Identifying Emotion in Organizational Settings
Towards Dealing with Morality
Terán Oswaldo
1,2
, Christophe Sibertin-Blanc
1
and Benoit Gaudou
1
1
IRIT, Université Toulouse 1 – Capitole, 2 rue du doyen Gabriel Marty, Toulouse, France
2
Dpto de Investigación de Operaciones and CESIMO, Universidad de Los Andes, La Hechicera, Mérida, Venezuela
Keywords: Modelling Morality, OCC Emotions, MABS, Systems of Organized Action, SocLab.
Abstract: Emotions play an essential role in the behaviour of human beings, either at their sudden occurrence or by
the continuous care to prevent the occurrence of unpleasant ones and to search for the occurrence of pleas-
ant ones. Notably, in any system of collective action, they influence the behaviours of the actors with re-
spect to each others. SocLab is a framework devoted to the study of the functioning of social organizations,
through the agent-based modelling of their structure and the simulation of the processes by which the actors
adjust their behaviours the one to another and so regulate the organization. This position paper shows how
SocLab enables to characterize the configurations of an organization that are likely to arouse different kinds
of social emotions in the actors, in order to cope with the emotional dimension of their behaviours. The case
of a concrete organization is introduced to illustrate this approach and its usefulness for a deeper under-
standing of the functioning of organizations.
1 INTRODUCTION
Social simulation consists in the modelling of social
systems and the study of their behaviour by the per-
formance of computer simulations
(Axelrod, 1997),
including economics, organization, politics, history
or social-ecological systems (see for example the
JASSS on-line journal). The development of this
approach is due to the widening recognition that
social systems feature the characteristics of complex
systems: they display emergent behaviour not pre-
dictable from knowledge of their constituent so that
essential phenomena cannot be caught by analytical
approaches.
Regarding the simulation of social relationships
(Squazzoni, 2012), Sibertin-Blanc et al. (2013a)
proposes a formalisation of a well-experienced theo-
ry of the sociology of organization, the Sociology of
the Organized Action (SOA) (Crozier, 1964; Cro-
zier and Friedberg, 1980) which studies how social
organizations (for example a firm, an association,
any collective or a political setting) are regularized,
as a result of the counterbalancing processes among
the power relationships of the social actors. This
formalization is implemented in the SocLab envi-
ronment (El Gemayel, 2013) which enables to define
the structure of an organization as an instance of a
generic meta-model, to study its structural properties
in an analytical way, to explore the space of its pos-
sible configurations (and so to discover its Pareto
optima, Nash equilibriums, structural conflicts and
so on), and to compute by simulation how it is plau-
sible that each actor behaves with regard to others
within this organizational context. As far as one
agrees with the fundaments of SOA, this platform
looks like a tool for organizational diagnoses, the
analysis of scenarios regarding possible evolutions
of an organization or the study of phenomena occur-
ring within virtual organizations featuring particular
characteristics.
According to the SOA, the behaviour of each ac-
tor is strategic while being framed by a bounded
rationality. In this approach, the interaction context
defines a social game, where each actor adjusts his
behaviour with regard to others in order, as a meta-
objective, to obtain a satisfying level of capability to
reach his goals. The aim of a social game is to find
stationary states, i.e., configurations where actors no
longer modify their behaviour because each one sat-
isfies himself with the level of capability he obtains
from the current state of the game, so that the organ-
ization is in a sustainable regularized configuration.
The SocLab framework has been applied to the
study of concrete organizations (see e.g. Sibertin et
al., 2006; Adreit et al., 2010; El Germayel et al.,
2011; Sibertin et al., 2013a) on the basis of sociolog-
284
Oswaldo T., Sibertin-Blanc C. and Gaudou B..
Identifying Emotion in Organizational Settings - Towards Dealing with Morality.
DOI: 10.5220/0004919402840292
In Proceedings of the 6th International Conference on Agents and Artificial Intelligence (ICAART-2014), pages 284-292
ISBN: 978-989-758-016-1
Copyright
c
2014 SCITEPRESS (Science and Technology Publications, Lda.)
ical inquiries. However in some cases, the simula-
tion algorithm that makes actors to play the social
game (Sibertin et al., 2013b) provides results about
the behaviour of some actors that do not accurately
match the field observations.
