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  • Diversity combining ARQ over the m(> 2)-ary unidirectional channel

    Creator:
    Elarief, Noha
    Abstract:
    In diversity combining automatic repeat request (ARQ), erroneous packets are combined together forming a single, more reliable, packet. In this thesis, we give a diversity combining scheme for the m-ary unidirectional channel. A system using the given scheme with a t-unidirectional error detecting code is able to correct up to...
    Resource Type:
    Masters Thesis
    Full Text:
    , no. 11, pp.. 63-69, Nov. 1985. [7] M. Anantha, B. Bose and L. G. Tallini, “ARQ Protocols and

  • The Effectiveness of Using Robotics for Career Technology Education in a Middle School STE(A)M Course

    Creator:
    Bodle, Ernie
    Abstract:
    Using robotics in education allows students to become familiar with multiple topics in science, technology, engineering, and mathematics (STEM). With the use of robotic educational tools in the 8th – 12th grade classrooms, such as Sphero, Anki Cozmo, and Lego Mindstorms, few devices allow students to build the robots’ electrical...
    Resource Type:
    Masters Thesis
    Full Text:
    . Title: The Effectiveness of Using Robotics for Career Technology Education in a Middle School STE(A)M

  • Explanations and Processes to Enable Humans to Assess AI with Respect to Manipulable Properties

    Creator:
    Dodge, Jonathan E.
    Abstract:
    Assessing AI systems is difficult. Humans rely on AI systems in increasing ways, both visible and invisible, meaning a variety of stakeholders need a variety of assessment tools (e.g., a professional auditor, a developer, and an end user all have different needs). We posit that it is possible to provide...
    Resource Type:
    Dissertation
    Full Text:
    . . . . . . . . . . . . . 159 F Log Appendix - Computing a target tensor with CNN Agent . . . . . . . . 162 G How to

  • A methodology to reduce the strain on hydro turbines using advanced life extending control of multiple energy storage systems

    Creator:
    Brosig, Sean G.
    Abstract:
    Over the last 20 years, there has been rapid growth in the amount of installed wind power in the Pacific Northwest, specifically in the Columbia River Gorge. The variable and non-dispatchable nature of this resource requires that it be balanced in some form by other sources on the grid. In...
    Resource Type:
    Masters Thesis
    Full Text:
    AN ABSTRACT OF THE THESIS OF Sean G. Brosig for the degree of Master of Science in Electrical and

  • Model-based approximation methods for reinforcement learning

    Creator:
    Wang, Xin
    Abstract:
    The thesis focuses on model-based approximation methods for reinforcement learning with large scale applications such as combinatorial optimization problems. First, the thesis proposes two new model-based methods to stablize the value–function approximation for reinforcement learning. The first one is the BFBP algorithm, a batch-like reinforcement learning process which iterates between...
    Resource Type:
    Dissertation
    Full Text:
    Methods for Reinforcement Learning. Abstract approved: Thomas G Dietterich The thesis focuses on model

  • Electronic Stability of Metal Halide Perovskites

    Creator:
    Hong, Min Ji
    Abstract:
    Despite near unanimous opinion on the consequences of climate change by scientific community, the rate at which carbon is emitted into the atmosphere continues to increase. The need for a clean and sustainable source of energy is therefore one of humankind's most urgent challenges. Solar energy is the most abundant...
    Resource Type:
    Dissertation
    Full Text:
    . ...................................................... 47 Figure 5.1Time resolved microwave conductivity (TRMC) transients: photo- conductance (∆𝐺) as a

  • Improving automated email tagging with implicit feedback

    Creator:
    Sorower, Mohammad Shahed
    Abstract:
    Machine learning systems are generally trained offline using ground truth data that has been labeled by experts. However, these batch training methods are not a good fit for many applications, especially in the cases where complete ground truth data is not available for offline training. In addition, batch methods do...
    Resource Type:
    Dissertation
    Full Text:
    : Improving Automated Email Tagging with Implicit Feedback Abstract approved: Thomas G. Dietterich Machine

