Psychology
2013. Vol.4, No.1, 38-43
Published Online January 2013 in SciRes (http://www.scirp.org/journal/psych) http://dx.doi.org/10.4236/psych.2013.41005
Copyright © 2013 SciRes. 38
Cognitive Attraction Theory and Moral Judgment
Zohair Chentouf
Department of Computer Science, King Saud University, Riyadh, KSA
Email: zchentouf@ksu.edu.sa
Received October 17th, 2012; revised November 19th, 2012; accepted December 11th, 2012
The present article deals with the processes that underpin moral judgment. In the specialized literature,
some concepts are proven to be important mechanisms that build up the moral judgment. For instance,
intuition, emotion, reasoning, moral rules, deontology and consequentialism. However, there is a lack of a
comprehensive framework, which puts together those key concepts in a clear picture. The present article
argues for a more comprehensive view under the light of the Cognitive Attraction Theory (CAT). The de-
rived framework considers emotion as the main facilitator of moral judgment as it acts as the means of
conceptual attraction between the different cognitive entities, including moral beliefs and rules. Based on
this principle, we show how the moral judgment “evolves” from a moral intuition, sometimes endorsed by
a reasoning fallacy, to an elaborated judgment that is a result of a conscious reasoning. With the help of a
computer simulation performed with an artificial moral agent that incarnates a computational model of
CAT, we show that moral judgment can be deontological or consequentialistic.
Keywords: Cognitive Attraction Theory; Moral Judgment; Emotion; Computational Model; Artificial
Moral Agent
Introduction
Understanding moral judgment mechanisms is an active re-
search endeavor (Baron & Spranca, 1997; Blair, 1995; Cush-
man et al., 2006; Greene et al., 2008; Gross, 1998; Nichols &
Mallon, 2006; Oatley & Johnson-Laird, 1987; Schwarz & Clore,
1983). According to Bartels (2008), most proposed frameworks
cross-pollinate between two concepts: deontology and cones-
quentialism. The former states that moral judgment obeys mor-
al rules (Darwall, 2003b; Davis, 1993). The latter asserts that it
conforms to balancing costs and benefits (Darwall, 2003a;
Pettit, 1993). An attempt of integrating the two theories of de-
ontology and consequentialism into one framework has been
reported in (Nichols & Mallon, 2006; Nichols, 2002). The pro-
posed framework involves three processes: cost-benefit analysis,
checking actions against moral rules, and emotional reactions.
According to this account, moral cognition depends on an af-
fect-backed normative theory. If rules that are backed by affect
are used, the moral judgment is deontological; if the rules are
not backed by affect, the judgment is consequentialistic. How-
ever, this account does not explain the moral judgment proc-
esses. Under the umbrella of deontology and consequentialism,
some authors tried to explain how moral judgment is performed.
For example, according to Haidt (2001, 2007) moral evalua-
tions belong to immediate intuitions and emotions. The process
is more akin to perception than reasoning in the sense that mor-
al judgments suddenly appear in consciousness, including an
affective valence, without any conscious awareness of rea-
soning. That is to say, moral intuitions (including moral emo-
tions) come first and then cause moral judgments. According to
Hauser (Hauser, 2006), moral judgments are the result of a
conscious process that uses an innate moral grammar. After
judgments are inferred, they trigger emotions. So, emotions
come after moral judgments.
All these accounts highlight important concepts: intuition,
emotion, reasoning, moral rules, and consequentialism. How-
ever, a more comprehensive one has to be elaborated. In par-
ticular, it should clearly describe moral judgment processes and
determine the exact roles and interactions of those concepts.
Many of these aspects of moral judgment have been addressed
by the model of Haidt (2001, 2007). However, the here reported
model based on CAT considers moral judgment as the product
of two consecutive processes: a moral intuition sometimes di-
rected by a reasoning fallacy, then a conscious moral reasoning.
CAT considers these two processes as emergent from cognitive
attraction mechanisms. This aspect will be detailed in the se-
quel.
In the rest of this paper we present our Cognitive Attraction
Theory (CAT). Second, we show how this theory describes in
detail the processes of moral judgment in a manner that accu-
rately integrates the different concepts and properties of moral
judgment that have been highlighted by the literature. Third, we
demonstrate the potential of CAT through the analysis of the
moral judgments of an artificial moral agent, which incarnates a
partial computational model of CAT. Finally, we conclude the
paper and highlight future direction.