This gap between the observed and computed
behaviours can be ascribed to the fact that SocLab
neglects emotions. However, it is well know that
emotions contribute to the regulation of social actors'
behaviours together with phenomena such as mime-
sis (Selten et Ostmann, 2001) or reputation and trust
(Giardini et al., 2013). Indeed, social behaviours are
not so much driven by abstract reasoning than by
complex feelings that are produced by the interac-
tion context and perceived by the partners. Emotions
contribute to the regulation of behaviours that
emerges in human groups from the mutual adapta-
tion of each one’s behaviour to behaviour of others.
Emotion regulation processes are important as
they enlist emotion to support adaptive, organized
behavioral strategies(Clark, 1992).
Thus, in order to improve the verisimilitude of
the actors’ behaviours computed by the simulation
algorithm, and so the reliability of the provided re-
sults, the SocLab platform must cope with social
emotions. The first step in this way is to characterize
the configurations of an organization that are able to
trigger emotions in an actor and to further question
simulation results that reveal to be highly prone to
launch emotions. Such information could be very
useful from a sociological point of view to confirm
or not the stability of an organization. In particular,
it is likely that an actor with negative emotions
which, in addition, is endowed with a significant
power, will seek to make the structure of the organi-
zation to evolve toward a social game whose rules
are more favourable for him.
The further step is to integrate emotions into the
algorithm that implements the actors' decision-
making processes, so that simulations yield organi-
zational configurations that take into account strate-
gic emotions. To this end, actors must seek not only
getting the means to achieve their own goals but also
preventing (promoting) of the occurrence of config-
urations able to arouse negative (positive) emotions.
The remaining of the paper is structured as fol-
lows. Emotions are understood in many ways and
we first have to define what kinds of emotions we
consider and how they are characterized. We refer to
this end to the well-known Ortony, Clore and Col-
lins (Ortony et al., 1988) model that is presented in
section 2. Section 3 layouts the SocLab modelling of
organizations and the actors' decision process in
order to introduce the variables which characterize
social configurations. Then, we associate to each
kind of emotion indexes which values characterize
configurations likely to trigger this emotion in cer-
tain actors. The fourth section applies this frame-
work to a concrete system of organized action which
is somehow problematic. After a short presentation
of this organization and an overview of its SocLab
model (all relevant details are given in Terán et al.,
2013
), we give the values of the indexes for the con-
figuration resulting from simulations and their inter-
pretation in terms of actors' emotion.
2 ORTONY THEORY OF
EMOTIONS
We use the theory of Ortony, Clore and Collins (Or-
tony et al., 1988) (OCC) for the characterisation of
the various kinds of emotions because: (1) it is well-
funded and recognized as a standard in computer
science, notably in MABS; and (2) it deals with
most social emotions we have to consider.
Figure 1: Ortony et al. (2000, pp 30) classification of emo-
tions.
Following OCC, emotions are linked to events, to
actions of people (oneself or other), or to objects.
The linked item might be actual or prospective, and
an emotion might have a desirable or undesirable
character to the extent it might affect the achieve-
ment or not of a goal, comply with or violate a moral
norm, or be associated with a liked or disliked ob-
ject. Emotions are then classified in a tree structure
(see Fig. 1), as follows: (1) in case the linked ele-
ment is an event that affects the achievement of a
goal, the outcome of the event is appraised either as
IdentifyingEmotioninOrganizationalSettings-TowardsDealingwithMorality
285
desirable or as undesirable, and the actor feels either
pleased or displeased, correspondingly; (2) in case
the linked element is an action that complies or not
with a behavioural norm, the actor appraises the ac-
tion either as praiseworthy or blameworthy, and his
reaction will be either approval or disapproval; (3) in
case the linked element is an object, the actor ap-
praises the object either as appealing or unappealing,
and so he will either likes or dislikes it. In SocLab
only the two first kinds of emotions appear: goal-
based (e.g. related with properties of a configuration
whose occurrence is an event), and norm-based (e.g.
regarding the behavior of one actor toward another
one). This will be better explained in section 3.1
3 IDENTIFYING EMOTIONS
IN SocLab
To enable the modelling of social relationships be-
tween the actors of organizations, SocLab proposes
a meta-model that catches the common concepts and
properties of social organizations and is instantiated
on specific cases as models of concrete or virtual
social organizations or Systems of Organised Action
(Crozier, 1964; Crozier and Friedberg, 1980). Ac-
cordingly, the model of the structure of an organiza-
tion is composed of instances of actors and relations
that are linked by the control and depend associa-
tions.
