Jan Treur
Vrije Universiteit Amsterdam, Computer Science, Faculty Member
ABSTRACT
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IntroductionIt is a recent trend in the literature on verification to study the use of compositionality and abstractionto structure the process of verification; for example, see (Abadi and Lamport, 1993; Hooman, 1994;Dams, Gerth and Kelb,... more
IntroductionIt is a recent trend in the literature on verification to study the use of compositionality and abstractionto structure the process of verification; for example, see (Abadi and Lamport, 1993; Hooman, 1994;Dams, Gerth and Kelb, 1996). In (Cornelissen, Jonker and Treur, 1997) a compositional verificationmethod was introduced for logic-based specifications of knowledge-based systems. The currentpaper discusses the requirements for the choice and use of a suitable logic with which ...
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In this paper, graphical representations for knowledge structures in DESIRE (Brazier Dunin-Keplicz, Jennings & Treur 1995; Brazier, Treur, Wijngaards & Willems 1996) are presented, together with a graphical editor based on the... more
In this paper, graphical representations for knowledge structures in DESIRE (Brazier Dunin-Keplicz, Jennings & Treur 1995; Brazier, Treur, Wijngaards & Willems 1996) are presented, together with a graphical editor based on the Constraint Graph environment (Kremer, 1997). Moreover, a translator will be described which translates these graphical representations to textual representations in DESIRE. The strength of the combined environment is a powerful -- yet easy-to-use -- framework to support the development of knowledge based and multi-agent systems.
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When designing complex knowledge-based systems, it is often hard to guarantee that the specification of a system that has been designed actually fulfills the needs, i.e., whether it satisfies the design requirements. Especially for... more
When designing complex knowledge-based systems, it is often hard to guarantee that the specification of a system that has been designed actually fulfills the needs, i.e., whether it satisfies the design requirements. Especially for critical applications, for example in aerospace domains, there is a need to prove that the designed system will have certain properties under certain conditions (assumptions). While developing a proof of such properties, the assumptions that define the bounds within which the system will function properly are generated.
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Organizational performance analysis enables organizations to uncover unexpected properties of organizations and allow them to reconsider their internal workings and provide support for this. To perform such an analysis and obtain... more
Organizational performance analysis enables organizations to uncover unexpected properties of organizations and allow them to reconsider their internal workings and provide support for this. To perform such an analysis and obtain appropriate support, in this paper organizations are modeled as labeled graphs that capture the interactions of the entities and the characteristics of those interactions, such as their content and frequency, through labels in the graph. Algebraic representations and manipulations of the labels enable analysis of ...
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Research Interests: Engineering, Computer Science, Artificial Intelligence, Information Theory, Cognition, and 15 moreAgent Based, Formal Analysis, Electronic Markets, Cooperation, Information Flow, Formal Specification, Incident Management, Classification, Formal method, Incomplete Information, Real Time, Error Detection, Information System, Psychology and Cognitive Sciences, and Medical and Health Sciences
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Research Interests: Cognitive Science, Computer Science, Philosophy, Negotiation, Linguistics, and 15 moreTheoretical Computer Science, Abstraction, Distributed System, System Design, Multi Agent System, Code Generation, Compositionality, Modularity, Synchronous Language, Mathematical Model, Applied artificial intelligence, Modular Design, Programming language, Mathematical Proof, and Springer Ebooks
Social media is one of the widely used channels for interpersonal communication, and to give personal feedback. However, negative feedback can affect esteem and mental health of a person. This paper presents a computational network model... more
Social media is one of the widely used channels for interpersonal communication, and to give personal feedback. However, negative feedback can affect esteem and mental health of a person. This paper presents a computational network model of a humanoid agent for getting inappropriate feedback, who learns to react with a level of competence on aggression due to feedback. This model can serve as an input to detect and handle cyber-aggression.
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Parents play an important role in the mental development of a child. In our previous work, we addressed how a narcissistic parent influences a child (online/offline) when (s)he is happy and admires the child. Now, we address the influence... more
Parents play an important role in the mental development of a child. In our previous work, we addressed how a narcissistic parent influences a child (online/offline) when (s)he is happy and admires the child. Now, we address the influence of a parent who is not so much pleased and, may curse the child for being the reason for his or her unhappiness. An abusive relationship with a parent can also cause trauma and poor mental health of the child. We also address how certain coping behaviors can help the child cope with such a situation. Therefore, the aim of the study is three folds. We present an adaptive agent model of a child, while incorporating the concept of mirroring through social contagion, the avoidance behaviors from a child, and the effects of regulation strategies to cope with stressful situations.
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Social media like Twitter or Instagram play a role of fertile ground for self-exhibition, which is used by various narcissists to share their frequent updates reflecting their narcissism. Their belief of saving and assisting others, make... more
Social media like Twitter or Instagram play a role of fertile ground for self-exhibition, which is used by various narcissists to share their frequent updates reflecting their narcissism. Their belief of saving and assisting others, make them vulnerable to the feedback of others, so their rage is as dangerous as their messiah complex. In this paper, we aim to analyse the behaviour of a narcissist when he is admired or receives negative critics. We designed a complex adaptive mental network model of the process of narcissism based on the theories of neuroscience and psychology including a Hebbian learning principal. The model was validated by analyzing Instagram data.