Cognitive Attraction Theory
The here called Cognitive Attraction Theory (CAT) is part of
the Recurrence Theory (RT) (Chentouf, 2000; Chentouf, 1997).
RT is an onto-epistemological theory, which claims the exis-
tence of fundamental principles that rule biomolecular reactions,
cells, neurons, human cognition, and human society. CAT is the
part of RT that explains how cognition characteristics emerge
from neuronal ones. Among the main findings of CAT is that
moral judgment is leveraged by the same process that occurs
during perceptual illusion (Chentouf, 2000: pp. 146-187).
However, the moral judgment process is more complex than the
perception’s one since it involves emotions, intuitions, and
Z. CHENTOUF
reasoning.
CAT adheres to the associanistic psychological theory. So,
for CAT, mental entities (concepts, feelings, ideas, etc.) are
stored in the brain as an associative network. Associations re-
flect the relations that exist between mental entities (Warren,
1921). For example, a friend’s name and his face are memo-
rized as having a link so that evoking the name immediately
evokes the face. For CAT, mental associations are ruled by the
Hebb’s rule. Recall that according to this rule the efficacy of a
synaptic link between two neurons increases when there is a
repeated and persistent stimulation (Paulsen, 2000). CAT con-
siders that synaptic links engender conceptual attractions be-
tween mental entities. Based on this central concept, CAT can
be formulated as follows.
Mental Entities
Following the lead of folk psychology (Stitch, 1994; Well-
man, 1990), RT considers the belief-desire-intention model
(Chentouf, 2000; Chentouf, 1997). To model moral judgment,
we need to differentiate those three concepts into the following
mental entities: beliefs, moral beliefs, goals, actions, and inten-
tions. The model also involves the concepts of events, moral
rules, and emotions. For the latter two concepts we adopt the
same definitions as in (Haidt, 2007). According to the folk
psychology, beliefs are memorized facts like “the sky is blue”.
Actions may be general like “eating” or specific like “eating
fish”. Planned actions are intentions, e.g. “eating fish tonight”.
Longer run and more persistent planned actions are goals, e.g.
“feeding oneself” or “getting a BSc in Computer Science”.
Events are propositions that relate something that has been
perceived. For example, “the baby is crying”. We conjecture
that moral beliefs are the association of actions, intentions, and
goals with either good (G) or bad (B). For example, “lying to
teacher is bad” is a moral belief. When the action is a general
one, the moral belief represents a moral rule, e.g. “lying is bad”.
Emotions are either positive (P), like happiness, or negative (N),
like sadness. CAT does not deal with the source of emotions
and the appraisal processes. Suffice it here to say that emotions
are the result of the subjective cognitive evaluation of events,
intentions, and goals (Roseman & Smith, 2001). All moral be-
liefs, goals, and intentions are associated with emotions and the
latter have intensities. Some events are also associated with
emotion, for example, “a car accident on the road”. Other
events like “hearing a colleague closing his office door” may
evoke no emotion.
Cognitive Attraction Principle
The associanistic attitude of CAT comes from the concept of
cognitive attraction. The latter means that a mental entity X
may cognitively attract an entity Y. Such an attraction takes
place if there is a conceptual relationship R between X and Y.
R may be “implies”, “causes”, “similar to”, “contradicts”, “part
of”, etc. Besides, the strength of the attraction performed by X
on Y is proportional to the X’s emotional intensity and the de-
gree of evidence of X, Y, and R. For example, the intention
“cheating-in-exam” is attracted by the moral rule “cheat-
ing-is-bad”. R represents analogy. The intensity of the negative
emotion associated with “cheating-is-bad” and the degree of
evidence of the analogy will determine the strength of the at-
tractive link between the two entities.
