Predicting satisfaction: perceived decision quality by decision-makers in Web-based group decision support systems

In future, the organizations' likelihood to endure and succeed will depend greatly on the quality of every decision made. It is known that most decisions in organizations are made in group. With the purpose of supporting decision-makers anytime and anywhere, Web-based Group Decision Support Systems (GDSS) have been studied. The amount of Web-based GDSS incorporating automatic negotiation mechanisms such as argumentation has been steadily increasing. Usually, these systems/models are evaluated through mathematical proofs, number of rounds or seconds to propose (reach) a solution. However, those techniques are not very informative in terms of the decision quality. Here, we propose a model that intends to predict the decision-makers' satisfaction (perception of the decision quality), specifically designed to deal with multi-criteria problems. Our model considers aspects such as: meeting's outcomes, decision-maker's intentions, expectations and emotional cost. To validate the proposed model in terms of its ability to predict decision-makers' satisfaction, we developed a prototype of a Web-based GDSS to be used in a case study where the participant had to make a joint decision. The decision process consisted in a set of 5 rounds, where the participant could (re) configure his/her preferences along the process. The satisfaction model ascertained its ability to predict the participants' satisfaction and allowed to understand that (as is stated in the literature) the inclusion of cognitive and emotional variables is essential to evaluate satisfaction more accurately.This paper is a revised and an expanded version of a paper entitled "Evaluating the Perception of the Decision Quality in Web-Based Group Decision Support Systems: A Theory of Satisfaction" presented at International Conference on Practical Applications of Agents and Multi-Agent Systems 2017, Porto, Portugal [12]. This work has been supported by COMPETE Programme (operational programme for competitiveness) within project POCI-01-0145-FEDER-007043, by National Funds through the FCT - Fundacao para a Ciencia e a Tecnologia (Portuguese Foundation for Science and Technology) within the Projects UID/CEC/00319/2013, UID/EEA/00760/2013, NORTE-01-0247-FEDER-021958, and the PhD. grants SFRH/BD/89697/2012 and SFRH/BD/89465/2012 attributed to Joao Carneiro and Pedro Saraiva, respectively

