In this thesis it is posed that the central object of preference discovery is a co-creative process in which the Other can be represented by a machine. It explores efficient methods to enhance... Show moreIn this thesis it is posed that the central object of preference discovery is a co-creative process in which the Other can be represented by a machine. It explores efficient methods to enhance introverted intuition using extraverted intuition's communication lines. Possible implementations of such processes are presented using novel algorithms that perform divergent search to feed the users' intuition with many examples of high quality solutions, allowing them to take influence interactively. The machine feeds and reflects upon human intuition, combining both what is possible and preferred. The machine model and the divergent optimization algorithms are the motor behind this co-creative process, in which machine and users co-create and interactively choose branches of an ad hoc hierarchical decomposition of the solution space.The proposed co-creative process consists of several elements: a formal model for interactive co-creative processes, evolutionary divergent search, diversity and similarity, data-driven methods to discover diversity, limitations of artificial creative agents, matters of efficiency in behavioral and morphological modeling, visualization, a connection to prototype theory, and methods to allow users to influence artificial creative agents. This thesis helps putting the human back into the design loop in generative AI and optimization. Show less
This thesis is about augmented reality (AR). AR is commonly considered a technology that integrates virtual images into a user’s view of the real world. Yet, this thesis is not about such... Show moreThis thesis is about augmented reality (AR). AR is commonly considered a technology that integrates virtual images into a user’s view of the real world. Yet, this thesis is not about such technologies. We believe a technology-based notion of AR is incomplete. In this thesis, we challenge the technology-oriented view, provide new perspectives on AR and propose a different understanding. We argue that AR is characterized by the relationships between the virtual and the real and approach AR from a fundamental, experience-focused view. By doing so, we create an unusually broad and diverse image of what AR is, or arguably could be. We discuss the fundamental characteristics of AR and the many possible manifestations it can take and propose new, imaginative AR environments that have no counterpart in a purely physical world. Show less
The purpose of this study was the prospective comparison of objective and subjective effects of target volume region of interest (ROI) delineation using mouse-keyboard and pen-tablet user input... Show moreThe purpose of this study was the prospective comparison of objective and subjective effects of target volume region of interest (ROI) delineation using mouse-keyboard and pen-tablet user input devices (UIDs). The study was designed as a prospective test/retest sequence, with Wilcoxon signed rank test for matched-pair comparison. Twenty-one physician-observers contoured target volume ROIs on four standardized cases (representative of brain, prostate, lung, and head and neck malignancies) twice: once using QWERTY keyboard/scroll-wheel mouse UID and once with pen-tablet UID (DTX2100, Wacom Technology Corporation, Vancouver, WA, USA). Active task time, ROI manipulation task data, and subjective survey data were collected. One hundred twenty-nine target volume ROI sets were collected, with 62 paired pen-tablet/mouse-keyboard sessions. Active contouring time was reduced using the pen-tablet UID, with mean +/- SD active contouring time of 26 +/- 23 min, compared with 32 +/- 25 with the mouse (p a parts per thousand currency signaEuro parts per thousand 0.01). Subjective estimation of time spent was also reduced from 31 +/- 26 with mouse to 27 +/- 22 min with the pen (p = 0.02). Task analysis showed ROI correction task reduction (p = 0.045) and decreased panning and scrolling tasks (p < 0.01) with the pen-tablet; drawing, window/level changes, and zoom commands were unchanged (p = n.s.) Volumetric analysis demonstrated no detectable differences in ROI volume nor intra- or inter-observer volumetric coverage. Fifty-two of 62 (84%) users preferred the tablet for each contouring task; 5 of 62 (8%) denoted no preference, and 5 of 62 (8%) chose the mouse interface. The pen-tablet UID reduced active contouring time and reduced correction of ROIs, without substantially altering ROI volume/coverage. Show less
In this thesis we have studied the influence of emotion on learning. We have used computational modelling techniques to do so, more specifically, the reinforcement learning paradigm. Emotion is... Show moreIn this thesis we have studied the influence of emotion on learning. We have used computational modelling techniques to do so, more specifically, the reinforcement learning paradigm. Emotion is modelled as artificial affect, a measure that denotes the positiveness versus negativeness of a situation to an artificial agent in a reinforcement learning setting. We have done a range of different experiments to study the effect of affect on learning, including the effect on learning if affect is used to control the exploration behaviour of the agent and the effect on learning when affect is communicated by a human (though real-time analysis of that human__s facial expressions) to a simulated robot. We conclude that affect is a useful concept to consider in adaptive agents that learn based on reinforcement learning and that in some cases affect can indeed help the learning process. Further, affective modelling in this way can help understand the psychological processes that underlie influences of affect on cognition. Finally, we have developed a formal notation for a specific type of emotion theory, i.e., cognitive appraisal theory. Show less