  • Anomaly Detection and Probabilistic Diagnosis for Automated Data Quality Control

    Creator:
    Zemicheal, Tadesse H.
    Abstract:
    Advances in sensor technology are greatly expanding the range of quantities that can be measured while simultaneously reducing the cost. However, deployed sensors drift out of calibration and fail, so every sensor network requires quality control procedures to promptly detect these failures. To address these problems, we propose a two-level...
    Resource Type:
    Dissertation
    Full Text:
    : Thomas G. Dietterich Advances in sensor technology are greatly expanding the range of quantities that

  • Learning MDP action models via discrete mixture trees

    Creator:
    Wynkoop, Michael S.
    Abstract:
    This thesis addresses the problem of learning dynamic Bayesian network (DBN) models to support reinforcement learning. It focuses on learning regression tree models of the conditional probability distributions of the DBNs. Existing algorithms presume that the stochasticity in the domain can be modeled as a deterministic function with additive noise....
    Resource Type:
    Masters Thesis
    Full Text:
    , 2008. Title: Learning MDP Action Models via Discrete Mixture Trees Abstract approved: Thomas G

  • Efficient training and feature induction in sequential supervised learning

    Creator:
    Hao, Guohua
    Abstract:
    Sequential supervised learning problems arise in many real applications. This dissertation focuses on two important research directions in sequential supervised learning: efficient training and feature induction. In the direction of efficient training, we study the training of conditional random fields (CRFs), which provide a flexible and powerful model for sequential...
    Resource Type:
    Dissertation
    Full Text:
    Feature Induction in Sequential Supervised Learning Abstract approved: Thomas G. Dietterich Sequential

  • Creating, Understanding and Applying Machine Learning Models of Multiple Species

    Creator:
    Griffioen, Arwen Twinkle E.
    Abstract:
    Many problems in ecology and conservation biology can be formulated and solved using machine learning algorithms for multi-label classification. This dissertation addresses three topics related to predicting the distributions of multiple species. It improves existing methods and proposes a new modeling paradigm to address the multi-species, multi-label problem. The first...
    Resource Type:
    Dissertation
    Full Text:
    Species Abstract approved: ______________________________________________________ Thomas G

  • A study of methods for fine-grained object classification of arthropod specimens

    Creator:
    Lin, Junyuan
    Abstract:
    Object categorization is one of the fundamental topics in computer vision research. Most current work in object categorization aims to discriminate among generic object classes with gross differences. However, many applications require much finer distinctions. This thesis focuses on the design, evaluation and analysis of learning algorithms for fine- grained...
    Resource Type:
    Masters Thesis
    Full Text:
    Fine-grained Object Classification of Arthropod Specimens Abstract approved: Thomas G. Dietterich

  • Three methods for estimating subpixel cover fractions in coarse resolution imagery

    Creator:
    Damon, Diane L.
    Abstract:
    Coarse resolution imagery, such as that produced by the MODIS instrument, poses the challenge of estimating sub-pixel proportions of di erent land cover types. This problem is di cult because of the variety and variability of vegetation within individual pixels. This thesis describes and compares two existing algorithms for estimating...
    Resource Type:
    Masters Thesis
    Full Text:
    . D17, pp. 19009–19021, 1992. [9] DeFries, R. S., Townshend, J. R. G., and Hansen, M. C., “Continuous

  • Simulator-Defined MDP Planning with Applications in Natural Resource Management

    Creator:
    Alkaee Taleghan, Majid
    Abstract:
    This work is inspired by problems in natural resource management centered on the challenge of invasive species. Computing optimal management policies for maintaining ecosystem sustainable is challenging. Many ecosystem management problems can be formulated as MDP (Markov Decision Process) planning problems. In a simulator-defined MDP, the Markovian dynamics and rewards...
    Resource Type:
    Dissertation
    Full Text:
    G. Dietterich This work is inspired by problems in natural resource management centered on the

