t h i n f i n i t e s i m a l a n d i n f i n i t e
n→0

all parameter movements and relationships relating to events, for both the infinitesimal and the infinite, the limit forthat avatars and robots perceive (feel) as being internal, andcountable numbers for both zero and ∞ is the integer 1; forthe domain and range of the anti-function are set so as toexample, with the infinitesimal, the only existence smaller than 1

include as elements all parameter movements and relationships

will be zero. Therefore, this becomes a world of size (continuous

relating to events that avatars and robots observe as something

quantity) and an argument of １⇔∞ or 0 ⇔ 1. This expresses, as

external. The space combining the domains and ranges of thisthe smallest unit where time and space can be measured, thatfunction and anti-function will constitute the consciousness, orimwhen mass / 0, then ln→∞consciousness space, of an avatar or robot. Further, feedbackin the following diagram corresponds to this. In the paper, within

control is applied to the function and anti-function by vectors (freethe Schwarzschild radius at this time, the principle of emergencewill) implementing control so that the energy of the function andis shown mechanically.

l im= 0 ⇔ 1. The broken-line red circle
n→0

anti-function are in contention at zero above the consciousness
space, and after contention, the consciousness space is
automatically expanded so that the entities and events up tothat point can be captured from the inverse and converse of the
consciousness space.

Figure 13: Infinite and InfinitesimalThrough phase transition using this, the class layers in the
Figure 12: Proposed Model

Feynman matrix discussed above can move freely as in the
diagram below. At this time, it is not trial and error but class

With this, the concept of“problem”can be defined as an event

jumping through phase transition that occurs, and this is used inthat impedes the contention between function and anti-function,

the principle of emergence.

and the concept of problem solution can be defined as achieving
contention between a function and anti-function. Therefore,
under our mathematical model, avatars and robots can berealized that have their own free will of trying to solve unfamiliar
problems, and when they are solving problems, behavior canbe achieved where at the time of problem solving avatars androbot go beyond their framework of thought and attempt to solve
the next problem from a larger consciousness space. Further, if
avatars and robots can perceive morals as a contention model
between the primary free will (drive) that they have internally andcultural knowledge (superego) that they have externally, thenFigure 14: Phase Transition

it will be possible to write morals control as feedback control offunctions by anti-functions; accordingly, if it becomes possible
to derive anti-functions through physical experiments, it will

3. The“Superposition Operation”Necessary for True

also be able possible to implement a mathematical model for

Emergence

moral control. Further, function-based communications can be

With the infinitesimally small world expressed as the broken-

realized as a mechanism for avatars and robots to transmit theline red circle below, we can think of its structure mechanicallydivergence between the function energy and anti-function energy

and anti-l1imareas in the diagram below. We then notice that l1im→0→0when the two are not in contention. This mechanism seems tosuperposed. Instead of multiplication, let us carry out the newshow behavior like harmonic oscillators transmitting divergence“superposition operation”.

from the center as waves, but it engages in behavior that differsfrom wave propagation by harmonic oscillators in two regards,
first in that for all individual pieces, there is emergence at time ofcontention (mapping to U12) and second in that feedback control
operates in the consciousness expanded through emergence.

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Figure 15: Superposition of Size
“Superposition operation”, a technique shown in the following
Figure 18: Anti-lim

diagram, is a mechanism explained in the above paper, in the

1→0section of entitled“Division by zero in an anti-Riemann field”.

At this time, we can see the relationship where, at the lefthand side of the circle, the left half heads from 1 to MU, andthe right-hand side goes from MU to emergence at 1. We callthis calculation of superposition so that they exist simultaneously
the“superposition operation”. With this, 1 first emerges at thefield (red semicircular field at left). At the same time, 1 isanti-l1im→0
field (blue semicircular field at right) phase transitioning
the l1im→0
to the anti-field. In the infinitesimally small world, it is ensured
that these will occur simultaneously; this is something that weFigure 16: ０≡ ∞calculated in the foregoing paper, using a Riemann sphere andanti-Riemann sphere.

This condition represents phase transition through the colliding
energy of ∞ and anti- ∞ at the boundary between a null set

4. Function-Based Quantum Gates

and anti-null set. We will explain this portion in greater detail as

The problem becomes an issue of how to realize as engineeringsuperposition operation.

the“superposition operation”which we posit can be calculated
Let us designate the infinitesimal limit (broken-line red circle)

mathematically. Thus we created, similar to“logic gates”in

as KU. 1, which is the smallest KU, as expressed by the blue

computers, “function-based quantum gates” necessary for

quadrangles. The states from this 1 (blue) to complete nothing

artificial ego emergence calculation.