Figure 2: The core of the meta-model of the structure of
Systems of Organized Action.
Figure 2 shows the meta-model of organizations'
structures, as a UML class diagram. A relation is
founded on an organization’s resource, or a set of
related resources, and it is controlled by a single
actor. Resources are material or cognitive (factual or
procedural believes or expectations) elements re-
quired to achieve some intended actions, so that their
availability is necessary for some actors. The state
attribute of a relation represents the behaviour of the
controller actor with regard to the availability of the
resource for the ones who needs it. Its range of value
SB goes from the least cooperative behaviours of the
controller preventing the access to the resource to
the most cooperative behaviours favouring this ac-
cess, while the zero value stands for neutral behav-
iours.
The stake attribute of the dependence of an actor
on a relation corresponds to the actor's need of the
relation to reach its own goal, on a scale:
null = 0, negligible = 1,… ,significant = 5,… , critical = 10.
The effect function evaluates how much the state
of the relation makes the resource available to the
actor, so that effect
r
: A x SB
r
---> [-10, 10] has
values in:
worst access = -10, ..., neutral = 0, ...,optimal access =10.
In addition, actors may have solidarities the ones
with regard to others, defined by as function solidar-
ity(a, b) ---> [1, -1] where negative values corre-
sponds to hostilities and positive values to effective
friendships.
Defining the state, or configuration, of an organ-
ization as the vector of all relations states, each state
of the organization determines on the one hand how
much each actor has the means he needs to achieve
his goals, defined as:
satisfaction(a, s) =
c
A
r
R
solidarity(a, c)*
stake(c, r) * effect
r
(c, s
r
)
and on the other hand how much he contributes to
the satisfactions of each other actor, defined as:
influence(a,b,s) =
r
R; a controls r
c
A
solidarity(b,c)* stake(c, r) * effect
r
(c, s
r
).
This interaction context defines a social game,
where each actor seeks, as a meta-objective, to ob-
tain from others enough satisfaction to reach its
goals and, to this end, adjusts the state of the rela-
tions he controls. Doing so, it modifies the value of
its influence and therefore the satisfaction of actors
who depend on the relations it controls
.
The aim of a social game is to reach a stationary
state: there, actors do no longer change the state of
the relations they control, because every one accepts
his level of satisfaction provided by the current state
of the game, so that the organization is in a regular-
ised configuration.
The actors' strategic attitude is framed by a
bounded rationality (Simon, 1982). The simulation
module of SocLab makes the actors to play the so-
cial game (El Gemayel et al., 2011; Sibertin et al.,
2013b). The model of the actors' rationality is im-
plemented as a process of trial and error based on a
self-learning rules system. Each actor manages a
variable that corresponds to his ambition, and the
game ends when the satisfaction of every actor ex-
ceeds his ambition.
To sum up, each simulation run yields a regularised
configuration which associates to each actor numeri-
ICAART2014-InternationalConferenceonAgentsandArtificialIntelligence
286
cal values of its satisfaction and its influence, and
these values may be used to determine whether this
configuration is able to arouse a kind of emotion.
3.1 Indexes of Emotions in SocLab
Table 1 shows the emotions a SocLab actor is likely
to feel in a given configuration of the organization.
Table 1: Emotions experienced by an actor in SocLab.
Power (influence) exercised by
Self Other The Whole organization
Satisfaction Received by
Self
gratificat
/remorse
gratitude
/Anger
joy/distress
Other
pride
/guilt
admirat/
reproach
If pleased/displeased about
° desirable event:
happy-for/resentment
—-----------------------------------------------
° undesirable event:
gloating/pity
The
Whole
pride/
shame
admirat/
reproach
As above
On one hand, the OCC norm-based emotions are
associated with the action done by agents, let us say
A, what in SocLab is an individual actor, A itself,
another actor, the whole organisation (the whole set
of actors, including A) or all others (all actors ex-
cluding A). On other hand, the goal-based emotions
are based on configurations related with the
achievement of a goal. An OCC event is understood
in SocLab as a configuration where the actor reaches
in some degree its aim. The event is given by the
configuration and properties of the game, including
those of the actors. For clarity we will prefer to talk
about the configuration rather than about an event.
