Agents for educational games and simulations

This book consists mainly of revised papers that were presented at the Agents for Educational Games and Simulation (AEGS) workshop held on May 2, 2011, as part of the Autonomous Agents and MultiAgent Systems (AAMAS) conference in Taipei, Taiwan. The 12 full papers presented were carefully reviewed and selected from various submissions. The papers are organized topical sections on middleware applications, dialogues and learning, adaption and convergence, and agent applications

Socio-Cognitive and Affective Computing

Social cognition focuses on how people process, store, and apply information about other people and social situations. It focuses on the role that cognitive processes play in social interactions. On the other hand, the term cognitive computing is generally used to refer to new hardware and/or software that mimics the functioning of the human brain and helps to improve human decision-making. In this sense, it is a type of computing with the goal of discovering more accurate models of how the human brain/mind senses, reasons, and responds to stimuli. Socio-Cognitive Computing should be understood as a set of theoretical interdisciplinary frameworks, methodologies, methods and hardware/software tools to model how the human brain mediates social interactions. In addition, Affective Computing is the study and development of systems and devices that can recognize, interpret, process, and simulate human affects, a fundamental aspect of socio-cognitive neuroscience. It is an interdisciplinary field spanning computer science, electrical engineering, psychology, and cognitive science. Physiological Computing is a category of technology in which electrophysiological data recorded directly from human activity are used to interface with a computing device. This technology becomes even more relevant when computing can be integrated pervasively in everyday life environments. Thus, Socio-Cognitive and Affective Computing systems should be able to adapt their behavior according to the Physiological Computing paradigm. This book integrates proposals from researchers who use signals from the brain and/or body to infer people's intentions and psychological state in smart computing systems. The design of this kind of systems combines knowledge and methods of ubiquitous and pervasive computing, as well as physiological data measurement and processing, with those of socio-cognitive and affective computing

A theoretical and practical approach to a persuasive agent model for change behaviour in oral care and hygiene

There is an increased use of the persuasive agent in behaviour change interventions due to the agent‘s features of sociable, reactive, autonomy, and proactive. However, many interventions have been unsuccessful, particularly in the domain of oral care. The psychological reactance has been identified as one of the major reasons for these unsuccessful behaviour change interventions. This study proposes a formal persuasive agent model that leads to psychological reactance reduction in order to achieve an improved behaviour change intervention in oral care and hygiene. Agent-based simulation methodology is adopted for the development of the proposed model. Evaluation of the model was conducted in two phases that include verification and validation. The verification process involves simulation trace and stability analysis. On the other hand, the validation was carried out using user-centred approach by developing an agent-based application based on belief-desire-intention architecture. This study contributes an agent model which is made up of interrelated cognitive and behavioural factors. Furthermore, the simulation traces provide some insights on the interactions among the identified factors in order to comprehend their roles in behaviour change intervention. The simulation result showed that as time increases, the psychological reactance decreases towards zero. Similarly, the model validation result showed that the percentage of respondents‘ who experienced psychological reactance towards behaviour change in oral care and hygiene was reduced from 100 percent to 3 percent. The contribution made in this thesis would enable agent application and behaviour change intervention designers to make scientific reasoning and predictions. Likewise, it provides a guideline for software designers on the development of agent-based applications that may not have psychological reactance