  • Image features and learning algorithms for biological, generic and social object recognition

    Creator:
    Zhang, Wei
    Abstract:
    Automated recognition of object categories in images is a critical step for many real-world computer vision applications. Interest region detectors and region descriptors have been widely employed to tackle the variability of objects in pose, scale, lighting, texture, color, and so on. Different types of object recognition problems usually require...
    Resource Type:
    Dissertation
    Full Text:
    : ______________________________________________________ Thomas G. Dietterich Automated recognition of object categories in images is a critical

  • Applying machine learning for prediction, recommendation, and integration

    Creator:
    Bao, Xinlong
    Abstract:
    This dissertation explores the idea of applying machine learning technologies to help computer users find information and better organize electronic resources, by presenting the research work conducted in the following three applications: FolderPredictor, Stacking Recommendation Engines, and Integrating Learning and Reasoning. FolderPredictor is an intelligent desktop software tool that helps...
    Resource Type:
    Dissertation
    Full Text:
    approved: Thomas G. Dietterich This dissertation explores the idea of applying machine learning

  • Learning cost-sensitive diagnostic policies from data

    Creator:
    Zubek, Valentina Bayer
    Abstract:
    In its simplest form, the process of diagnosis is a decision-making process in which the diagnostician performs a sequence of tests culminating in a diagnostic decision. For example, a physician might perform a series of simple measurements (body tem- perature, weight, etc.) and laboratory measurements (white blood count, CT scan,...
    Resource Type:
    Dissertation
    Full Text:
    . Title: Learning Cost-Sensitive Diagnostic Policies from Data. Abstract approved: Thomas G. Dietterich

  • Machine Learning Methods for Computational Sustainability

    Creator:
    Liu, Liping
    Abstract:
    Maintaining the sustainability of the earth’s ecosystems has attracted much attention as these ecosystems are facing more and more pressure from human activities. Machine learning can play an important role in promoting sustainability as a large amount of data is being collected from ecosystems. There are at least three important...
    Resource Type:
    Dissertation
    Full Text:
    Methods for Computational Sustainability Abstract approved: Thomas G. Dietterich Maintaining the

  • Activity recognition in desktop environments

    Creator:
    Shen, Jianqiang
    Abstract:
    Knowledge workers are struggling in the information flood. There is a growing interest in intelligent desktop environments that help knowledge workers organize their daily life. Intelligent desktop environments allow the desktop user to define a set of “activities” that characterize the user’s desktop work. These environments then attempt to identify...
    Resource Type:
    Dissertation
    Full Text:
    i s i n g s t u d e n t s h e n p r o j e c t T a s k T r a c e r c o m m e n t s o n t h e s i

  • A Benchmarking Study of Unsupervised Anomaly Detection Algorithms

    Creator:
    Emmott, Andrew F.
    Abstract:
    It is common practice in the unsupervised anomaly detection literature to create experimental benchmarks by sampling from existing supervised learning datasets. We seek to improve this practice by identifying four dimensions important to real-world anomaly detection applications --- point difficulty, clusteredness of anomalies, relevance of features, and relative frequency of...
    Resource Type:
    Masters Thesis
    Full Text:
    . . . . . . . . . . . . . . . . . . . . . 111 G Supplemental Tables for Chapter 7 . . . . . . . . . . . . . . . . . . . 116 LIST OF TABLES

  • A probabilistic model for anomaly detection in remote sensor streams

    Creator:
    Dereszynski, Ethan W.
    Abstract:
    Remote sensors are becoming the standard for observing and recording ecological data in the field. Such sensors can record data at fine temporal resolutions, and they can operate under extreme conditions prohibitive to human access. Unfortunately, sensor data streams exhibit many kinds of errors ranging from corrupt communications to partial...
    Resource Type:
    Masters Thesis
    Full Text:
    Remote Sensor Streams Abstract approved: Thomas G. Dietterich Remote sensors are becoming the standard