The occurrence and intensity of each emotion is
identified by an index which is defined on the basis
of a proportion, or a percentage. The index is a com-
parison between what is actually done (e.g., the in-
fluence given by the actor) and what could be done
(e.g., the potential for giving). Indeed, a social actor
“appraises” the situation in the context of the possi-
bilities available for it. The emotional interpretation
of the values of each index depends on the very na-
ture of the organization under consideration and of
individual traits of the actor A. Globally, considering
as an example the Joy/Distress emotions, one could
consider that Joy appears above 70% and distress
under 50%.
These indexes are not variables used by the
agent in its decision making process. They are based
on the essential properties of configurations, i.e.
what is given (Influence or Inf) from A to B, or in
what is received (Satisfaction or Sat) by A from B,
where A and B may be: a particular actor, the whole
organisation or all the other actors, as shown in Ta-
ble 1. For instance, we will call minSat(A) (resp.
maxSat(A)) the minimal (resp. maximal) Satisfac-
tion A can receive from the whole. The same stands
for minInf(A) and maxInf(A). Similarly, Sat(A, s)
(resp. Inf(A, s)) stands for the Satisfaction (resp.
Influence) of A at configuration s.
1. Well-being emotions: Joy/Distress
The OCC model defines joy (distress) as: to be
pleased (displeased) about the occurrence of a desir-
able (undesirable) event, or the (regulated) configu-
ration resulting from such an occurrence. In So-
cLab, the joy/distress of an actor A is defined as:
Joy(A,s) = (Sat(A,s) - minSat(A)) / (maxSat(A) -
minSat(A))
2. Gratification/Remorse
OCC defines gratification (remorse) as being
pleased (displeased) about a desirable (undesirable)
event or situation that results from oneself action
and thus entails the approving (disapproving) of
one's own praiseworthy (blameworthy) action. Thus:
Gratif(A, s) = (Inf(A, A, s) – minInf(A, A)) / (max-
Inf(A ,A) - minInf(A,A)
).
3. Pride/Guilt and Pride/Shame
An actor could feel prideful (guilty or shameful)
when he approves (disapproves) his praiseworthy
(blameworthy) action regarding its effect on another
or on the whole. Thus, Pride (Guilt) of A with regard
to B is:
Pride(A, B, s) = (Inf(A, B, s) – minInf (A, B)) /
(maxInf (A, B) - minInf (A, B)).
Replacing B by O (all the others) we have the
Pride (Shame) of an actor A with regard to all oth-
ers.
Similarly, the Pride (Shame) of A with regard to
the whole organization is defined as:
Pride(A, W, s) = (Inf(A, s) - minInf(A)) / (maxInf(A)
- minInf(A)).
4. Gratitude/Anger.
The OCC model defines gratitude (anger) as to be
pleased (displeased) about the consequences for
oneself of another's praiseworthy (blameworthy)
action. Thus gratitude (anger) is similar to gratifica-
tion (remorse), but it regards what is given by the
other instead of what is given by oneself. We define
IdentifyingEmotioninOrganizationalSettings-TowardsDealingwithMorality
287
the Gratitude (Anger) of A towards B as:
Gratitude(A, B, s) = (Inf(B, A, s) – minInf(B,A)) /
(maxInf(B ,A) – minInf(B,A)).
5. Admiration/Reproach
Admiration (reproach) is related to approving (dis-
approving) some other's praiseworthy (blamewor-
thy) action, evaluated wrt the consequences for an-
other actor B, for all others, or for the whole organi-
zation. More precisely, Actor A evaluates the influ-
ence given by actor B considering its consequences
for C, in accordance to the solidarity A feels towards
C. This can happen either because A perceives the
consequence for C of B’s action, or the feeling of B
towards C (sharing of emotions). Thus, the Admira-
tion (Reproach) of A towards B, given the A's soli-
darity towards C, is:
Admiration(A,B,C,s) = Gratitude(C,B,s) * Solidarity(A,C)
The sign of Solidarity(A, C) determines whether A
feels Admiration (positive) or Reproach (negative)
towards B.