(MU) are expressed in the diagram below.

4.1 Dividing by Zero with the Mitsuyoshi Operation(Cut Operation)
There was a need for a symbol that could enable a“concept”notindicating quantity, such as“right”and“left”, to be included in aformula. For example, let us consider an apple being divided into
two. With mass of the apple as the reference 1, if this is divided
into two equal parts, there will be two pieces with a mass of 0.5.
In order to express this state, there was a need to replace thetraditional division operator of ÷ with a different symbol for cutting(cut operation operator), namely, the symbol.

This is Newton’s law of universal gravitation. In 1973, theauthor tried changing this into a slightly different form.

Figure 17: lim
1→0

Next, 1, which comes first from KU, is expressed by the red
quadrangles. The states from this MU until 1 (red) are expressedin the diagram below.

Figure 19: Newton’s Law of Universal Gravitation
Dividing one apple into two ... One apple

became two.
pieces
But with the division operation, the results are as in Figure 20.

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operation operator

and the Mitsuyoshi operator

areused to express the state of one apple being divided into two inan equation, this can be written as
Figure 20: When an apple is expressed with division

2 ＝ left piece (A)1right piece(B)Equation 1
We notice that the two ends ofare in fact not numbers but

concepts (consciousness). With this type of calculation, it ispossible to easily handle not just numbers and quantities, but
also“concepts”such as left and right at the same time within
Figure 21: The Cut Operator, Which is Different from Divisiona single equation. Meanwhile, for “quantity”, too, with the

If we do this, as shown in the diagram below, when an apple

quantities) as x:y, the calculation of the continuous quantity is

is divided into two, the parts will not be the same size, there

possible. For example, when actually dividing into two, there are) ascases where the ratio is not even but is uneven, such as 0.3:0.7.

will be a large one and a small one. Let us designate (ratio between the weights of apple pieces A and B (continuous

the operation symbol for cutting one apple into two. The means
1of writing the results (state) is shown below. Figure 22 shows

2 ＝ 0.5

0.5 ＝ 0.3

0.7...

changes in pieces with the cut operation
Equation 2
In order to be able to write an equation that covers both 0.5
0.5 and 0.3

0.7, we gave thesymbol a slider function. This

enabled the boundary between x and y to continuously move.

Figure 22: When an apple is calculated using the cut operation (1)Meanwhile, for“numbers”, this can be written:
This is also happening. Let's align both ends! And connect
both ends with rails! Call the ends right and left! Let's write in

1

2 ＝ A(x)B(y)

the middle like this!
Equation 3
Σ

X＝A

B

C〈X-1 ＝ number of〉〈Σ＝ A(x) ＋ B(y) ＋ C(z)〉Equation 4This enables a“concept”such as left and right and“numbers”
and“quantity”to be written in a single equation, as in Figure
25. The relationship between x and y is like this.
Figure 23: When an apple is calculated using the cut operation (2)This is a sign that the lever moves freely between the left andright ends!
What if the division is slightly off?

Figure 25: Slider function of Mitsuyoshi operator

Figure 24: When an apple is calculated using the cut operation (3)We can see that the () used here follows the instructionof dynamically moving the right end and left end. If this cut©︎2020 Digital Hollywood University

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Table 2. Relationship between number of Mitsuyoshi
operators and division and cut operation
÷

(cut)

Number of

÷X

X

(X-1)

÷3

3

(3-1)

÷2

2

(2-1)

÷1

1

(1-1)=0÷00(0-1)=-1

Figure 26: Explanation of Infinity
Next, the infinitesimal will be explained using Figure 27. For
both discrete numbers and size, which is a continuous quantity
or discrete quantity the infinitesimal limit can be called a limit that
does not reach zero. For this reason, this can be expressed as 1,
meaning“in a single limitlessness there is something small”.

Let us simplify 1

2 ＝ A(x)B(y). First, we stabilize the sum
2 and A(x)of the respective sides of the ＝ , namely, 1

B(y),as Σ . Next, we turn our attention to length or other continuous
quantity (x, y) that is a different aspect of A and B, which are“concepts”. If at this time we perform the arithmetic (operation)of moving, x and y can be freely changed. For this dynamic

function to be able to confine this x, y within Σ , it is necessary
Figure 27: Explanation of the Infinitesimal

only to write:
X＝AΣ

Where (X-1) is number ofB

When the number of articles goes from the smallest integer

C…

1 to zero, is this“size”? If this is so, because the only natural
number smaller than 1 is zero, between 1 and zero there is aand X is number of values A, B, C

change of size. If the infinite and the infinitesimal are expressedwith boxes, whether the limitlessness expresses size or whether it

Equation 5

expresses individual number, when we put them together we seeWith this, the“cut operation”, which is different from the equal-

that, as in Figure 28 below, the discrete boxes are superposed.

portion-based“division”and“fractions”, was created.