  • Sequential supervised learning and conditional random fields

    Creator:
    Ashenfelter, Adam J.
    Abstract:
    Supervised learning is concerned with discovering the relationship between example sets of features and their corresponding classes. The traditional supervised learning formulation assumes that all examples are independent from one another. The order of the examples contains no information. Nonetheless, many problems have a sequential nature. Classifiers for these problems...
    Resource Type:
    Masters Thesis
    Full Text:
    Supervised Learning and Conditional Random Fields. Abstract approved: Thomas G. Dietterich Supervised

  • Protein secondary structure prediction using conditional random fields and profiles

    Creator:
    Shen, Rongkun
    Abstract:
    Protein secondary structure prediction plays a pivotal role in predicting protein folding in three-dimensions. Its task is to assign each residue one of the three secondary structure classes helix, strand, or random coil. This is an instance of the problem of sequential supervised learning in machine learning. This thesis describes...
    Resource Type:
    Masters Thesis
    Full Text:
    Fields and Profiles Abstract approved: Thomas G. Dietterich

  • Constraining Bayesian network learning with qualitative models

    Creator:
    Altendorf, Eric E.
    Abstract:
    Machine learning encompasses probabilistic and statistical techniques that can build models from large quantities of extensional information (examples) with minimal dependence on intensional information (domain knowledge). This focus of machine learning is reflected in the never-ending quest for "off-the-shelf" classifiers. To generalize to unseen data, however, we must make use...
    Resource Type:
    Masters Thesis
    Full Text:
    Network Learning with Qualitative Models. Abstract approved: Thomas G. Dietterich Machine learning

  • Evaluating online text classification algorithms for email prediction in TaskTracer

    Creator:
    Keiser, Victoria L.
    Abstract:
    This paper examines how six online multiclass text classification algorithms perform in the domain of email tagging within the TaskTracer system. TaskTracer is a project-oriented user interface for the desktop knowledge worker. TaskTracer attempts to tag all documents, web pages, and email messages with the projects to which they are...
    Resource Type:
    Masters Thesis
    Full Text:
    Knowledge Workers. 2009. [5] Dragunov, A. N., Dietterich, T. G., Johnsrude, K., McLaughlin, M., Li, L

  • The Familiarity Hypothesis: Explaining the Behavior of Deep Learning Methods in Out-of-Distribution Detection

    Creator:
    Guyer, Alexander
    Abstract:
    Many object recognition applications require detecting and responding to objects drawn from a different distribution from that of the training data. This task is referred to as out-of-distribution (OOD) detection, and it is often formulated as an outlier detection problem wherein the probability distribution of the known data P(X) is...
    Resource Type:
    Masters Thesis
    Full Text:
    : ______________________________________________________ Thomas G. Dietterich Many object recognition applications require detecting and

  • Probabilistic models for quality control in environmental sensor networks

    Creator:
    Dereszynski, Ethan W.
    Abstract:
    Networks of distributed, remote sensors are providing ecological scientists with a view of our environment that is unprecedented in detail. However, these networks are subject to harsh conditions, which lead to malfunctions in individual sensors and failures in network communications. This behavior manifests as corrupt or missing measurements in the...
    Resource Type:
    Dissertation
    Full Text:
    : Probabilistic Models for Quality Control in Environmental Sensor Networks Abstract approved: Thomas G

  • Machine learning methods for public policy : simulation, optimization, and visualization

    Creator:
    McGregor, Sean
    Abstract:
    Society faces many complex management problems, particularly in the area of shared public resources such as ecosystems. Existing decision making processes are often guided by personal experience and political ideology rather than state-of-the-art scientific understanding. This dissertation envisions a future in which multiple stakeholders are provided with computational tools for...
    Resource Type:
    Dissertation
    Full Text:
    Methods for Public Policy: Simulation, Optimization, and Visualization Abstract approved: Thomas G

  • Calibrating recurrent sliding window classifiers for sequential supervised learning