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Social media like Twitter or Instagram play the role of fertile platforms for self-exhibition and allow their users to earn a good repute. People higher in grandiosity share their contents in a charismatic way and as a result, they are... more
Social media like Twitter or Instagram play the role of fertile platforms for self-exhibition and allow their users to earn a good repute. People higher in grandiosity share their contents in a charismatic way and as a result, they are successful in gaining attention from others, which may also influence their responses and behaviors. Such attention and repute enable them to be a trendsetter or a socially recognized maven. In this paper, we present a complex adaptive mental network model of a narcissist to see how popularity can adaptively influence his/her behavior. To analyze and to support behavior showed by our model, we used some key performance indicators from the literature to study the popularity and narcissism of 30 Instagram profiles. The results of the—both computational and empirical—study indicate that our presented computational adaptive network model in general shows the behavior found from the empirical data.
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This volume constitutes the thoroughly refereed conference proceedings of the 26th International Conference on Industrial Engineering and Other Applications of Applied Intelligence Systems, IEA/AIE 2013, held in Amsterdam, The... more
This volume constitutes the thoroughly refereed conference proceedings of the 26th International Conference on Industrial Engineering and Other Applications of Applied Intelligence Systems, IEA/AIE 2013, held in Amsterdam, The Netherlands, in June 2013. The total of 71 papers selected for the proceedings were carefully reviewed and selected from 185 submissions. The papers focus on the following topics: auctions and negotiation, cognitive modeling, crowd behavior modeling, distributed systems and networks, evolutionary algorithms, knowledge representation and reasoning, pattern recognition, planning, problem solving, robotics, text mining, advances in recommender systems, business process intelligence, decision support for safety-related systems, innovations in intelligent computation and applications, intelligent image and signal processing, and machine learning methods applied to manufacturing processes and production systems.
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Research Interests: Cognitive Science, Computer Science, Philosophy, Negotiation, Linguistics, and 15 moreTheoretical Computer Science, Abstraction, Distributed System, System Design, Multi Agent System, Code Generation, Compositionality, Modularity, Synchronous Language, Mathematical Model, Applied artificial intelligence, Modular Design, Programming language, Mathematical Proof, and Springer Ebooks
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Segregation is a widely-observed phenomenon through history, different cultures and around the world. This paper addresses how in a network of immigrants segregation emerges from friendship homophily. The simulation results show that... more
Segregation is a widely-observed phenomenon through history, different cultures and around the world. This paper addresses how in a network of immigrants segregation emerges from friendship homophily. The simulation results show that homophily results in clusters of lower and higher local language use. A mathematical analysis provides a more in depth understanding of the phenomena observed in the simulations.
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Regular physical activity contributes to higher levels of well-being, healthy aging and prevention of several chronic diseases such as depression. To establish or change behaviours concerning physical activity, social contagion may play a... more
Regular physical activity contributes to higher levels of well-being, healthy aging and prevention of several chronic diseases such as depression. To establish or change behaviours concerning physical activity, social contagion may play a role. The aim of this study was to model the contagion of physical activity based on empirical Twitter data and to assess the role of homophily within this contagion. To model the contagion of physical activity, an adaptive temporal-causal network model was designed, and accordingly, the parameters of the model were tuned using empirical data obtained from Twitter. Two variants of the adaptive temporal-causal network model were created, in which one calculated the weights of the connections between the nodes based on follow relations on Twitter, while in the other the connection weights were modulated by the homophily principle. The results indicate that within the considered social network of already active persons homophily does not play an important role in the physical activity behaviour.
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This study describes the use of adaptive temporal-causal networks to model and simulate the development of mutually interacting opinion states and connections between individuals in social networks. The focus is on adaptive networks... more
This study describes the use of adaptive temporal-causal networks to model and simulate the development of mutually interacting opinion states and connections between individuals in social networks. The focus is on adaptive networks combining the homophily principle with the more becomes more principle. The model has been used to analyse a data set concerning opinions about the use of alcohol and tobacco, and friendship relations. The achieved results provide insights in the potential of the approach.
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In this chapter a Network-Oriented Modeling approach is used to obtain a temporal-causal network model that generates prior and retrospective ownership states for an action based on principles from recent neurological theories. A prior... more
In this chapter a Network-Oriented Modeling approach is used to obtain a temporal-causal network model that generates prior and retrospective ownership states for an action based on principles from recent neurological theories. A prior ownership state is affected by prediction of the effects of a prepared action, and exerts control by strengthening or suppressing actual execution of the action. A retrospective ownership state depends on whether the sensed consequences of an executed action co-occur with the predicted consequences, and is the basis for acknowledging authorship of actions, for example, in a social context. It is shown how a number of known phenomena can occur. For example, scenarios are shown for vetoing a prepared action due to unsatisfactory predicted effects, and for mirroring an observed action performed by another person, without imitating the action. Moreover, it is shown how poor action effect prediction capabilities can lead to reduced retrospective ownership states, as in persons suffering from Schizophrenia. The obtained temporal-causal network model can be used as a basis for simulation-based training, for example, to develop a virtual patient based on the model so that a psychiatrist or psycho-therapist (e.g., during his or her education) can gain insight in the processes in certain types of patients, or to analyse how effective a certain form of therapy can be. A second type of application is in the area of gaming or virtual stories in which, for example, persons with deviations in ownership states play a role and based on that show unexpected behaviour.