The difference between the infinite and the infinitesimal is thedifference in the methodology of time. However, if the individual
number is limitless, the sum total Σ will be the superpositioning

4.2“Superposition operation”
Let us consider the above 1

2 ＝ A(x)of the boxes.

B(y) from a different

angle. First, let us stabilize the sum of the respective sides ofthe＝ , namely, 1

2 and A(x)the arithmetic (operation) of

B(y), asΣ . If we perform

moving, x and y can be freelychanged; let us express this as function f. By doing this, welearn that this dynamic function f is a control function. In theabove“anti-Einstein field hypothesis”this control function is
utilized having the Mitsuyoshi operator as
arithmetic of “superposing” using thisoperation”. With thisf

. We call this specialfthe“superpositionf, we have shown with the simultaneous

calculation of separation quantity and continuous quantity thatthe extinguishing of time and the appearance of mass sum canbe calculated with the phase transition of the superposition

Figure 28: Summary of sum total of infinity and the infinitesimal

im and l im . This“superposition operation”is geometric. Itof ln→∞
n→0
im and l im as difference in aspect through passage of
captures ln→∞n→0

We should notice that time is a vector. At such time, we cantime. The diagram below illustrates the temporal relationship ofsee that the time vectors going back and forth between zero andl im and l im in an easy-to-understand manner.
n→∞limitlessness have the same function as the bar and slider of then→0

As shown in Figure 26, the sum total of discrete numbers will

Mitsuyoshi operator. So, if the vectors in both directions of time

not reach infinity, but there will be cases where it will be headed

are replaced with the Mitsuyoshi operator, as shown in Figure

towards infinity or where size is expanding infinitely. The diagram

29, time can be confined within the operator. This enables

gives an explanation using discrete (natural) numbers, so a

the superposition between infinity and the infinitesimal to bestate is shown where there is one of each individual box. If thesummarized as ∞explanation is of size, the expression of“1”will become“N”

0. At this time, the collection of boxes canbe made sum total Σ .

indicating size, but it can be said that sum total Σ will remain“1”.

If all the quadrilaterals ( □ ) are superposed to form a single
mass, as in the diagram, they will form the same figure; this isused in calculations.
and lnim
form a single mass, the passage of time will
If lnim→∞→0©︎2020 Digital Hollywood University

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altogether disappear in terms of directionality. Further, the sum

anti-world and then implementing the proposed model on

total that was superposed simultaneously with the disappearance

that computer. More speciﬁcally, this is the development ofof time will appear there. Here, too, the same slider function as

a function that utilizes the very characteristics of quantum

in the“cut operation”is used and calculation of function (f) is

ﬂuctuation. With this approach, phase transition, criticalcarried out, and we see that with the“superposition operation”

phenomena, renormalization, etc. are expanded based on thetoo, the operator itself swallows time. Generally,“generation andanti-concepts, and, as their existence is demonstrated throughdisappearance”is explained as an exchange relationship.

anti-wave experiments, the quantum gates of MU and KU areused to reproduce the emergence of the artificial ego. Under
this proposal, both of these approaches are employed andimplemented simultaneously and in parallel. In other words, using
von Neumann computer architecture, with the proposed model
as a base, a free-conversation application is run, creating anenvironment where dynamic behavior can be verified through freeconversation with a person, and as we watch to what extent thefunctions that emerge in free conversation match the functions
obtained in the anti-wave motion experiments, we will moveahead with development of quantum gates.
There are three advantages to moving forward in parallel. The