    Creator:
    Joshi, Saket Subhash
    Abstract:
    Sequential supervised learning problems involve assigning a class label to each item in a sequence. Examples include part-of-speech tagging and text-to-speech mapping. A very general-purpose strategy for solving such problems is to construct a recurrent sliding window (RSW) classifier, which maps some window of the input sequence plus some number...
    Resource Type:
    Masters Thesis
    Full Text:
    as a function of input and output con- text. 7 6 G) C 0 C.) 0. 02 0 1 2 3 4 5 6 7 input

  • Equivalent circuit modeling of on-chip magnetic devices based on terminal measurements

    Creator:
    Gaskill, Steven G.
    Abstract:
    The addition of thin-film alloy magnetic materials to integrated circuit processing enables a number of novel monolithic circuits. Examples include fully integrated magnetic field sensors, signal and power galvanic isolation circuits, and power supplies on chip (PwrSoC). There are several benefits to integrating these traditionally off-chip devices, including improved manufacturability,...
    Resource Type:
    Dissertation
    Full Text:
    AN ABSTRACT OF THE DISSERTATION OF Steven G. Gaskill for the

  • Low-Power 12-bit Quasi-Passive Segmented DAC Implemented in 130nm CMOS Technology

    Creator:
    Pierce, Alexander G.
    Abstract:
    This thesis work proposes a low-power 12-bit digital-to-analog converter (DAC) designed in a 130nm process. The DAC to be presented is of a segmented design where the architecture is split into pipelined and thermometer coded segments. This allows for high linearity and low distortion while maintaining high speed and low...
    Resource Type:
    Masters Thesis
    Full Text:
    bandwidth fs/M where M is the number of FFT points. The theoretical noise floor can be computed by

  • Channel Estimation in TDD MU-MIMO Systems using Sub-Linear Sparse Signal Recovery Algorithms

    Creator:
    Barry, David G.
    Abstract:
    Massive Multiple-User Miltiple-Input Multiple-Output (MU-MIMO) wireless communication systems incorporate promising advanced strong technologies for upcoming 5G communications. To obtain some of the high spectrum and energy e ciencies bonuses brought by MU-MIMO systems, the ability to obtain Channel State information, especially on the receiver side (CSI), is important. To minimize...
    Resource Type:
    Masters Thesis
    Full Text:
    control A to manipulate and recover X in a below-linear time space, with M < N . A simple solution to

  • Auxiliary Tasks for Efficient Learning of Point-Goal Navigation

    Creator:
    Desai, Saurabh Satish
    Abstract:
    Top-performing approaches to embodied AI tasks like point-goal navigation often rely on training agents via reinforcement learning over tens of millions (or even billions) of experiential steps – learning neural agents that map directly from visual observations to actions. In this work, we question whether these extreme training durations are...
    Resource Type:
    Masters Thesis
    Full Text:
    for Efficient Learning of Point-Goal Navigation Abstract approved: Stefan M. Lee Top-performing

  • Understanding and supporting end-user debugging strategies

    Creator:
    Grigoreanu, Valentina I.
    Abstract:
    End users' programs are fraught with errors, costing companies millions of dollars. One reason may be that researchers and tool designers have not yet focused on end-user debugging strategies. To investigate this possibility, this dissertation presents eight empirical studies and a new strategy-based end-user debugging tool for Excel, called StratCel....
    Resource Type:
    Dissertation
    Full Text:
    : ______________________________________________________ Margaret M. Burnett End users’ programs are fraught with errors, costing companies millions

  • Information Theoretical Analysis of Self-Similar Trees

    Creator:
    Chunikhina, Evgenia V.
    Abstract:
    Tree-like patterns are ubiquitous in nature. Botanical trees, river networks, and blood systems are the most well-known examples of complex hierarchical systems met in observations. Interestingly, many of such systems exhibit statistical self-similarity. There are two main types of self-similarity: Horton self-similarity and Tokunaga self-similarity. Although there is an increased...
    Resource Type:
    Dissertation
    Full Text:
    : Information Theoretical Analysis of Self-Similar Trees Abstract approved: Juan M. Restrepo Tree-like