Experience representation in information systems

This thesis looks into the ways subjective dimension of experience could be represented in artificial, non-biological systems, in particular information systems. The pivotal assumption is that experience as opposed to mainstream thinking in information science is not equal to knowledge, so that experience is a broader term which encapsulates both knowledge and subjective, affective component of experience, which so far has not been properly embraced by knowledge representation theories. This is the consequence of dominance of behaviourism and later cognitivism in the XXth-century science, which tended to reduce mind and experience respectively to behavioural expressions and discrete states relating mindful creature to external world, meanwhile the processes of knowing to manipulations with symbols. We support the view that traditional knowledge representation approaches will not suffice to embrace the entirety of mental phenomena. We propose that in order to understand, represent and model the thinking and behavioural processes of mindful entities in information systems we need to look into the phenomenon of experience beyond the boundaries of knowledge. At the same time we propose to look at experience in a more structured way and try to capture it in formal terms, making it amenable to symbolic representation, being aware at the same time of innate limitations of symbolic representations compared to the natural representations in biological bodies. Under the paradigm of mind intentionality, which assumes that minds have this special intrinsic feature that they can relate to external word and thus are about external world, it can be asserted that experience is one in all intentional mind state composed of knowledge that is the intentional contents of this state, the world-to-mind relation, meanwhile its inseparable subjective component is composed of subjective feelings of the mindful individual corresponding to this intentional mind states. If so, we propose that experience can be defined as two-dimensional mental phenomena consisting of mental states that have both knowledge and affective component. Consequently we suggest that experience can be represented as pairs of elements of sets K, and A, where K represents knowledge, hence contents of remembered intentional states of mind (i.e. intentional contents of experience), whereas A represents affect, i.e. the subjective qualitative component of experience. iii Importantly, it does not particularly matter if we define experience as a set of mind states or a mind state process for assessing if the overall relation between knowledge and subjective experience that we have outlined above is valid. Whether there is knowing rather then knowledge or experiencing rather than experience which seems increasingly a contemporary principle, remains a fascinating philosophical, ontological to be more specific, question, however it falls beyond the scope of the thesis and therefore we shall not concentrate on it herewith. Furthermore we propose that the subjective component of experience is also intrinsically intentionalistic, but meanwhile the intentionality in case of knowing is directed outward, to the external world, in case of feeling it is directed inwards to the within of the experiencing mindbody. We tap into the contemporary thinking in the philosophy of mind that the primordial, intrinsic intentionalistic capacity of mind is non-linguistic, as there must be other more primordial, non-linguistic form of intentionality that allows human children, as well as other language-capable animals, to learn language in first place. Contemporary cognitive neuroscience suggest that this capacity is tightly related to affect. We also embrace the theories of consciousness and self coming from brain scientists such as Damasio and Panksepp who believe that there is a primordial component of self, a so called protoself composed of the raw feelings coming from within the body, which are representations of bodily states in the mind, and have strictly subjective character. Therefore we can look at this compound of primordial feelings as a mirror in which external world reflects via the interface of the senses. This results in experience that has this conceptually dual, yet united within the conscious mindbody, composition of intentional contents that is knowledge and subjective component that is built up by feelings coming from within the experiencing mindbody. For it is problematic to state sharply either that this composition is dual or united we can refer to these two separately considered aspects of experience either as components or dimensions. In this thesis we pay particular attention to the role the affective component of experience plays in the behaviour of organisms, and we use the concept of rational agency to discuss the relations between agent experience and behaviour. This role is primarily about motivation and experience vividness, i.e. how easily experiential states can be retrieved from memory. The affective dimension of experience determines the drivers for agent action and influences the remembering and forgetting (memory) processes that experience is prone to. We reflect on how the above presented framework could enhance one of the most popular rational agency models: the Believes Desires Intentions model (BDI) based on Bratmann’s account of practical reason that has dominated information science and artificial intelligence literature. Inspired by Davidson, who opposing Hume’s account that the passions (desires) drive action while reason (belief) merely directs its force, concluded that iv “(...) belief and desire seem equally to be causal conditions of action. But (...) desire is more basic in that if we know enough about a person’s desires, we can work out what he believes, while the reverse does not hold.” (Davidson, 2004) we conclude that in so far as BDI model approaches them, desires are sort of beliefs. Indeed a desire in the above sense is a verbalised desire, i.e. in order for a proposition to be included in the deliberation an agent must have internally verbalize it and accept it by which he converts it into a belief. As a result an agent acquires a belief about its desire. Apart from desires made thus explicit and becoming beliefs there are implicit experiential states that directly influence behaviour, these are not embraced by the Desires set in the BDI and other instrumentalist rationality models as these currently do not have adequate forms of representation. If this is so, the BDI models looses its D creating a gap which must be filled in, which we try to do with the subjective dimension of experience. Under such an account each belief, either the proper one or about the desire, represented formally with a proposition should have an extra component added which would stand for the subjective affective state to this belief. Some preliminary suggestions how this could be implemented are proposed and discussed. The central proposition of this thesis states that experience, broadly understood as the entirety of contents and quality of a conscious mind state, can be satisfactorily represented in information systems, and any information system which objective is to emulate natural agent behaviour with satisfactory faithfulness cannot do without a sound experience representation framework. To achieve this it is necessary to realize and accept, based on convincing evidence from neuroscience, that the missing subjective component of experience is affect that forms and integral part of natural agent’s experience, and determines, or at least impacts profoundly the behaviour of natural agents. Relating affect to knowledge would result in a satisfactory approximation of experience. It is to realize as well that the subjective dimension of experience, classified as affect, is not entirely private, subjective epiphenomenal entity but rather can be studied in objective terms as neurological correlates in the brain following account of emotion and affect as fostered by contemporary neuroscience. By identifying affective correlates of intentional contents of states of mind, which build up knowledge, we can exploit a broader concept experience for the purpose of more accurate emulation of natural agents’ thinking process and behaviour in information systems. This thesis presents and discusses a bulk of evidence coming mainly from three fields: information science, philosophy of mind and cognitive neuroscience that led us to the above stated conclusions, as well as establishes a framework for experience representation in information systems