6. Happy-for/resentment, and Gloating/pity
These emotions appear when the actor perceives
what is happening for another particular actor as a
consequence of a configuration resulting from col-
lective action. Example: an actor B is getting a low
capacity while it is giving a lot; this means that he is
collaborative and expects the others to be so towards
him, and the low collaboration from others toward
him is unjust. Under this situation, if an actor A has
negative (positive) solidarity towards actor B, then
A feels pleased (displeased) by what is happening to
B, and so A would feel gloating (pity) in the follow-
ing proportion:
Pity (A, B, W, s) = Abs[Joy (B, W, s) – Pride (B, W, s)]/
Joy (B, W, s) * Sol (A, B);
Notice that (Joy(B, W, s) - Pride(B, W, s)) is nega-
tive (undesirable). Pity (gloating) occurs if solidarity
is positive (negative). When (Joy(B, W, s) - Pride(B,
W, s)) is positive (desirable), the same equation de-
fines
Happy-for/resentment.
4 THE CASE
The model of a concrete team is introduced to ex-
emplify how emotions and morality can be identified
in SocLab, and to illustrate how such identification
can help in auditing organisations or designing poli-
cies for promoting collaboration. The team is in
charge of designing a methodology for Institutional
Planning in the Public Sector (we will call it Team
for Designing a Planning-Methodology, or TDPM).
The model has been developed in interaction with
persons who are or have been involved in the TDPM
team, with whom also the simulation results have
been shared and discussed (a precise description of
the TDPM's model is given in (Terán et al., 2013))
.
TDPM is part of a Public Foundation entrusted
with the investigation and development of socially
pertinent free technologies, which in turn is part of
the Ministry for Science and Technology of a
LatinAmerican country. That Public Foundation has
four departmental units for its basic activities, and a
Management Unit. The basic units are:
Pertinence Unit: advises other units about the
relevance of technologies.
Development Unit: produces the tools for the
methodologies.
Research Unit: designs free technologies meth-
odologies, organisational forms and tools.
Technological Spreading Unit: spreads the use
of the methodology.
4.1 The TDPM Team
The TDPM's model includes seven actors coming
from all the five units of the Public Foundation (an
actor can correspond to several similar concrete
member of an organization): two actors from the
Research Unit, two actors from the Development
Unit, and one from each of the three other units. The
work process the TDPM follows the cycle shown in
Fig. 3. Each actors of the team has some duty and
controls some relations, as explained below:
Director. It controls the relations: controlWork
and materialSuport. The first one consists in work
report and evaluation mechanisms, and the sec-
ond one on all material assistance.
researcherS. It designs the planning methodolo-
gy, and specifies the requirements of the tools. It
controls the relation researchMethS.
researcherO. It operatively helps the Research-
erS. It controls the relation researhMethO.
developerS. It develops software tools, and so
controls the relation develToolS.
developerO. It helps the developerS actor opera-
tively, developing particular functionalities of the
software, controlling the relation develToolO.
pertAdviserS. It is responsible for advising the
rest of the team about the social pertinence of the
methodology, controlling the relation pertinence.
techSpreaderO. It is responsible for technological
spread, for promoting the use of the methodology,
controlling the relation techSpread.
ICAART2014-InternationalConferenceonAgentsandArtificialIntelligence
288
Figure 3: Activities of the team developing the planning
methodology. It completes a cycle begging by identifying
requirements of the society, and finishing with spreading
the product (methodology) into the society.
The two following attitudes are found:
some actors of the team are highly engaged, crea-
tive, and thus their work is key for the team;
other members of the team are weakly engaged,
distanced, and their work is little productive and
slightly supports the TDPM's aims.
In the TDPM team, the actors pertAdviserS, re-
searcherS and developerS reveal to be highly en-
gaged; while the other four actors are distanced at
different degrees.
4.2 Results
Table 2 shows the distribution of influences and
satisfactions at the regularised configuration result-
ing from simulations. Table 3 gives the intensities of
Joy, Pride, Gratification and Gratitude felt by the
actors at this configuration. For Gratitude particular
cases are presented, indicating towards whom the
actor feels such an emotion. The other emotions,
namely Admiration/Reproach, Happy-for/ Resent-
ment and Gloating/Pity, do not appear in the present
model because there are not significant solidarities
between actors.
From Table 3 we see that all actors have a good
level of Joy and Gratification. In particular, re-
searchO has the minimal value of Joy, while per-
tAdviserS has the maximal one.