  • Learning greedy policies for the easy-first framework

    Creator:
    Xie, Jun
    Abstract:
    Easy-first, a search-based structured prediction approach, has been applied to many NLP tasks including dependency parsing and coreference resolution. This approach employs a learned greedy policy (action scoring function) to make easy decisions first, which constrains the remaining decisions and makes them easier. This thesis studies the problem of learning...
    Resource Type:
    Masters Thesis
    Full Text:
    my thesis committee: Prof. Thomas G. Dietterich and Prof. Prasad Tadepalli, for their encouragement

  • Towards Pactive (Passive + Active) Sensing for Security Applications

    Creator:
    Menon, Arya
    Abstract:
    Increasing threats of terrorism and contraband smuggling have led to a growing interest in millimeter wave/ THz security sensors. Recently, systems combining active and passive sensing into one unit have been proposed where the active mode provides information on range and reflectivity, and the passive mode complements the active by...
    Resource Type:
    Dissertation
    Full Text:
    Abstract approved: ______________________________________________________ Thomas M. Weller

  • Information Foraging Theory as a Unifying Foundation for Software Engineering Research : Connecting the Dots

    Creator:
    Piorkowski, David
    Abstract:
    Empirical studies have shown that programmers spend up to one-third of their time navigating through code during debugging. Although researchers have conducted empirical studies to understand programmers’ navigation difficulties and developed tools to address those difficulties, the resulting findings tend to be loosely connected to each other. To address this...
    Resource Type:
    Dissertation
    Full Text:
    : ______________________________________________________ Margaret M. Burnett Empirical studies have shown that programmers spend up to one

  • Gender HCI issues in end-user programming

    Creator:
    Beckwith, Laura A.
    Abstract:
    Until recently, research has not considered whether the design of end-user programming environments, such as spreadsheets, multimedia authoring languages, and CAD systems, affects males and females differently. As a result, we began investigating how the two genders are impacted by end-user programming software and whether attention to gender differences is...
    Resource Type:
    Dissertation
    Full Text:
    Approved: __________________________________________________ Margaret M. Burnett Until recently

  • Effects of interruption-style on end-user programmers

    Creator:
    Robertson, T. J. (Thomas James)
    Abstract:
    This thesis presents the results of two studies that investigate the question of what interruption-styles are most appropriate for end-user programmers who are debugging programs. In the studies, end-user programmers are presented with surprises that encourage them to investigate, use, and learn about debugging devices in their programming environment. We...
    Resource Type:
    Masters Thesis
    Full Text:
    . Burnett, M., Cook, C., Pendse, 0., Rothemiel, G., Summet, J., Wallace, C. End- user software engineering

  • Modeling programmer navigation : an empirical evaluation of predictive models

    Creator:
    Piorkowski, David
    Abstract:
    Software developers frequently need to perform code maintenance tasks, but doing so requires time-consuming navigation through code. A variety of tools are aimed at easing this navigation by using models to predict places in the code that a developer might want to visit, and then providing shortcuts so that the...
    Resource Type:
    Masters Thesis
    Full Text:
    Empirical Evaluation of Predictive Models Abstract approved: Margaret M. Burnett Software

  • Behaviors and strategies in end-users' collaborative programming

    Creator:
    Liu, Zheng
    Abstract:
    Traditionally, research into end-user programming has focused on how to make programming more accessible to end users conducting the programming activities all by themselves. However, few researchers have considered introducing the concept of collaborative programming into the area of end-user programming, and how the programming environments and devices should be...
    Resource Type:
    Masters Thesis
    Full Text:
    -Users' Collaborative Programming Abstract approved: argaret M. Burnett Traditionally, research into

  • Personalizing machine learning systems with explanatory debugging

    Creator:
    Kulesza, Todd
    Abstract:
    How can end users efficiently influence the predictions that machine learning systems make on their behalf? Traditional systems rely on users to provide examples of how they want the learning system to behave, but this is not always practical for the user, nor efficient for the learning system. This dissertation...
    Resource Type:
    Dissertation
    Full Text:
    Explanatory Debugging Abstract approved: Margaret M. Burnett How can end users efficiently influence the

