When simulating emotions in an a ective agent we must include factors that can a ect the agent emotional behavior such as mood or personality. Personality can make a person more prone to feel certain types of emotions and mood. In this work we present the preliminary results obtained in an experiment carried out to nd the factors that a ect human emotional behavior in order to simulate this behaviour in an a ective agent. We have focused on the e ect of personality on the di erences between agents mood. Preliminary results show that there is a correlation between the participants' personality and their initial mood.
There are several theories that try to explain the human behavior. One of the
most relevant is the practical reasoning that is based on the idea that humans use
the reason to decide how to act [7]. But human behavior is not always rational.
This is due in part to emotions, mood and personality [12]. Many psychological
studies have shown that personality in uences cognitive processes (e.g. decision
making process) as well and a ective processes (e.g. making a person more or less
prone to feel certain moods) [2, 20, 23]. Therefore, in order to simulate human
behavior through an a ective agent, it is necessary to study the in uence of its
personality on the agent cognitive and a ective processes [15, 16]. In this article
we show the preliminary results obtained in an experiment with 300 participants
conducted to develop an a ective agent model in the GenIA3 architecture [
Over the years di erent models have been proposed to represent di erent affective characteristics such as personality, emotions and mood. One of the most used models in psychology to de ne a ection and personality is the PANAS model [13]. This model uses two dimensions to represent personality: Positive A ect (PA) and Negative A ect (NA) [21]. According to this model PA and NA can be considered as two independent variables. For example, the state of relaxation corresponds to a low level of negative a ect, while calm is conditioned to a low positive a ect. The positive a ect re ects how enthusiastic, active, alert, and energetic a person is. While the negative a ect re ects how disgusted, disinterested, angry, guilty, cowardly, and nervous a person is. Some moods are the result of the combination of both variables. Happiness for example, is related to a high level of positive a ect and a low level of negative a ect, while sadness is related to low levels of positive a ect and high levels of negative a ect [19]. The PANAS model can be used to analyze human personality using questionnaires in which the questions are conducted generically [11]. For example, in the question \Are you usually feel sad?", the PA and NA factors can be interpreted as personality values instead of mood because the question refers to the "usual" emotional state of the person. The simplicity of this model make it appropriate to be used in modelling agents personality. There are other psychological models to represent personality using quantitative variables such as the Five Factor Model [10] that uses ve variables to de ne personality: Openness, Consciousness, Extraversion, Agreebleness, and Neuroticism.
Di erent studies have been carried out to relate emotions and personality. For example, the trait of Extraversion is related to positive emotions and moods while Neuroticism is related to negative emotions and moods [5, 14, 15, 20, 17]. Similarly, in the PANAS model the PA and NA variables related to personality have a relationship with the PA and NA variables related to mood [22].
In recent years, di erent models have been proposed to simulate a ective
human behavior [8, 9]. One of the most innovative proposals is GenIA3, which
is a general purpose architecture for a ective agents based on the BDI model
(beliefs, desires and intentions) [
Our main goal is to develop an a ective agent capable of simulating human
behavior through emotions, personality, and mood. However, as we argued before,
in order to develop this agent model it is necessary to study the relationships
between the di erent a ective categories. As part of the development of our
a ective agent model, in this work we analyze the relationship between
personality and mood. We have used the data obtained from an experiment [
the standard deviation of the M NA variable is very small, indicating that the data may be concentrated near the mean. This is better shown in Figure 1, in which we can see that the data of the variable M NA is concentrated in low values, while the variable M PA has a more normal distribution.
On the other hand, Table 2 shows the correlation between PANAS variables for both personality and mood. As we can see, P PA and P NA have a moderate correlation with M NA. While M PA variable has a high correlation with P PA and a moderate correlation with P NA. We can also see that all correlations are statistically signi cant except for P PA and P NA. In order to analyze how personality a ects mood we have performed a regression analysis on M PA and M NA variables.
The result of the regression analysis for M PA variable is shown in Table 3. The only statistically signi cant variable in this regression model is P PA since its p-value is less than 0.05. Figure 2 shows the statistical analysis of the regression model. As we can see, the residues of the regression model fall along the straight line at a 45% angle in the Q-Q plot which provide strong evidence that these numbers come from an uniform distribution. The residual graph (Figure 2) shows that the variation of the residues is constant, so we can assume that the assumption of linearity is met. Therefore we can assume that the regression model is valid for the M PA variable.
The r-squared value is 0.2931 therefore this regression model explains the 29:31% of the variability of the variable M PA. Although it is a low percent
M_2NA age, we must consider the variability of the data when performing this type of psychological experiments. Therefore, both a r-squared of thirty percent can be a good value if we consider that we have only used personality to explain the di erences between participants' initial mood. Therefore, each a ective agent of our model will calculate its initial mood considering that thirty percent of its M PA depend on its P PA value.
For the prediction of M NA value, as we mentioned above, the data is asymmetric and with low dispersion, which makes it di cult to apply a linear regression algorithm. We have tried to apply di erent transformations of the data and we have not found any linear regression model that met the normality conditions. 5
In this work we have presented a preliminary analysis of the in uence of personality on mood using the data obtained in an experiment with 300 participants. This analysis allow us to obtain a model that partially explain the relationship between mood and personality and emotional behavior. We are using this model to develop a multi-agent system capable of simulating human behavior in a realistic way.
We have shown that the P PA variable from the PANAS model has a positive correlation with the variable M PA, which indicates that there is in uence of personality on mood. However, the variable M NA has an asymmetric distribution, which has made it di cult to nd a linear regression model to determine the in uence of personality on this variable. Nevertheless, in this work we have shown the importance of personality in mood, being able to explain almost thirty percent of the variability of the variable M PA.
We are currently analyzing in deep all the results of the experiment in order to nd a model that allows us to identify the proportion of variance of the NA variable that can be explained by personality. Once these models are obtained, we want to implement a multi-agent system within the GenIA3architecture that allows us to simulate human behavior taking into account di erent personalities.
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