An interesting result appears when we compare the
values of Pride to the Whole (Pride_W) and Pride to
others (Pride_O). Pride to the whole is high for all
actors but in some cases Pride to others is low. This
means that some actors give a lot to themselves but
little to others. The worst case is that of tech-
SpreaderO, followed by developerO (0.29 and 36.3,
respectively). The techSpreaderO case is critical and
should strongly affect the performance of the team.
Also the Director is not very much engaged
(Pride_O is only
52.7%), somewhat affecting the
performance of the team.
This case illustrates how the level of moral emo-
tions is correlated with the level of engagement of
the actors, and could help in defining policies to
improve actors’ engagement and so the organisa-
tion's performances. In particular, actions aiming at
favouring (in some actors) pride to all the others
could be beneficial. Afterwards, those policies can
be improved from careful feedback about the gener-
ated changes in the actors’ engagement and emo-
tions. In the long term, the promotion of appropriate
emotions would be aimed at establishing desirable
organisational norms.
5 RELATED WORK
Different formalizations of OCC can be found in the
literature, see for instance Steunebrink et al. (2012)
or Adams (2010). These formalizations represent
formal descriptions of the qualitative aspects of
emotions (or conditions to happen), which indicates
when an emotion is triggered. On the other hand,
quantitative aspects of emotions (e.g., emotion in-
tensity) addressed in the present paper has received
scarce treatment. One work in this area is offered by
Steunebrink et al. (2008).
OCC does not specify in detail how to deal with
the quantitative aspect of emotions, apart from men-
tioning some variables on which emotions depend,
and giving some hints about how to manage the
quantitative aspect of emotions, by using the varia-
bles potential, threshold and intensity. Intensity is
defined as the difference between potential and
threshold (see Steunebrink et al.; 2008, p. 3). For
instance, the potential (and thus the intensity) of
some emotions related with the action of agents is
affected by the variables degree of praiseworthiness
(blameworthiness), degree of desirability and degree
of effort. In particular, the effect of these variables
can be considered linear: potential is a weighted sum
of the named variables. In general, in OCC, potential
is defined in terms of the Central Intensity Variables
and the Local Variables.
Similarly, only hints are given in OCC about
how to define the qualitative value of the threshold
of emotions: they might be determined in terms of
Global Variables which are related with the “mood”
(a kind of disposition) of the individual; e.g., if the
individual general feeling or “mood” becomes more
agreeable than in a previous state, then the threshold
of negative emotions would be increased in relation
to the values at that previous state. Among the OCC
Global Variables, we have: sense of reality, and the
IdentifyingEmotioninOrganizationalSettings-TowardsDealingwithMorality
289
subjective importance of a situation.
Alike OCC, Steunebrink et al. (2008) does not
study the variables affecting the intensity of emo-
tions, but instead concentrates on the integration of
qualitative aspects into the logical formalization of
OCC. For this, they need to describe not only the
initial value of an emotion, but also how its value
changes over time, decreasing until disappearing or
being negligible, what is represented via an inverse
sigmoid function.
5.1 Our Approach
In SocLab the interest is in the regularized configu-
ration resulting from simulation, where certain prop-
erties occurs according to the state of each relation
and the values of each actor’s Influence (what is
given) and Satisfaction (what is got). In this sense,
we can say that the resulting intensities of the emo-
tions are regulated emotional states, which can be
related with measures of central tendency (e.g.,
means, medians, or modes). Thus, the interest is not
in simulating the dynamics of emotions as in
Steunebrinck et al. (2008); i.e., the aim is not to
simulate the conditions in which emotions occur, or
their initial and subsequent values over time.
In this sense, we take a different approach from
that of Steunebrinck et al. (2008). The determination
of emotions rests in relational properties of the ac-
tors, associated with the actors’ aims and morality;
that is, emotions are defined in terms of what an
actor gives and what an actor receives. It is supposed
that the conditions for the emotion are fulfilled at the
regulated state, and so we do not need to test them.
However, the intensity of an emotion is not nec-
essarily positive, as it might also be either null or
negative. As emotions of interest in SocLab are de-
fined in pairs (e.g., pride vs. shame), if the intensity
is positive, then the positive component happens,
otherwise the negative component is the case.
Thus, the paper focuses in determining the inten-
sity of each emotion, which for simplicity here is
assumed to be equal to its potential (the threshold is
0). However, alike OCC and Steunebrink et al.