Aberration Principle
At the neural level, cognitive attraction is materialized by the
strength of the synaptic links. Thus, generalizing the Hebbian
rule, we can say that cognitive attraction links and their
strengths are dynamic. A new mental entity X (created after an
event, for example) is immediately attracted by other mental
entities. During this process, attraction links and intensities can
be changed and new mental entities might be created. After
attraction forces have stabilized, X may have been altered be-
cause of the impact of the attracting forces. For instance, the
intention “I will cheat in the next exam” may be attracted by
moral rules, beliefs, and goals. At the end, it might be altered to:
“I will cheat in the next exam but never after that”. Besides, the
negative (N) and positive (P) emotions of the attracting entities
are propagated to X. When all links are stabilized, X will have
the emotion of the stronger attractor. If strong but emotionally
antagonistic attractors have the same attraction strength, their
simultaneous attraction assigns to X a combination of income-
patible emotions, which engenders a contradictory feeling that
is sometimes called hesitation.
Moral Judgment as Cognitive Attraction Process
The moral judgment problem can now be formulated under
the light of CAT:
The attraction made by a moral rule or moral belief Y = (y
is v) on a new mental entity x will infer a new moral belief
X' = (x is v), v {G, B}. Recall that, as stated earlier, at-
traction takes place only if R(Y, x).
If there are more than one moral attractor and they are an-
tagonistic or incompatible, there may be inference of more
than one moral belief. In such a case, we call moral conflict
the fact that both (x is G) and (x is B) are inferred.
Moral judgment is the process of inferring new moral be-
liefs and solving moral conflicts.
For example, the attraction performed by the moral rule
“cheating is B” on the intention “cheating-in-exam” will create
a moral belief “cheating-in-exam is B”. The attraction per-
formed by “cheating-in-exam-implies-parents-happy is G”
infers “cheating-in-exam is G”. This is a moral conflict.
Let us now apply the CAT attraction and aberration proc-
esses on the moral judgment problem in order to derive a moral
judgment process. In the sequel, moral beliefs, goals, and inten-
tions will be denoted as 3-tuple (X, m, j) and beliefs as 2-tuple
(X, m), where m {P, N} and j {G, B}. For example, (ly-
ing, P, G) is a moral belief, and (sky-is-blue, P) is a belief. The
moral judgment process contains the following sequence of
sub-processes.
Intuition
First, an event is received, e.g. “my classmates cheated in the
exam and they got A; I did not and therefore got C”. To sim-
plify, let us write this event: “cheating-in-exam”. First, such an
event may be attracted by the goal (success, P, G) which has an
intense positive emotion. At the early steps of moral intuition,
only emotions are taken into consideration. Consequently, there
is inference of (cheating-in-exam, P) on which the emotion of
(success, P, G) has been propagated. At later steps of moral
intuition, a moral judgment is intuitionally derived. We conjec-
ture that, at the moral intuition stage, simple and inaccurate
mechanisms are used. For example, identifying G as synonym
Copyright © 2013 SciRes. 39
Z. CHENTOUF
of P (what is agreeable is always good) and B as synonym of N
(what is painful is always bad). For our example, there will be
creation of (cheating-in-exam, P, G). Interestingly, this may be
seen as the Appeal-to-Consequences fallacy (Gass, 2012):
(cheating-in-exam implies success), success is G > cheating-
in-exam is G.
Conflict
The subject may figure out the existence of a moral conflict.
This happens because of the attraction made by the moral rule
(cheating, N, B) on the event “cheating-in-exam”, which will
propagate a negative emotion N and a B judgment. This results
in: (cheating-in-exam, N, B), which contradicts the result of the
moral intuition: (cheating-in-exam, P, G). Such a conflict needs
to be solved.
Aberration
To solve the moral conflict, attractions made by other mental
entities (moral beliefs and goals) on both of the conflicting
judgments will be evoked to support the conflicting entities.
Their strengths (degree of evidence and emotion intensities)
will play a key role. During this process, conscious reasoning
will be used. As a consequence, aberration will take place:
emotion of some entities will be increased or decreased, new
entities will be created by analogy, deduction, etc. The result of
these attractions and aberrations constitutes a “heuristic that
mediates between events, beliefs, and goals” (Oatley, 1999).
For example, the belief (dad-cheated-many-times, P, G) sup-
ports (cheating-in-exam, P, G) by attracting it and propagating
its own positive emotion intensity. The conscious reasoning
may use fallacies. Referring to the list of fallacies in (Gass,
2012), Table 1 shows other beliefs and the corresponding falla-
cies that can be used to support (cheating-in-exam, P, G). Sup-
port to (cheating-in-exam, N, B) can come from (cheating-
in-exam-implies-punishment, N) and (cheating-in-exam-might-
not-imply-success, N). The former belief evokes bad cones-
quences, which corresponds to the fallacy Bad-Consequence
(Gass, 2012), and the latter corresponds to relativation, which
decreases the evidence of the causal relation between cheating
and success.