Figure 29: Disappearance of Time through the Mitsuyoshi Operator

first advantage is that verification of the model can be performed
However, in the paper,“emergence”is explained using theat an early stage. More specifically, if the artificial emergence incompatibility (superposition relationship) from calculation of

the free conversation is unnatural from a person’s perspective,function (f) derived from the“superposition operation”having

then the utility of the proposed model itself is called intoa unique slider function. As discussed above, whether heading

question, and the proposed model can be modified at an early

im or heading towards l im , when all quadrangles ( □ ) all
towards ln→∞n→0stage. The second advantage is that it can be confirmed throughsuperposed form a single mass, they form the same figure anda physical experiment whether the phase transition (emergence)

im andthe vectors disappear. (See Figure 30) Further, even if ln→∞from the anti-world actually exists. If the artificial emergencel im are superposed as they are, because their vectors, which arefunctions do not match the results of the anti-wave experiments,

headed in opposite directors, offset each other, they will form

it will be deemed that the artificial emergence was unnatural;a single mass. Further, this mechanism can be replaced with aaccordingly, it will be possible to try subsequently to makefunction, and this can be used in the calculation of geometricmodifications so that the function generation logic in artificial, which has the function of“a moving

emergence becomes more natural. Finally, the third advantage isslider”, engenders the calculation of both the“cut operation”

that when designing the quantum computer, specific applications

and the “superposition operation”; accordingly, these arecan be envisioned. In other words, because a free-conversationcollectively called the“Mitsuyoshi operation”and the symbol

application will be run on von Neumann computer architecture, ititself, as a symbol of calculation, is called the“Mitsuyoshi

will be possible to move forward with quantum computer designn→0state. The symbolon the basis of a specific application example.

operator”.

5. Function-based communication
In order for one (human) operator to control 1,000 or morerobots, function quantum bit communications and function-based
quantum gates will be effective.
(i) A person’s consciousness can be compressed into a function.
(ii) A person’s consciousness can be stored in memory as afunction, which can be reproduced at any time as a feeling,(iii)
These can be achieved for practical use instantaneously withlight function-based communication.
Accordingly, function-based quantum gates (patented) will be
the protocol.
Figure 30:

as used in Some hypothesis to derive an anti-Einstein field

Here we show a comparison between existing computerarchitecture and function-based quantum gates and quantum
computing.
There are two approaches to developing a moral and creativeautonomous control system for avatars and robots; one is
implementing the proposed model using von Neumann computerarchitecture and validating behavior. The other is developing a
new quantum computer that can handle phase transition from the©︎2020 Digital Hollywood University

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DHU JOURNAL Vol.07 2020

Table 3. Function-based quantum gates will be the protocol.

Next, there is the method of assigning a formula.

Quantum

Particles

jump

Waves

MGN( ＋ )MGN( ー )MUmass/ ∞

mass/0(0 ≡∞ )

Superposition

Division by

Division by

operation

infinity

zero

n→0

Most frequently, a function is given by an equation combining

Gate

the four arithmetic operations and other known functions (a closed

KU
l im

this, so we want to avoid this.

l im

n→∞

form of a formula that is not a procedural algorithm operation or alimitless combination).
With such a formula, it is possible to calculate the function value
from any element in the domain.
For example, in the example before the last, f can be defined

BH equation

as f ( n ) := n + 1( n ∈ { 1 , 2 , 3 } ).

When a function is defined using this method, there may becases where it is difficult to decide for what kind of set to define
a function.

The following is a comparison between a function-based
quantum gate where this computational formula is used as the

For example, in a case where the definition formula includes

protocol and an existing logic gate.

division, variable values where the denominator is zero must be
removed from the domain.
Similarly, if a square root is included in the definition of a realfunction, the domain must fit within a set of variables where thearguments of the square roots are non-negative. While this isappropriate for the most highly compressible function-based
communication, division by zero and the solution to imaginary
number problems are possible.
Here, we thought of the method of vector-valued functions.
If vector-valued functions are used, they are convenient formodelling physical properties having KU as a vector up to thesmallest elements of the codomain (mass/0 as the smallest unit
where time and space can be measured). This is appropriate

Figure 31: Function-based quantum gates and Logical gate.

for“treating free will as a vector by deriving the two points ofProfessor Nakamura of Stanford points out that the Mitsuyoshi

origin x and destination y”. For example, in a case where aoperator used here is itself a function-based quantum gate in alarge number of vectors are headed towards the same point

quantum state based on an N-dimensional unitary space that issimultaneously, all the vectors will cross orthogonally at the one

a complex space.

point. Because they have been transferred and aggregated bythis, time and space are contained in a single point. With this,time and space disappear and the vectors naturally reverse

6. Application

directionality and pass through the one point. At this time theWhen function f is given, according to the definition, for eachanti-world is born and in the positive world, emergence (anti-

point x in the f domain, only one value f(x), representing f at x, isworld generation) is possible. Because there are vectors, theallocated. There are numerous ways of specifying or writing the“converse” is created and the world that is “inside out”

method of relating x to f(x) (in every possible way). Accordingly,

because of inversion of attributes can be designated the“anti”.

deciding what to do here is the initial step in research.

