Index Catalog // ScholarsArchive@OSU

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

Semantic embodied navigation : developing agents that navigate from language and vision

Creator:: Krantz, Jacob
Abstract:: Autonomous robotic agents are on their way to becoming in-home personal assistants, construction assistants, and warehouse workers. The degree of autonomy of such systems is reflected by the manner in which we specify goals to them; the abstraction of low-level commands to high-level goals goes hand-in-hand with increased autonomy. In...
Resource Type:: Dissertation

Investigating Latent State and Uncertainty Representations in Reinforcement Learning

Creator:: Koul, Anurag
Abstract:: Learning latent space representations of high-dimensional world states has been at the core of recent rapid growth in reinforcement learning(RL). At the same time, RL algo- rithms have suffered from ignored uncertainties in the predicted estimates of model-free or model-based methods. In our work, we investigate both of these aspects...
Resource Type:: Dissertation

Characterizing and Addressing Dataset Shift with Deep Learning

Creator:: Olson, Matthew L.
Abstract:: This dissertation delves into understanding, characterizing, and addressing dataset shift in deep learning, a pervasive issue for deployed machine learning systems. Integral aspects of the problem are examined: We start with the use of counterfactual explanations in order to characterize the behavior of deep reinforcement learning agents in visual input...
Resource Type:: Dissertation

Assessing and Finding Faults in AI: Two Empirical Studies

Creator:: Khanna, Roli
Abstract:: With the advent of Artificial Intelligence (AI) in every sphere of life in today's day and age, it has become increasingly important for non-AI experts to be able to comprehend the underlying logic of how AI systems work, assess them and find faults in these systems, particularly when they are...
Resource Type:: Masters Thesis

Improving User Mental Models of XAI Systems with Inclusive Design Approaches

Creator:: Hamid, Md Montaser
Abstract:: Explainable Artificial Intelligence (XAI) systems aim to improve users’ understanding of AI but rarely consider the inclusivity aspects of XAI. Without inclusive approaches, improving explanations might not work well for everyone. This study investigates leveraging users’ diverse problem-solving styles as an inclusive strategy to fix an XAI prototype, with the...
Resource Type:: Masters Thesis

SocioEconomicMag Meets a Platform for SES-Diverse College Students: A Case Study

Creator:: Agarwal, Puja
Abstract:: Emerging research shows that individual differences in how people use technology sometimes cluster by socioeconomic status (SES) and that when technology is not socioeconomically inclusive, low-SES individuals may abandon it. To understand how to improve technology’s SES-inclusivity, we present a multi-phase case study on SocioEconomicMag (SESMag), an emerging inspection method...
Resource Type:: Masters Thesis

Uncertainty in Deep Learning with Implicit Neural Networks

Creator:: Ratzlaff, Neale
Abstract:: The ability to extract uncertainties from predictions is crucial for the adoption of deep learning systems to safety-critical applications. Uncertainty estimates can be used as a failure signal, which is necessary for automating complex tasks where safety is a concern. Furthermore, current deep learning systems do not provide uncertainty estimates,...
Resource Type:: Dissertation

Theory and Implementation of a Variational Database Management System

Creator:: Ataei, Parisa S.
Abstract:: In this thesis, I present the variational database management system, a formal framework and its implementation for representing variation in relational databases and managing variational information needs. A variational database is intended to support any kind of variation in a database. Specific kinds of variation in databases have already been...
Resource Type:: Dissertation

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

ScholarsArchive@OSU

Auxiliary Tasks for Efficient Learning of Point-Goal Navigation

Semantic embodied navigation : developing agents that navigate from language and vision

Investigating Latent State and Uncertainty Representations in Reinforcement Learning

Characterizing and Addressing Dataset Shift with Deep Learning

Assessing and Finding Faults in AI: Two Empirical Studies

Improving User Mental Models of XAI Systems with Inclusive Design Approaches

SocioEconomicMag Meets a Platform for SES-Diverse College Students: A Case Study

Uncertainty in Deep Learning with Implicit Neural Networks

Theory and Implementation of a Variational Database Management System

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

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