Table 2: The exerted influence (in columns) and obtained satisfaction (in lines) by the actors of the TDPM team at the con-
figuration resulting from simulations. The last column shows the percentage of satisfaction each actor receives from all
actors in relation to what it can get. Similarly, the last two lines show the actual percentage of influence each actor gives to
the Whole and to all the Others, in relation to what it can give.
Director
researcherS
researcherO
developerS
developerO
pertAdviserS
techSpreaderO
Satisfaction
%SatifWhole
Director 29.8 15 0.8 15 0 6.9 -5.9 61.5 89.7
researcherS 2.3 40 1.5 7.2 -0.8 6.9 -5.9 51.1 86
researcherO -0.4 -4 14.8 0.9 -0.2 0 0 11.1 71
developerS -1.8 25 1.5 36 -2.3 0 0 58 85
developerO -2.7 4 0.3 18 19 0 0 38 89
pertAdviserS 2.7 20 0 18 -0.4 24.3 -4.9 59.5 90
techSpreaderO -0.6 0 0 0 0 0 45 43.9 72
Influence 29.2 100 18.8 95.1 15.4 38.1 28 46.3
% Inf. To Whole 78.9 100 95.6 100 93.1 99.5 100
%Inf. To Others 52.8 100 59.2 100 36.3 99.3 0.3
Table 3: Intensity of emotions felt by the actors of the TDPM team in the configuration described in Table 2.
For Gratitude only examples are given.
Joy Gratif Pride_O Pride_W Gratitude Towards
Director
89.7 97.68 52.7 78.9 20.5 techSpreaderO
researcherS
85.5 100 100.0 100 99 techSpread.
researcherO
71.3 97 59.2 95.6 99.3 perAdviserS
developerS
84.7 95 100.0 100 100 researchS
developerO
89.4 94.8 36.3 93.1 95 developerS
pertAdviserS
90.2 99.6 99.29 99.5 52 direcctor
techSpreaderO
72 99.6 0.29 99.5 - developerO
ICAART2014-InternationalConferenceonAgentsandArtificialIntelligence
290
(2008), we do not concentrate on specifying either
the variables determining the intensity or the varia-
bles indicating the threshold of the emotions. For
instance, for the case of Pride and Gratification, the
emotion intensity results from evaluating what the
actor is given to itself or to others, in relation to
what it can give. This might be seen as a conse-
quence or as measure of the actor’s morality. On the
other hand, the index of Joy focuses on what the
actor is receiving, in comparison to what it can re-
ceive, what measures the degree of achievement of
the actor goals.
It is important to notice the introduction of the
notion of solidarity, which is missing in Steunebrink
et al. as in OCC. This allows differentiating a diver-
sity of relationships between an actor and the others.
For instance, Admiration of actor A towards actor B
might happen not only because the action of B is of
direct interest for A, but also because it is of interest
for an actor C to whom A feels solidarity. This per-
mits to considerably increase the richness of the de-
scribed social relationships.
6 CONCLUSIONS
The paper show how emotions can be identified in
SocLab models of organizations by the definition of
indexes that evaluates the potential arousal of moral
emotions such as pride and guilt. Considering a con-
crete organization, it has illustrated how the
knowledge of the actors' emotional states improves
the understanding of the functioning of an organiza-
tion.
Considering the fact that social actors try to pre-
vent bad emotions and reach good ones, this opens
the way for the simulation algorithm to cope with
the emotions of actors. In the case study, the indexes
show low levels of moral emotions for some actors,
and thus, e.g., help in a diagnosis of the organisation
in order to design policies to improve the level of
engagement of those lowly engaged actors. These
policies would promote desirable norms of behav-
iour, taking into account moral emotions as incen-
tive/punishment in settling and strengthen those
norms, in order to increase collaboration in the or-
ganisation. This issue will be addressed in further
research.
ACKNOWLEDGEMENTS
This work has been supported by the French ANR
project EMOTES “Emotions in social interaction:
Theoretical and Empirical Studies”, contract No.
ANR-11-EMCO 004 03.
REFERENCES
Adam Carole, 2007. Emotions: From Psychological Theo-
ries to Logical Formalization and Implementation in a
BDI agent. Ph.D. Thesis, Université de Toulouse,
Toulouse, France. 216 p.
Andreit, F., Roggero, P., Sibertin-Blanc, C. and Vautier,
C., 2011. Using SocLab for a Rigorous Assessment of
the Social Feasibility of Agricultural Policies. Interna-
tional Journal of Agricultural and Environmental In-
formation Systems 2(2), p. 1-20.