Fuzzy Computational Model for Emotion Regulation Based on Affect Control Theory

Emotion modeling is a multi-disciplinary problem that has managed to attract a great deal of research work spanned to a wide spectrum of scholarly areas starting at humanistic science fields passing through applied sciences and engineering and arriving at health care and wellbeing. Emotion research under the umbrella of IT and Computer Science was extensively successful with a handful of achievements especially in the last two decades. Affective Computing is an IT originated systematic research area that strives to best model emotions in a way that fits the needs for computer applications enriched with affective component. A comprehensive Affective Computing based system is made of three major components: a component for emotion detection, a component for emotion modeling, and finally a component to generating affective responses in artificial agents. The major focus of this dissertation is on developing efficient computational models for emotions. In fact most of the research works presented in this dissertation were focused on a sub problem of emotion modeling known as emotion regulation at which we strive to model the dynamics of changes in the emotional response levels of individuals as a result of the overt or covert situational changes. In this dissertation, several emotion related problems were addressed. Modeling the dynamics for emotion elicitation from a pure appraisal approach, investigating individualistic differences in emotional processes, and modeling emotion contagion as a type of social contagion phenomena are a few to name from those conducted research works. The main contribution of this dissertation was to propose a new computational model for the problem of emotion regulation that is based on Affect Control Theory. The new approach utilized a hybrid appraisal-dimensional architecture. By using a fuzzy modeling approach, the natural fuzziness in perceiving, representing and expressing emotions was effectively and efficiently addressed. Furthermore, the combination of automata framework with the concept of bipolar emotional channels used at the heart of the modeling processes of the proposed model has further contributed to promote the behavior of the model in order to exhibit an accepted degree of human-like affective behavior

From audiences to mobs : crowd simulation with psychological factors

Ankara : The Department of Computer Engineering and the Institute of Engineering and Science of Bilkent University, 2010.Thesis (Ph. D.) -- Bilkent University, 2010.Includes bibliographical references leaves 90-101.Crowd simulation has a wide range of application areas such as biological and social modeling, military simulations, computer games and movies. Simulating the behavior of animated virtual crowds has been a challenging task for the computer graphics community. As well as the physical and the geometrical aspects, the semantics underlying the motion of real crowds inspire the design and implementation of virtual crowds. Psychology helps us understand the motivations of the individuals constituting a crowd. There has been extensive research on incorporating psychological models into the simulation of autonomous agents. However, in our study, instead of the psychological state of an individual agent as such, we are interested in the overall behavior of the crowd that consists of virtual humans with various psychological states. For this purpose, we incorporate the three basic constituents of affect: personality, emotion and mood. Each of these elements contribute variably to the emergence of different aspects of behavior. We thus examine, by changing the parameters, how groups of people with different characteristics interact with each other, and accordingly, how the global crowd behavior is influenced. In the social psychology literature, crowds are classified as mobs and audiences. Audiences are passive crowds whereas mobs are active crowds with emotional, irrational and seemingly homogeneous behavior. In this thesis, we examine how audiences turn into mobs and simulate the common properties of mobs to create collective misbehavior. So far, crowd simulation research has focused on panicking crowds among all types of mobs. We extend the state of the art to simulate different types of mobs based on the taxonomy. We demonstrate various scenarios that realize the behavior of distinct mob types. Our model is built on top of an existing crowd simulation system, HiDAC (High-Density Autonomous Crowds). HiDAC provides us with the physical and low-level psychological features of crowds. The user normally sets these parameters to model the non-uniformity and diversity of the crowd. In our work, we free the user of the tedious task of low-level parameter tuning, and combine all these behaviors in distinct psychological factors. We present the results of our experiments on whether the incorporation of a personality model into HiDAC was perceived as intended.Durupınar, FundaPh.D