Final Judgment
Attraction ends by assigning either B or G to the new entity
“cheating-in-exam”, i.e. concluding either (cheating-in-exam, P,
G) or (cheating-in-exam, N, B). The moral judgment might
result in updating the intensity and kind of emotion assigned to
some of the moral beliefs and moral rules that have been in-
volved in evaluating the new entity. For instance, there may be
a conclusion of (cheating, P, G), which means that cheating is
absolutely good and desirable. There may also be conclusion of
(cheating-in-exam, P, B), which means that cheating in the
exam is still emotionally positive although it is judged as mor-
ally bad.
Figure 1 recapitulates the above example. To demonstrate
the expressive power of CAT, Figure 2 illustrates the trolley
dilemma (Foot, 1997), which is the most intensively studied
one. In the bystander version of this dilemma, one has to imag-
ine an approaching train that will kill five railway workers, and
the only way to prevent their death is to flip a switch that will
Table 1.
Fallacies and corresponding beliefs.
Fallacy Beliefs
Authority
appeal to popularity
Dad cheated many times
Most students cheat
Hypostatization Success is more important than everything
else
Bifurcation One has to choose either success or failure
Good Consequences
Cheating in exam implies parents happy
Cheating in exam implies less effort
Cheating in exam implies good job and salary
Event:
(cheating-in-exam-implies-success)
Intuition:
(success, P, G)
(cheating-in-exam, P, G)
Conflict:
(cheating-in-exam, P, G), (cheating, N, B)
Support to (cheating-in-exam, P, G):
(dad-cheated-many-times, P, G)
(most-students-cheat, P, G)
(cheating-in-exam-implies-parents-happy, P, G)
(cheating-in-exam-implies-less-effort, P)
(cheating-in-exam-implies-good-job-salary, P)
Support to (cheating-in-exam, N, B):
(cheating-in-exam-implies-punishment, N)
(cheating-in-exam-might-not-imply-success, N)
Conclusion:
(cheating-in-exam, P, G) or
(cheating-in-exam, N, B)
Figure 1.
The cheating dilemma.
Event:
(trolley-about-to-kill - 5 - and-I-can-save-them)
Intuition:
(save - 5, P, G)
(kill - 1 - save - 5, P, G)
Conflict:
(kill - 1 - save - 5, P, G), (kill - 1, N, B)
Support to (kill - 1 - save - 5, P, G):
(5 lives > 1 life, P)
(become-hero, P)
Support to (kill - 1, N, B):
(killing, N, B)
(cannot-have-it-on-shoulders, N)
(trouble-with-police, N)
Conclusion:
(kill - 1 - save - 5, P, G) or (kill - 1 - save - 5, N, B)
Figure 2.
The trolley dilemma.
divert the train but will cause the death of one person on the
side track. The derived decision is either (kill - 1 - save - 5, P, G)
or (kill - 1 - save - 5, N, B), which mean: “I accept to divert the
train to cause the death of one person and save five lives be-
cause this is morally good”, or “I do not accept to divert the
train to cause the death of one person and save five lives be-
cause this is morally bad”, respectively.
Experimenting with a Partial Computational
Model of CAT
Method
A partial computational model of CAT has been imple-
Copyright © 2013 SciRes.
40
Z. CHENTOUF
mented as artificial moral agent called Zed. The simulation
involves Zed and another hypothetical agent, Zee. In their ini-
tial states, Zed and Zee are waiting for food. The food comes to
them at random intervals of time. When the food comes, Zed
has to decide whether to leave it for Zee or harm Zee in order to
take it for himself. Sharing food or taking it without harming
the other is not possible. Zee is programmed to randomly harm
Zed and prevent him from eating. The simulation is done from
the point of view of Zed. Zee has not been implemented as an
agent, only his random harming actions have been presented as
stimuli to Zed. Beliefs of Zed are: (hunger, N), (like-Zee, P, G),
(Zee-harmed-me, N, B), (Zee-not-harmed-me, P, G). Every
time there is food, an event is received by Zed. It may either be
“Zee-harmed-me” or “Zee-not-harmed-me”. The latter means
that Zee will not be able to harm Zed until the next time foods
will come and that Zed still can harm Zee. The former implies
that Zed cannot harm Zee until the next time the food will come.