Axelrod, R., 1997. Advancing the Art of Simulation in the
Social Sciences. In R. Conte, R. Hegselmann and P.
Terna (Eds), Simulating Social Phenomena (pp. 21-
40). Lecture Notes in Economics and Mathematical
System. Springler-Verlag.
Clark M, 1992. Emotion and social behavior (Ed), Sage
Publications.
Clore, Gerald L. and A. Ortony, 2000. Cognition in emo-
tion: Always, sometimes, or never. In Cognitive neu-
roscience of emotion, edited by Richard D. Lane, and
Lynn Nadel, 24-61. New York: Oxford University
Press.
Crozier, M., 1964. The Bureaucratic Phenomenon. Chica-
go: University of Chicago Press.
Crozier M. and E. Friedberg, 1980. Actors and Systems:
The Politics of Collective Action. The University of
Chicago Press.
El-Gemayel, J., Chapron, P., Sibertin-Blanc, C (2011).
Impact of Tenacity upon the Behaviors of Social Ac-
tors. Advances in Practical Multi-Agent Systems, Quan
Bai and Naoki Fukuta (Eds), Studies in Computational
Intelligence 325, p. 287-306, Springer.
El-Gemayel J., 2013. Modèles de la rationalité des acteurs
sociaux. PhD of the Toulouse University, France.
Giardini F., R. Conte, and M. Paolucci, 2013. Reputation.
Chapitre 15 In Simulating Social Complexity - A
Handbook, Bruce Edmonds and Ruth Meyer Editors.
Springer.
Ortony, A., Clore, G., and A. Collins, 1988. The cognitive
structure of emotions. New York: Cambridge Univer-
sity Press.
Selten, R., Ostmann, A, 2001. Imitation Equilibrium. Ho-
mo Oeconomicus 43, 111–149.
Sibertin-Blanc, C., Amblard, F. and Mailliard, M. (2006).
A coordination framework based on the Sociology of
Organized Action. In Coordination, Organizations,
Institutions and Norms in Multi-Agent Systems, O.
Boissier, J. Padget, V. Dignum and G. Lindemann
(Eds), LNAI, 3913, 3-17. Springer.
Sibertin-Blanc, C. Roggero, F. Adreit, B. Baldet, P.
IdentifyingEmotioninOrganizationalSettings-TowardsDealingwithMorality
291
Chapron, J. El Gemayel, M. Mailliard, and S. Sandri,
2013a SocLab: A Framework for the Modeling,
Simulation and Analysis of Power in Social Organiza-
tions, Journal of Artificial Societies and Social Simu-
lation (JASSS), 16(4). http://jasss.soc.surrey.ac.uk/
Sibertin-Blanc, C. and El Gemayel J. 2013b. Boundedly
Rational Agents Playing the Social Actors Game -
How to reach cooperation. Proceeding of IEEE Intelli-
gent Agent Technology, V. Raghavan (Ed.), 17-20
nov. 2013, Atlanta.
Simon, H. A., 1982. Models of bounded rationality: Be-
havioral economics and business organization. The
MIT Press.
Squazzoni, F., 2012. Agent-Based Computational Sociol-
ogy, Wiley.
Staller A. and P. Petta, 2001. Introducing Emotions into
the Computational Study of Social Norms: A First
Evaluation, Journal of Artificial Societies and Social
Simulation vol. 4, no. 1.
Steunebrink, B. R., Dastani, M. M. & Meyer, J-J.Ch.,
2008. A Formal Model of Emotions: Integrating Qual-
itative and Quantitative Aspects. In G. Mali, C.D. Spy-
ropoulos, N. Fakotakis & N. Avouris (Eds.), Proceed-
ings of ECAI'08, pp. 256-260. IOS Press.
Steunebrink, B. R., Dastani, M. M. & Meyer, J.-J.Ch.,
2012. A Formal Model of Emotion Triggers: An Ap-
proach for BDI Agents. Synthese, 185(1):83-129,
Springer.
Terán, O., and Sibertin-Blanc C., 2013. Social Model of a
Team Developing a Planning-Methodology. OpenAbm
http://www.openabm.org/model/3983/version/1/view.
ICAART2014-InternationalConferenceonAgentsandArtificialIntelligence
292