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Personalizing Autonomous Driving with Rich Human Guidance
Full text linkWith progress in enabling autonomous cars to drive safely on the road, it is time to ask how should they be driving. This dissertation focuses on learning the desired objective function for autonomous cars with the goal of personalizing autonomous driving: drive following the passenger’s preferences across diverse environments. Traditionally autonomous cars have been trained using expert demonstrations, with an implicit assumption that the demonstrations are truly representative of optimal driving. Personalizing autonomous driving under this assumption would mean using Inverse Reinforcement Learning (IRL) to learn the objective function latent in the user’s own demonstration and then adopt the user’s own driving style. In this thesis, we question this assumption and propose algorithmic solutions for personalizing driving styles without demonstration data. Through user studies in a simulated driving environment, we first show that people do not want their autonomous cars to drive like them: they want a significantly more defensive car. Next we formalize driving preference as reward functions and propose several algorithms to learn them interactively from an alternative form of human guidance: Preference-based Learning. In Preference-based reward learning we show users several trajectory pairs sequentially and ask them to indicate their preference in each pair. This has been shown to be effective for learning reward functions in absence of demonstrations. Simple preference is, however, far less informative than all the demonstration data. The key contribution of this thesis is an algorithmic framework that leverages computational models of human behavior to enable learning from richer preference queries where response to each query contains more information than just a comparison. We propose different forms of rich preference queries. We ask people not only what they prefer, but also why they prefer. We design new queries to learn more complex reward functions that can potentially represent preferences in non-stationary environments. We introduce reward dynamics as a mixture of reward functions and parameters that govern how preferences change in response to the dynamics of the environment. We develop a unified formalism for treating all forms of human guidance as observations about the true preferences and use this formalism to derive objective functions for actively generating rich queries. We show empirically through simulations and also with user studies that richer preference queries can learn driving preference more accurately than comparison-alone queries. We also discover that richer queries not only speed up preference learning in practice but also offer more transparency into the decision-making algorithms of the autonomous car, thus enhancing people’s trust in the system. Although the human- robot system of choice in this thesis is autonomous car, our algorithmic solutions apply to personalizing other human-robot systems where the robot is a dynamical system that should match human preference and where demonstrations are unavailable due to complexity of robot operation or disparity between preferences and demonstrations
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Enabling Efficient, Responsive, and Resilient Buildings: Collaboration Between the United States and India
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Critical Simulation Based Evaluation of Thermally Activated Building Systems (TABS) Design Models
Full text linkThermally Activated Building Systems (TABS) is a recognized low-energy HVAC system. Sizing of these systems is complex due to their slow thermal response. Limited cooling capacity of these systems and inadequacy of conventional sizing method, that assumes high factor of safety, is preventing early adoption of these systems. TABS, however, is proven to be energy-efficient and capable of preserving comfort in several commercial buildings of Europe. There is, however no comprehensive case study report on comfort performance of TABS in the US. With this being the background, my dissertation aims to identify and recommend a design method for TABS that balances between accuracy of multivariable complex design models, high computational cost of models requiring an iterative approach and computational ease of simple single to bivariate linear design models. The dissertation work involved: 1) a systematic qualitative review of seven TABS design models from the literature, and 2) a simulation based quantitative comfort performance assessment of three shortlisted design models. I reviewed seven design and control models and characterized them systematically with an aim to investigate their applicability in various design scenarios and at different design stages. All of these models size water supply temperature (WST) as this parameter will be used for selection and sizing of the cooling plant or the condenser unit. The design scenarios include variable internal heat gain, different building thermal mass, varying pump operating hours and varying solar gain due to orientation. Other parameters affecting cooling load and thermal performance of TABS that were held constant in this study included window-to-wall area ratio, zone volume, construction insulation, supply air temperature and volume flow rate of the ventilation system, external shading, location, TABS mass flow rate, pipe layout, active surface configuration and TABS thermal properties. I considered three design stages: feasibility study, early design decisions, and detailed design sizing and the selection criteria are reliability and ease of implementation. Results of the qualitative analysis indicated that based on the above-mentioned criteria, a hybrid model recommended by ISO 11855 is the best candidate for detailed design and sizing of the cooling plant. An outdoor temperature (Toa) compensated model, a zone operative temperature (OT) feedback based model and the hybrid model from ISO 11855 were isolated for transient simulation based quantitative evaluation in terms of a novel comfort exceedance metric. This metric accounts for both duration and severity of discomfort and is weighted by instantaneous occupancy. For comfort analysis in terms of zone OT, zone RH was maintained using humidistats. TABS was the only cooling system in the building. Twelve simulations were carried out in a standard 5 zone small office building for CZ03 in EnergyPlus v7.0 under 2 different heat gains and 2 construction types. Results of the simulation study indicated that both the Toa compensated model and zone operative temperature feedback based model provided equally good comfort in 14 out of 20 design scenarios including zone orientation. However, the zone OT feedback model responded better to the heat gain and thermal mass conditions as expected, and is therefore recommended as a more robust model for early and detailed design phase implementation. The hybrid model recommended by ISO 11855 resulted in comfort exceedance of 10% to 48%, while the recommended threshold exceedance for this study was 3-5%. This model also resulted in significantly reduced discomfort using 24 hours hydronic cooling energy of TABS instead of the design day 24 hours cooling energy of convective system
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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