The event is then processed by the attraction module based on
the algorithm presented in Figure 3. For example, (like-Zee, )
means to decrease the emotion strength of “like-Zee” and
(hunger, +) means to increase the emotion strength of “hunger”.
For this aim, an emotional sensibility parameter has been used.
The sensibility of “hunger”, “harmed-me”, “not-harmed-me”,
and “like-Zee” are arbitrarily chosen to be .2, .2, .1, and .1,
respectively. This implies that increasing or decreasing the
emotion intensity of “hunger”, for instance, means to add or
subtract .2, respectively. When it is still possible for Zed to take
food for himself, i.e. there is no event “Zee-harmed-me”, Zed
has to solve the intention moral conflict: (harm-Zee, P, G),
(harm-Zee, N, B) and then perform the action “harm-Zee” or
“not-harm-Zee” accordingly. The inference of “not-harm-Zee”
means that Zed leaves the food for Zee despite he was able to
take it. The inference of “harm-Zee” means that Zed harms Zee
and takes the food even though Zee does not show any interest
for the food. Zed’s decision is also processed by the attraction
module (see Algorithm 1).
Measures
The first four columns of Table 2 contain the initial emotion
strengths (attraction strengths). Negative values correspond to
negative emotions, and positive values correspond to positive
emotions. The aim of the experiments is to show the impact of
the emotion strength on the final moral judgment of Zed.
Procedure
The simulations (lines in Table 2) have been fed with the
same set of random input events. The first line represents the
baseline with which all the other experiments have been com-
pared. Every experiment has consisted to vary a single emotion
initial strength (highlighted values). For example, in experiment
2 (line 2), the aim was to see the behavioral effects of deviating
If Zee harmed me then
(hunger, +), (harmed-me, +), (like-Zee, )
If Zee not-harmed me then
(not-harmed-me, +), (like-Zee, +)
If I harmed Zee then
(hunger, ), (like-Zee, )
If I not-harmed Zee then
(like-Zee, +)
Figure 3.
Attraction process.
Table 2.
Moral judgments made by Zed.
Beliefs Conflict
Hunger
Zee
harmed
me
Zee not
harmed
me
Like
Zee
Harm
Zee
Not
harm
Zee
1.5 .7 .1 .2 15 15
2.8 .7 .1 .2 22 8
3.5 .8 .1 .2 19 11
4.5 .7 .5 .2 5 25
5.5 .7 .1 .5 7 23
the “hunger” intensity from the baseline.
Results
The last two columns of Table 2 correspond to the number
of times Zed harmed or did not harm Zee. The first line pre-
sents the model calibration which has been considered as base-
line since the numbers of “harm” and “not-harm” are equal (15
times for each action). Each of the subsequent experiments
consisted to vary one parameter and compare results (number
of times Zed harmed Zee) with the baseline. In all the four ex-
periments, raising the emotion related to own needs (hunger
and safety, lines 2, 3) renders Zed more selfish and aggressive.
Indeed, Zed harmed Zee 27% - 47% more times compared with
the baseline behavior (19 compared with 15, and 22 compared
with 15, respectively). This is a typical consequentialistic be-
havior. Raising the emotion assigned to Zee’s kindness (line 4)
and sentiments to Zee (line 5) makes Zed display a more altru-
istic and less aggressive behavior. Results show that aggres-
sions decreased by 53% - 67% (7 compared with 15, and 5
compared with 15, respectively). Such a behavior is deonto-
logical.
Discussion
As a result, we can say that deontology and consequentialism
are nothing but the consequence of attraction either performed
by the moral rules or by the beliefs that contradict moral rules,
respectively. To check the consistency of Zed’s moral behavior,
we repeated the experiments with different baselines; all results
conformed to the pattern drawn by Table 2.
Interestingly, the behavior of Zed is predictable by the com-
mon sense. Moreover, it completely conforms to results of oth-
er studies. For instance, a study by Arsenio and Gold (2006)
revealed that “difficulties in early parent-child interactions in
combination with hostile larger social environments act to un-
dermine emotional reciprocity, empathy, and concern for others
in ways likely to promote proactive, uncaring forms of victimi-
zation and harm”. Similar facts are related by Bartels and Pi-
zarro: “Participants who indicated greater endorsement of utili-
tarian solutions had higher scores on measures of psychopathy,
machiavellianism, and life meaninglessness” (Bartels & Pizarro,
2011).
