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Persuasion has been studied for more than two millennia. Basically it can be viewed as the collection of methodologies aiming at changing, by means of communication, the mental state of the receiver, in view of a certain action (or set of actions) to be performed by the receiver. Inspired by this tradition, and by the practical realizations in the world of advertising, in this article a novel generation of intelligent interfaces is introduced, based on the idea that systems will have goals of their own to pursue, as far as inducing users (or rather any audience) to believe something, do something or change their attitude. The world of leisure and of tourism can specifically be impacted by such interfaces. In the article the main concepts are introduced, as well as elements that characterize persuasion systems in general; a revisitation of the concept of promotion campaign leads to the description of research prototypes and a short analysis of prospects for tourism. [ABSTRACT FROM AUTHOR]

The present work proposes a methodological approach for modeling adaptation decisions and for solving the problem of integrating existing as well as acquired knowledge in the decision module of an adaptive interface. So far, most applications do not exploit in full the value of data originating from user models or knowledge acquisition engines that monitor the user and the context. The proposed decision theoretic model is represented through specifically structured influence diagrams. It provides to designers and developers a specific method to encode user and context information, as well as other crucial decision factors, to be subsequently used in the decision making process regarding user interface adaptation actions. Such a process is driven by the definition of relevant utilities referring to the design of a user interface. The proposed model guides designers and developers of an adaptive or intelligent interface to integrate, without conflicts and incoherence, design strategies, design goals, user goals, alternative constituents, user profile, context and application domain knowledge. An illustrative example of the analyzed modeling method is presented. [ABSTRACT FROM AUTHOR]

We aim to explore a new kind of user interface solely dedicated to presenting the global inner dynamics of Multi-Agent Systems (MASs) on a higher level. Being complex systems, MASs are often only or barely understood by their designer(s). Could we enable a particular kind of agent to tell the designer’s story about the agent- and human-interactive behaviours taking place inside the MAS in a meaningful way? Could a set of virtual actors turn this story into a ‘dynamic user-experience’? After taking a closer look at how to gain insight into complex systems and why to pick a drama-based approach, we present the three pillars of perception, interpretation and presentation, on which we base our visualisation efforts. We show how they relate to various research fields such as agent technology, human computer interaction, psychology, computer graphics, animation, drama, body language and cognitive ergonomics. Based upon these insights we introduce a conceptual model for drama-based visualisation, followed by a stepwise description of how this framework could be applied. The article closes with some reflections and conclusions. [ABSTRACT FROM AUTHOR]

One goal of research in the area of human–machine interaction is to improve the ways a human user interacts with a computer through a multimedia interface. This interaction comprises of not only text, graphical animation, stereo sounds, and live video images, but also force and haptic feedback, which can provide more “real” feeling to the user. The force feedback joystick, a human interface device is an input–output device. It not only tracks user's physical manipulation input, but also provides realistic physical sensations of force coordinated with system output. As part of our research, we have developed a multimedia computer game that assimilates images, sounds, and force feedback. We focused on the issues of how to combine these media to allow the user feel the compliance, damping, and vibration effects through the force feedback joystick. We conducted series of human subject experiments that incorporated different combinations of media, including the comparative study of the different performances of 60 human users, aiming to answer the question: What are the effects of force feedback (and associated time delays) when used in combination with visual and auditory information as part of a multi-modal interface? It is hoped that these results can be utilized in the design of enhanced multimedia systems that incorporate force feedback. [ABSTRACT FROM AUTHOR]

Mixed-initiative problem solving lies at the heart of knowledge- based learning environments. While learners are actively engaged in problem-solving activities, learning environments should monitor their progress and provide them with feedback in a manner that contributes to achieving the twin goals of learning effectiveness and learning efficiency. Mixed-initiative interactions are particularly critical for constructivist learning environments in which learners participate in active problem solving. We have recently begun to see the emergence of believable agents with lifelike qualities. Featured prominently in constructivist learning environments, lifelike pedagogical agents could couple key feedback functionalities with a strong visual presence by observing learners' progress and providing them with visually contextualized advice during mixed-initiative problem solving. For the past three years, we have been engaged in a large-scale research program on lifelike pedagogical agents and their role in constructivist learning environments. In the resulting computational framework, lifelike pedagogical agents are specified by (1) a behavior space containing animated and vocal behaviors, (2) a design-centered context model that maintains constructivist problem representations, multimodal advisory contexts, and evolving problem-solving tasks, and (3) a behavior sequencing engine that in realtime dynamically selects and assembles agents' actions to create pedagogically effective, lifelike behaviors. To empirically investigate this framework, it has been instantiated in a full-scale implementation of a lifelike pedagogical agent for Design-A-Plant, a learning environment developed for the domain of botanical anatomy and physiology for middle school students. Experience with focus group studies conducted with middle school students interacting with the implemented agent suggests that lifelike pedagogical agents hold much promise for mixed-initiative learning. [ABSTRACT FROM AUTHOR]

Plan recognition is an active research area in automatic reasoning, as well as a promising approach to engineering interfaces that can exploit models of user's plans and goals. Much research in the field has focused on the development of plan recognition algorithms to support particular user/system interactions, such as found in naturally occurring dialogues. However, two questions have typically remained unexamined: 1) exactly what kind of interface tasks can knowledge of a user's plans be used to support across communication modalities, and 2) how can such tasks in turn constrain development of plan recognition algorithms? In this paper we present a concrete exploration of these issues. In particular, we provide an assessment of plan recognition, with respect to the use of plan recognition in enhancing user interfaces. We clarify how use of a user model containing plans makes interfaces more intelligent and interactive (by providing an intelligent assistant that supports such tasks as advice generation, task completion, context-sensitive responses, error detection and recovery). We then show how interface tasks in turn provide constraints that must be satisfied in order for any plan recognizer to construct and represent a plan in ways that efficiently support these tasks. Finally, we survey how interfaces are fundamentally limited by current plan recognition approaches, and use these limitations to identify and motivate current research. Our research is developed in the context of CHECS, a plan-based design interface. [ABSTRACT FROM AUTHOR]

This paper presents a mechanism which infers a user's plans from his/her utterances by directing the inference process towards the more likely interpretations of a speaker's statements among many possible interpretations. Our mechanism uses Bayesian theory of probability to assess the likelihood of an interpretation, and it complements this assessment by taking into consideration two aspects of an interpretation: its coherence and its information content. The coherence of an interpretation is determined by the relationships between the different statements in the discourse. The information content of an interpretation is a measure of how well defined the interpretation is in terms of the actions to be performed on the basis of this interpretation. This measure is used to guide the inference process towards interpretations with higher information content. The information content of an interpretation depends on the specificity and the certainty of the inferences in it, where the certainty of an inference depends on the knowledge on which the inference is based. Our mechanism has been developed for use in task-oriented consultation systems. The particular domain that we have chosen for exploration is that of travel booking. [ABSTRACT FROM AUTHOR]