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When persons function in a social context they interact with a number of other persons they know. These persons themselves also interact with a number of persons. And so on and on. When each person is modeled by a node and for each of... more
When persons function in a social context they interact with a number of other persons they know. These persons themselves also interact with a number of persons. And so on and on. When each person is modeled by a node and for each of these interactions arcs between the nodes are drawn, this results in a social network model, sometimes also called a social network; for example, as shown in Fig. 11.1. Note that as such arcs indicate that interaction takes place, and interaction in principle means that persons affect each other, from a dynamical perspective they can also be considered relations that represent mutual causal effects on certain mental states of persons.
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In this study, an adaptive temporal-causal network model is presented for learning of basic skills for social interaction. It focuses on greeting a known person and how that relates to learning how to recognize a person from seeing his or... more
In this study, an adaptive temporal-causal network model is presented for learning of basic skills for social interaction. It focuses on greeting a known person and how that relates to learning how to recognize a person from seeing his or her face. The model involves a Hebbian learning process. The model also addresses avoidance behavior related to enhanced sensory processing sensitivity. In scenarios persons without and with enhanced sensory processing sensitivity are compared. Mathematical analysis was performed to verify correctness of the model.
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In this paper a neurologically inspired cognitive agent model for desire regulation is presented that describes the desire generation process and a number of desire regulation strategies. This work addresses antecedent-focused desire... more
In this paper a neurologically inspired cognitive agent model for desire regulation is presented that describes the desire generation process and a number of desire regulation strategies. This work addresses antecedent-focused desire regulation strategies. These strategies include reinterpretation, attention deployment and situation modification. The model has been used to perform a number of simulation experiments concerning food desire and eating behaviour.
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In this paper it is analysed how emerging behaviour of an adaptive network for bonding based on homophily can be related to characteristics of the adaptive network’s structure, which includes the structure of the adaptation principles... more
In this paper it is analysed how emerging behaviour of an adaptive network for bonding based on homophily can be related to characteristics of the adaptive network’s structure, which includes the structure of the adaptation principles used. Relevant characteristics have been identified, such as a tipping point for homophily; it has been found how the emergence of clusters strongly depends on the value of this tipping point. It is shown that some properties of the structure of the network and the adaptation principle entail that the connection weights all converge to 0 (for states in different clusters) or 1 (for states within one cluster).
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This paper presents a computational network model for a person with a Borderline Personality Disorder. It was designed according to a Network-Oriented Modeling approach as a temporal-causal network based on neuropsychological background... more
This paper presents a computational network model for a person with a Borderline Personality Disorder. It was designed according to a Network-Oriented Modeling approach as a temporal-causal network based on neuropsychological background knowledge. Example simulations are discussed. The model was verified based on Mathematical Analysis of stationary points.
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Internet and cyber-technology have played an important positive role but it also served as a venue for cyber-bullying. This paper presents a computational model for online bullying. Its evaluation was done by simulation experiments and... more
Internet and cyber-technology have played an important positive role but it also served as a venue for cyber-bullying. This paper presents a computational model for online bullying. Its evaluation was done by simulation experiments and mathematical analysis, in comparison to expected patterns from the empirical literature. This model may provide useful input to build a support system to avoid this negative social behavior within society.
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Note that the chapter titles have hyperlinks leading to their abstracts and (eventually) to Powerpoint presentations.
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This book presents a new approach that can be applied to complex, integrated individual and social human processes. It provides an alternative means of addressing complexity, better suited for its purpose than and effectively... more
This book presents a new approach that can be applied to complex, integrated individual and social human processes. It provides an alternative means of addressing complexity, better suited for its purpose than and effectively complementing traditional strategies involving isolation and separation assumptions. Network-oriented modeling allows high-level cognitive, affective and social models in the form of (cyclic) graphs to be constructed, which can be automatically transformed into executable simulation models. The modeling format used makes it easy to take into account theories and findings about complex cognitive and social processes, which often involve dynamics based on interrelating cycles. Accordingly, it makes it possible to address complex phenomena such as the integration of emotions within cognitive processes of all kinds, of internal simulations and the mental processes of others, and of social phenomena such as shared understanding and collective action. A variety of sample models – including those for ownership of actions, fear and dreaming, the integration of emotions in joint decision-making based on empathic understanding, and evolving social networks – illustrate the potential of the approach. Dedicated software is available to support building models in a conceptual or graphical manner, transforming them into an executable format and performing simulation experiments. The majority of the material presented has been used and positively evaluated by undergraduate and graduate students and researchers in the cognitive, social and AI domains. Given its detailed coverage, the book is ideally suited as an introduction for graduate and undergraduate students in many different multidisciplinary fields involving cognitive, affective, social, biological, and neuroscience domains.