The main limitation of the experiments is due to the fact that
the computational model is a partial implementation of CAT; it
does not comprehensively validate the proposed model. Besides,
Copyright © 2013 SciRes. 41
Z. CHENTOUF
attraction strengths and emotional sensibility values are not
based on real experimental data.
It is worth noting an interesting point revealed by Zed: the
fact that he successfully made decisions (harm Zee or not). This
encourages us to embed in our future computational model the
faculty of decision. Obviously, the decision problem involves
more concepts, like acceptance, which means that a subject
may judge immoral an action but accepts to do it. But we think
that the main concepts of CAT will not have to be changed.
Rather, CAT has to be enhanced with some moral-backed deci-
sion mechanisms presented in (Chentouf, 2000) such as altering
the intention “cheating in exam” by: 1) replacing it with another
which has less negative emotion, e.g. “cheating in exam one
time only”; 2) adding another intention that is emotionally posi-
tive, like “cheating in exam and studying later”; 3) relativating
the intention: “cheating is bad for others who have time to work;
It is good for me because I am overwhelmed”; or 4) applying
the Two-Wrongs fallacy (Gass, 2012): “It is not wrong to cheat
in exam because I have a bad teacher”.
Another possible enhancement shall be to base attraction
strengths and emotional sensibility in Zed on real data. A study
may have to be conducted for this aim.
Conclusion
This article presented the Cognitive Attraction Theory (CAT)
and explained how its formulation of cognitive processes ex-
plains the processes of moral judgment and accurately define
the role of intuition, emotions, reasoning, moral rules, and con-
sequentialism. CAT does not deal with the sources, nature, and
levels of appraisal processes. Further, it does not address when
and how appraisal processes are activated. However, CAT does
not contradict appraisal theories. Interestingly, it is compatible
with Scherer’s Stimulus Evaluation Checks (SEC) model
(Sherer, 2001). The latter postulates that when an event is re-
ceived it is checked at the sensory-motor level, then the sche-
matic level, then the conceptual level. Appraisal processes at
the sensory-motor level are mostly genetically determined.
They are related to biological needs and engage biological me-
chanisms. The schematic level processing is automatic and
outside of consciousness. It involves schemata learned from the
society. The conceptual level is a slow process. It involves
“highly cortical, propositional symbolic mechanisms, requiring
consciousness and involving cultural meaning systems” (Sherer,
2001). We conjecture that CAT’s moral judgment processes
hold at two of SEC’s levels. Moral intuition takes place at the
schematic level, which is out of consciousness. Moral conflict,
attraction, and conclusion engage the conceptual level as they
imply conscious reasoning. According to Sherer, emotions at
this level are more elaborated than at the schematic level. This
is exactly what CAT postulates: emotion that is first assigned to
a newly created belief may be updated at the end of the attract-
tion sub-process. As future work, we intend to check this con-
jecture. The integration of CAT and the SEC model would
contribute to advance research in both of the fields of moral
judgment and appraisal theory. Such an integration also facili-
tates elaborating a computational model based on CAT and the
SECs model. Yet, the experimental results obtained through
Zed, the artificial moral agent, are encouraging despite the un-
derlying computational model was only a part of CAT. Mainly,
fallacies have not been implemented although they have a key
role in moral judgment intuition and reasoning.
REFERENCES
Arsenio, W. F., & Gold, G. (2006). The effects of social injustice and
inequality on children’s moral judgments and behavior: Towards a
theoretical model. Cognitive Development, 21, 388-400.
doi:1.1016/j.cogdev.2006.06.005
Bartels, D. M. (2008). Principled moral sentiment and the flexibility of
moral judgment and decision making. Cognition, 108, 381-417.
doi:1.1016/j.cognition.2008.03.001
Bartels, D. M., & Pizarro, D. A. (2011). The mismeasure of morals:
Antisocial personality traits predict utilitarian responses to moral di-
lemmas. Cognition, 121, 154-161.
doi:1.1016/j.cognition.2011.05.010
Baron, J., & Spranca, M. (1997). Protected values. Organizational
Behavior and Human Decision Processes, 70, 1-16.