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

A study of the use of natural language processing for conversational agents

Language is a mark of humanity and conscience, with the conversation (or dialogue) as one of the most fundamental manners of communication that we learn as children. Therefore one way to make a computer more attractive for interaction with users is through the use of natural language. Among the systems with some degree of language capabilities developed, the Eliza chatterbot is probably the first with a focus on dialogue. In order to make the interaction more interesting and useful to the user there are other approaches besides chatterbots, like conversational agents. These agents generally have, to some degree, properties like: a body (with cognitive states, including beliefs, desires and intentions or objectives); an interactive incorporation in the real or virtual world (including perception of events, communication, ability to manipulate the world and communicate with others); and behavior similar to a human (including affective abilities). This type of agents has been called by several terms, including animated agents or embedded conversational agents (ECA). A dialogue system has six basic components. (1) The speech recognition component is responsible for translating the user’s speech into text. (2) The Natural Language Understanding component produces a semantic representation suitable for dialogues, usually using grammars and ontologies. (3) The Task Manager chooses the concepts to be expressed to the user. (4) The Natural Language Generation component defines how to express these concepts in words. (5) The dialog manager controls the structure of the dialogue. (6) The synthesizer is responsible for translating the agents answer into speech. However, there is no consensus about the necessary resources for developing conversational agents and the difficulties involved (especially in resource-poor languages). This work focuses on the influence of natural language components (dialogue understander and manager) and analyses, in particular the use of parsing systems as part of developing conversational agents with more flexible language capabilities. This work analyses what kind of parsing resources contributes to conversational agents and discusses how to develop them targeting Portuguese, which is a resource-poor language. To do so we analyze approaches to the understanding of natural language, and identify parsing approaches that offer good performance, based on which we develop a prototype to evaluate the impact of using a parser in a conversational agent.linguagem é uma marca da humanidade e da consciência, sendo a conversação (ou diálogo) uma das maneiras de comunicacão mais fundamentais que aprendemos quando crianças. Por isso uma forma de fazer um computador mais atrativo para interação com usuários é usando linguagem natural. Dos sistemas com algum grau de capacidade de linguagem desenvolvidos, o chatterbot Eliza é, provavelmente, o primeiro sistema com foco em diálogo. Com o objetivo de tornar a interação mais interessante e útil para o usuário há outras aplicações alem de chatterbots, como agentes conversacionais. Estes agentes geralmente possuem, em algum grau, propriedades como: corpo (com estados cognitivos, incluindo crenças, desejos e intenções ou objetivos); incorporação interativa no mundo real ou virtual (incluindo percepções de eventos, comunicação, habilidade de manipular o mundo e comunicar com outros agentes); e comportamento similar ao humano (incluindo habilidades afetivas). Este tipo de agente tem sido chamado de diversos nomes como agentes animados ou agentes conversacionais incorporados. Um sistema de diálogo possui seis componentes básicos. (1) O componente de reconhecimento de fala que é responsável por traduzir a fala do usuário em texto. (2) O componente de entendimento de linguagem natural que produz uma representação semântica adequada para diálogos, normalmente utilizando gramáticas e ontologias. (3) O gerenciador de tarefa que escolhe os conceitos a serem expressos ao usuário. (4) O componente de geração de linguagem natural que define como expressar estes conceitos em palavras. (5) O gerenciador de diálogo controla a estrutura do diálogo. (6) O sintetizador de voz é responsável por traduzir a resposta do agente em fala. No entanto, não há consenso sobre os recursos necessários para desenvolver agentes conversacionais e a dificuldade envolvida nisso (especialmente em línguas com poucos recursos disponíveis). Este trabalho foca na influência dos componentes de linguagem natural (entendimento e gerência de diálogo) e analisa em especial o uso de sistemas de análise sintática (parser) como parte do desenvolvimento de agentes conversacionais com habilidades de linguagem mais flexível. Este trabalho analisa quais os recursos do analisador sintático contribuem para agentes conversacionais e aborda como os desenvolver, tendo como língua alvo o português (uma língua com poucos recursos disponíveis). Para isto, analisamos as abordagens de entendimento de linguagem natural e identificamos as abordagens de análise sintática que oferecem um bom desempenho. Baseados nesta análise, desenvolvemos um protótipo para avaliar o impacto do uso de analisador sintático em um agente conversacional

Domain independent strategies in an affective tutoring system

There have been various attempts to develop an affective tutoring system (ATS) framework that considers and reacts to a student’s emotions while learning. However, there is a gap between current systems and the theory underlying human appraisal models. The current frameworks rely on a single appraisal and reaction phase. In contrast, the human appraisal process (Lazarus, 1991) involves two phases of appraisal and reaction (i.e. primary and secondary appraisal phases). This thesis proposes an affective tutoring (ATS) framework that introduces two phases of appraisal and reaction (i.e. primary and secondary appraisal and reaction phases). This proposed framework has been implemented and evaluated in a system to teach Data Structures. In addition, the system employs both domain-dependent and domain-independent strategies for coping with students’ affective states. This follows the emotion regulation model (Lazarus, 1991) that underpins the ATS framework which argues that individuals use both kinds of strategies in solving daily life problems. In comparison, current affective (ITS) frameworks concentrate on the use of domain-dependent strategies to cope with students’ affective states. The evaluation of the system provides some support for the idea that the ATS framework is useful both in improving students’ affective states (i.e. during and by the end of a learning session) and also their learning performance

An ambient agent model for reading companion robot

Reading is essentially a problem-solving task. Based on what is read, like problem solving, it requires effort, planning, self-monitoring, strategy selection, and reflection. Also, as readers are trying to solve difficult problems, reading materials become more complex, thus demands more effort and challenges cognition. To address this issue, companion robots can be deployed to assist readers in solving difficult reading tasks by making reading process more enjoyable and meaningful. These robots require an ambient agent model, monitoring of a reader’s cognitive demand as it could consist of more complex tasks and dynamic interactions between human and environment. Current cognitive load models are not developed in a form to have reasoning qualities and not integrated into companion robots. Thus, this study has been conducted to develop an ambient agent model of cognitive load and reading performance to be integrated into a reading companion robot. The research activities were based on Design Science Research Process, Agent-Based Modelling, and Ambient Agent Framework. The proposed model was evaluated through a series of verification and validation approaches. The verification process includes equilibria evaluation and automated trace analysis approaches to ensure the model exhibits realistic behaviours and in accordance to related empirical data and literature. On the other hand, validation process that involved human experiment proved that a reading companion robot was able to reduce cognitive load during demanding reading tasks. Moreover, experiments results indicated that the integration of an ambient agent model into a reading companion robot enabled the robot to be perceived as a social, intelligent, useful, and motivational digital side-kick. The study contribution makes it feasible for new endeavours that aim at designing ambient applications based on human’s physical and cognitive process as an ambient agent model of cognitive load and reading performance was developed. Furthermore, it also helps in designing more realistic reading companion robots in the future