  • Interactive fault localization techniques to empower the debugging efforts of end-user programmers

    Creator:
    Ruthruff, Joseph Ronald
    Abstract:
    End users develop more software than any other group of programmers, using software authoring devices such as e-mail filtering editors, by-demonstration macro builders, and spreadsheet environments. Despite this, there has been only a little research on finding ways to help these programmers with the dependability of the software they create....
    Resource Type:
    Masters Thesis
    Full Text:
    : Margaret M. Burnett End users develop more software than any other group of programmers, using software

  • The InclusiveMag Method: A Start Towards More Inclusive Software for Diverse Populations

    Creator:
    Mendez, Christopher
    Abstract:
    How can software practitioners assess whether their software supports diverse users? Although there are empirical processes that can be used to find “inclusivity bugs” piecemeal, what is often needed is a systematic inspection method to assess software’s support for diverse populations. To help fill this gap, this thesis introduces InclusiveMag,...
    Resource Type:
    Masters Thesis
    Full Text:
    Abstract approved: ______________________________________________________ Margaret M. Burnett

  • Explanations and Information Foraging in Real-Time Strategy Games

    Creator:
    Penney, Sean J.
    Abstract:
    Assessing and understanding intelligent agents can be a difficult task for users who may lack an artificial intelligence (AI) background. A relatively new area, called “explainable AI,” is emerging to help address this problem, but little is known about how to present and structure information that an explanation system might...
    Resource Type:
    Masters Thesis
    Full Text:
    : Explanations and Information Foraging in Real-Time Strategy Games Abstract Approved: Margaret M. Burnett

  • Mental Models of Mere Mortals with Explanations of Reinforcement Learning

    Creator:
    Anderson, Andrew A.
    Abstract:
    How should reinforcement learning (RL) agents explain themselves to humans not trained in AI? To gain insights into this question, we conducted a 124 participant, four-treatment experiment to compare participants’ mental models of an RL agent in the context of a simple Real-Time Strategy (RTS) game. The four treatments isolated...
    Resource Type:
    Masters Thesis
    Full Text:
    Mere Mortals with Explanations of Reinforcement Learning Abstract approved: Margaret M. Burnett How

  • Generalizing the Idea Garden : Principles and Contexts

    Creator:
    Jernigan, William
    Abstract:
    In previous work, the Idea Garden was created to help those relatively new to programming overcome their barriers in CoScripter. The goal of this thesis was to generalize the Idea Garden's success to other users and environments. We present a set of principles on how to help EUPs like this...
    Resource Type:
    Masters Thesis
    Full Text:
    Abstract approved: ______________________________________________________ Margaret M. Burnett

  • Practices for Engineering Gender-Inclusivity into Software

    Creator:
    Hilderbrand, Claudia
    Abstract:
    Although the need for gender-inclusivity in software itself is gaining attention among both SE researchers and SE practitioners, and methods have been published to help, little has been reported on how to make such methods work in real-world settings. For example, how do busy software practitioners use such methods in...
    Resource Type:
    Masters Thesis
    Full Text:
    reports for staff L 7 technologies M 2 Education platform for instructors N >12 An IT-support

  • How does AAR/AI Support Problem Solvers with Diverse Behaviors and Cognitive Styles?

    Creator:
    Dikkala, Rupika
    Abstract:
    "What’s wrong with this AI?" Explainable AI (XAI) researchers are moving beyond explaining an AI’s actions, to helping users detect an AI’s failures. However this detection may not be enough—for actionability, we often need to pinpoint which part failed. We investigate how AAR/AI, a structured assessment process, supports users with...
    Resource Type:
    Masters Thesis
    Full Text:
    : Margaret M. Burnett “What’s wrong with this AI?” Explainable AI (XAI) researchers are moving beyond ex