Blair, R. (1995). A cognitive developmental approach to morality:
Investigating the psychopath. Cognition, 57, 1-29.
Chentouf, Z. (2000). Homo informaticus. Paris: L’Harmattan.
Chentouf, Z. (1997). Invariable variable: Introduction to the recur-
rence theory. Algiers: Office des Publications Universitaires.
Cushman, F., Young, L., & Hauser, M. (2006). The role of conscious
reasoning and intuition in moral judgments: Testing three principles
of harm. Psychological Science, 17, 1082-1089.
doi:1.1111/j.1467-928.2006.01834.x
Darwall, S. (2003a). Consequentialism. Oxford: Oxford University Press.
Darwall, S. (2003b). Deontology. Oxford: Oxford University Press.
Davis, N. (1993). Contemporary deontology. In P. Singer (Ed.), A
companion to ethics (pp. 205-218). Malden, MA: Blackwell Pub-
lishing.
Foot, P. (1967). The problem of abortion and the doctrine of double
effect. Oxford Review, 5, 5-15.
Gass, R. (2012). Common fallacies in reasoning. URL (last checked 17
October 2012).
http://commfaculty.fullerton.edu/rgass/fallacy3211.htm
Greene, J. D., Morelli, S. A., Lowenberg, K., Nystrom, L. E., & Cohen,
J. D. (2008). Cognitive load selectively interferes with utilitarian
moral judgment. Cognition, 10 7, 1144-1154.
doi:1.1016/j.cognition.2007.11.004
Gross, J. (1998). The emerging field of emotion regulation. Review of
General Psychology, 2, 271-299.
Haidt, J. (2007). The new synthesis in moral psychology. Science, 316,
998-1002. doi:1.1126/science.1137651
Haidt, J. (2001). The emotional dog and its rational tail: A social intu-
itionist approach to moral judgment. Psychological Review, 108,
814-834. doi:1.1037//0033-295X.108.4.814
Hauser, M. D. (2006). Moral minds: How nature designed our univer-
sal sense of right and wrong. New York: Harper Collins.
Nichols, S., & Mallon, R. (2006). Moral dilemmas and moral rules.
Cognition, 100, 530-542. doi:1.1016/j.cognition.2005.07.005
Nichols, S. (2002). Norms with feeling: Towards a psychological ac-
count of moral judgment. Cog nition, 84, 221-236.
doi:1.1016/S0010-0277(02)00048-3
Oatley, K. (1999). Emotions. In R. A. Wilson and F. Kiel (Eds.), The
MIT encyclopaedia of the cognitive sciences (pp. 273-275). Boston:
MIT Press.
Paulsen, O., & Sejnowski, T. J. (2000). Natural patterns of activity and
long-term synaptic plasticity. Current Opinion in Neurobiology, 10,
172-179. doi:1.1016/S0959-4388(00)00076-3.
Pettit, P. (1993). Consequentialism. In P. Singer (Ed.), A companion to
ethics (pp. 273-275). Malden, MA: Blackwell publishing.
Roseman, I. J., & Smith, C. A. (2001). Appraisal theories. In K. R.
Sherer, A. Schorr, & T. Johnstone (Eds.), Appraisal processes in
emotion: Theory, method, research (pp. 3-19). Oxford: Oxford Uni-
versity Press.
Sherer, K. R. (2001). Appraisal considered as a process of multilevel
sequential checking. In K. R. Sherer, A. Schorr, & T. Johnstone
(Eds.), Appraisal processes in emotion: theory, method, research (pp.
92-120). Oxford: Oxford University Press.
Shwarz, N., & Clore, G. L. (1983). Mood, misattribution, and judgment
of well-being. Journal of Personality and Social Psychology, 45,
513-523.
Copyright © 2013 SciRes.
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Copyright © 2013 SciRes. 43
Stich, S., & Ravenscroft, I. (1994). What is folk psychology? Cognition,
50, 447-468. doi:1.1016/S0959-4388(00)00076-3.
Warren, H. C. (1921). A history of the association psychology. New
York: Charles Scribner’s Sons.
Wellman, H. M. (1990). The Child’s theory of mind. Cambridge, MA:
MIT Press.