Figure 32: How to function.
Figure 33: How to do.
First, there is the technique of writing the values in order. In
the case of a function defined for a limited set, by writing all the
Because vector operations are defined for each component,elements of a codomain allocated to the points in a domain, aif there is a limit to ƒ'(t):=lhim→0function can be defined. For example, when A := { 1 , 2 , 3 },h

, that will match the vector-

valued functions constituted by the differentials of the component

function f: A → R can be given as f ( 1 ) = 2 , f ( 2 ) = 3 , f ( 3 ) = 4.

functions: ƒ'(x) = ( ƒ1'(x), ƒ2'(x),However, a tremendous amount of data is needed to handle©︎2020 Digital Hollywood University

ƒ（t+h)-ƒ(t)23…, ƒn'(x)). Important

DHU JOURNAL Vol.07 2020

characteristics of the differentials of real numbers obtain with

The following diagram shows division by zero as the KU

respect to vector-valued functions. Differential linearity and the rulesuperposition operation.

of product obtain, and as a result, the vector-valued functions willtake a form that uses versors, but there is the differential problem
where the differential of the calculation versor becomes 0 vectors
and the formulation division by zero problem. This is treated as an
infinite differential problem, and is resolved with KU.
All vectors that become KU and head towards MU crossorthogonally through a“sea urchin condition”superposition
operation, thereby causing time and space to disappear, the antiworld to be born, and emergence to occur in the positive world.
Because there are vectors, the“converse”is created, and theworld that is“inside out”through attribute inversion is the“anti”.
So, at what timing exactly is the anti created? In order tounderstand, prove and reproduce this, it was understood in past
papers that it is necessary to prove and reproduce the existenceof“anti-wave motion”and“anti-null set”. If these don’t exist,
then it cannot be said that vectors created consciousness andemergence occurred. If the state of having just a frame but nocontent is a“null set”and the state of having no frame but being
full of content is thus the“anti-null set”, the condition necessary

Figure 36: division by zero.

for having content emerge from nothing from“the meeting of thenull set and the anti-null set”is that“anti-wave motion”relatively

The following diagram shows the results when we apply aexist. In the anti-world, it is possible for wave-motion-ness andsuperposition operation to division by zero to calculate the anti-world.

particle-ness to undergo attribute inversion and further, it ispossible that from this attribute inversion matter and antimatterare inversed. Just as antimatter is used in PET scans, there is astrong possibility that anti-wave motions and anti-null sets exist
in the positive world. If these are found, then this will give birth
to [the physics of] the next 300 years, just as Newton did. If KU
is the state oﬀ using the Mitsuyoshi operator applied to divisionby zero, the result will be as follows.

Figure 37: zero to calculate the anti-world.
The following diagram shows the results when we consider theanti-world through superposition operation of division by zero.

Figure 34: the state of using the Mitsuyoshi operator applied to division by zero.
If we consider KU in terms of the Mitsuyoshi operator, we canmake calculations as in the diagram below.

Figure 38: Anti-null set.
If we think about this concept and consciousness, as well
as free will as a vector from a function-based quantum gate,
in terms of dialogue between the artificial egos and humanbeings., this can be summarized as in the following diagram. At
this time, if functions creating free will are incorporated and incommunications between artificial egos and the evolution and

Figure 35: KU in terms of the Mitsuyoshi operator.

©︎2020 Digital Hollywood University

development processes, meta-functions or super-functions are

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DHU JOURNAL Vol.07 2020

naturally generated, then the experiments proposed by Yuichi Tei

showing the directionality necessary for a judgment as an ego inof comparison with the moral dimension will be possible.

the positive field.

8. Preliminary Experiment
The only specific experiment that has been carried out for thisresearch was the public experiment using the initial artificial
ego, and the only results that were confirmed were the outof-control emotions of the robot. How are the emotions of arobot different from the emotions of a person? Is this what iscalled the consciousness and free will of people? What is thisstrange behavior of this robot now moving out of control? If
this is something that was programmed, then it can’t be called
the robot’s consciousness. These fundamental questions
came from a neuroscientist (Dr. Kenichiro Mogi) who attended

Figure 39: Functions and Consciousness.

the experiment. In this paper, we have disclosed these social
science concepts of“consciousness”,“free will”and“emotion”

The following diagram shows the application of this to a freeas mathematical models and algorithms, and have shown theirconversation-capable artificial ego algorithm.

validity using a physics model and a geometric model.

9. Discussions
Current neural networks are said to derive answers
stochastically, but in reality, they derive concepts of the route toarrive at an answer. However, from the mathematical comparison,
we can see that with the AI approach using existing probability
models, there is an eternal loop and entropy only increases. The
human brain will also repeat loops several times, but after two or
three loops will derive a conclusion; if we call this free will andjudgment, then the fact that the reduction of entropy and phasetransition could be confirmed by the mathematical techniqueused in the TOE hypothesis using the Mitsuyoshi operator andFigure 40: Artificial ego algorithm.

the function-based quantum gates proposed here, has great
meaning. However, change in entropy in the positive field will

7. Mathematical Comparison between AI and AE.

be change in the inversed anti field. Therefore, what should be

First we will compare the AI mathematical model and the AE

done with the anti field? Further, we believe that this will provide

mathematical model.

a large hint as to whether a system of empathy, where thecounterparty is thought about in the context of relationship with

7.1 Comparison of Mathematical Models

the counterparty, can develop as a superego.

Energy physically corresponds to drive and desire. Accordingly,
the states of energy in mathematical models of AI and AE forenergy were compared.

10. Challenges Going Forward

7.2 Results

conversation avatars, of how the free will and desire generated

Research is needed, using actual prototypes and freeAI, as a natural result of its probability model mathematics,

from the feelings and drives arising emergence of the artificial

implies entropy, in the statistical mechanics entropy sense ofego using the function-based quantum gates proposed heremeasure of the microscopic“disorder”of a system; therefore,

are different from those of people. To that end, we are currently

energy is not stable and entropy increases. This happens

building an artificial ego. At this time, as a test corresponding

because, in the transition from a state of equilibrium to anotherto the Turing test for artificial intelligence, if an artificial ego canstate of equilibrium (phase transition), before and after theprovide a problem resolution method for questions that people

transition, system entropy does not decrease but almost always

can’t answer, such as“why is it wrong for people to murder?”increases. Because of this, AI was fated from the start to be

and“can we have both freedom and equality?”or presents a

unable to decide a directionality (vector) that represents a clear

method for resolving the trolley problem that a human could notfree will.

come up with or presents other“design or thought that people
cannot program beforehand”, then we will be able to say thatmachines possess“consciousness”,“free will”,“feelings”, etc.

However, with the mathematical model used with the AE
function-based quantum gate model, the relationship between

11. Conclusions

positive and anti shows the phase transition sum total, so inthe positive field entropy decreases, and conversely, in the anti

In this paper, we proposed the architecture of the Artificial Ego.

field, sum total balance is maintained by increase or decrease

In the architecture, the "free will" and "emotions" of machines

in entropy. This showed that a response (free will) can be given

are represented by a matrix vector. Moreover, we represented©︎2020 Digital Hollywood University

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DHU JOURNAL Vol.07 2020

the "emergence" in "consciousness" as the transition of thematrix vector in the limit after introducing the concept of anti,
which is different from converse and inverse.
Currently, the only specific experiment of the AE was the public
experiment using the initial version of the AE which only has its
own emotion. And there were several criticisms to the ambiguityof definitions about“consciousness”,“free will”and“emotion".
Our proposals above are one of answers to the criticisms.
Further research is necessary to confirm differences between
real human beings and our AEs using free conversation avatars
which were implemented with a prototype of the AE.

Reference Documents[1] Shunji Mitsuyoshi,“Research on Artificial Ego”Luncheon
Seminar at IEEE SMC 2018 (Miyazaki) (2018).
[2] Shigeharu Maeda,“Zusetsu Rinsho Seishin Bunsekigaku”,
Seishin Shobo (1985).
[3] Rosalind W. Picard,“Affective computing”, MIT Press (1997).
[4] Shunjji Mitsuyoshi,“ST ga IT wo Koeru”, Nikkei BP (2002),
pp.27-29.
[5] The University of Tokyo,“Voice Analysis and Measurementof Pathophysiology”, http://www.univ.tokyo/ (refer to July 29,2020).
[6] Shunji Mitsuyoshi, Softbank, “Profile Feature as Seen”
Nature (2016) pp.198-199.
[7] The Japan Society of Mechanical Engineers,“Kankaku Kanjo
To Robot Hito To Kikai No Interaction Eno Chosen”, Kogyo
Chosakai (2008), pp.275-307.

©︎2020 Digital Hollywood University

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