Matching Items (58)
Filtering by
- All Subjects: artificial intelligence
- All Subjects: Children
- Creators: Computer Science and Engineering Program
- Creators: Department of Psychology
- Member of: Barrett, The Honors College Thesis/Creative Project Collection
- Member of: Theses and Dissertations
Description
Robots are often used in long-duration scenarios, such as on the surface of Mars,where they may need to adapt to environmental changes. Typically, robots have been built specifically for single tasks, such as moving boxes in a warehouse or surveying construction sites. However, there is a modern trend away from human hand-engineering and toward robot learning. To this end, the ideal robot is not engineered,but automatically designed for a specific task. This thesis focuses on robots which learn path-planning algorithms for specific environments. Learning is accomplished via genetic programming. Path-planners are represented as Python code, which is optimized via Pareto evolution. These planners are encouraged to explore curiously and efficiently. This research asks the questions: “How can robots exhibit life-long learning where they adapt to changing environments in a robust way?”, and “How can robots learn to be curious?”.
ContributorsSaldyt, Lucas P (Author) / Ben Amor, Heni (Thesis director) / Pavlic, Theodore (Committee member) / Computer Science and Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
This paper is centered on the use of generative adversarial networks (GANs) to convert or generate RGB images from grayscale ones. The primary goal is to create sensible and colorful versions of a set of grayscale images by training a discriminator to recognize failed or generated images and training a generator to attempt to satisfy the discriminator. The network design is described in further detail below; however there are several potential issues that arise including the averaging of a color for certain images such that small details in an image are not assigned unique colors leading to a neutral blend. We attempt to mitigate this issue as much as possible.
ContributorsLobo, Ian (Co-author) / Koleber, Keith (Co-author) / Markabawi, Jah (Co-author) / Masud, Abdullah (Co-author) / Yang, Yingzhen (Thesis director) / Wang, Yancheng (Committee member) / Computer Science and Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
The objective of this research is to determine an approach for automating the learning of the initial lexicon used in translating natural language sentences to their formal knowledge representations based on lambda-calculus expressions. Using a universal knowledge representation and its associated parser, this research attempts to use word alignment techniques to align natural language sentences to the linearized parses of their associated knowledge representations in order to learn the meanings of individual words. The work includes proposing and analyzing an approach that can be used to learn some of the initial lexicon.
ContributorsBaldwin, Amy Lynn (Author) / Baral, Chitta (Thesis director) / Vo, Nguyen (Committee member) / Industrial, Systems (Contributor) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2015-05
Description
Food safety is vital to the well-being of society; therefore, it is important to inspect food products to ensure minimal health risks are present. A crucial phase of food inspection is the identification of foreign particles found in the sample, such as insect body parts. The presence of certain species of insects, especially storage beetles, is a reliable indicator of possible contamination during storage and food processing. However, the current approach to identifying species is visual examination by human analysts; this method is rather subjective and time-consuming. Furthermore, confident identification requires extensive experience and training. To aid this inspection process, we have developed in collaboration with FDA analysts some image analysis-based machine intelligence to achieve species identification with up to 90% accuracy. The current project is a continuation of this development effort. Here we present an image analysis environment that allows practical deployment of the machine intelligence on computers with limited processing power and memory. Using this environment, users can prepare input sets by selecting images for analysis, and inspect these images through the integrated pan, zoom, and color analysis capabilities. After species analysis, the results panel allows the user to compare the analyzed images with referenced images of the proposed species. Further additions to this environment should include a log of previously analyzed images, and eventually extend to interaction with a central cloud repository of images through a web-based interface. Additional issues to address include standardization of image layout, extension of the feature-extraction algorithm, and utilizing image classification to build a central search engine for widespread usage.
ContributorsMartin, Daniel Luis (Author) / Ahn, Gail-Joon (Thesis director) / Doupé, Adam (Committee member) / Xu, Joshua (Committee member) / Computer Science and Engineering Program (Contributor) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
This creative project is a children's book entitled Sheldon the Shy Tortoise. Accompanying the story is a literature review of the research on childhood shyness. The purpose of the project is to gain a better of understanding of shyness in childhood. Topics covered in the literature review include risk factors and causes, negative social and behavioral effects, impact on academics, and treatment options. Using this information, the children's book was written. It aims to be fun for children to read while also providing insight and encouragement into some of the problems related to being shy. The story features animal characters and a relatively simple plot so it is easily understandable by the target audience of late-preschool and early-elementary children. The main character, Sheldon the tortoise, is often physically and metaphorically "stuck in his shell". He wants to participate in social activities but is afraid to do so. Through a series of events and interactions, Sheldon starts to come out of his shell in every sense of the phrase. The book is illustrated using photographs of hand-crocheted stuffed animals representing each of the characters. By incorporating scholarly research into the writing process, children will hopefully be able to gain an understanding of their shyness and ways to help decrease it. Teachers should be able to better understand their shy students and understand some of the unique challenges of working with shy children. This creative project helps convey necessary information to children and families during a critical period of development.
ContributorsRyan, Amanda (Author) / Hansen, Cory (Thesis director) / Bernstein, Katie (Committee member) / Department of Speech and Hearing Science (Contributor) / Sanford School of Social and Family Dynamics (Contributor) / Department of Psychology (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Instead of providing the illusion of agency to a reader via a tree or network of prewritten, branching paths, an interactive story should treat the reader as a player who has meaningful influence on the story. An interactive story can accomplish this task by giving the player a large toolset for expression in the plot. LudoNarrare, an engine for interactive storytelling, puts "verbs" in this toolset. Verbs are contextual choices of action given to agents in a story that result in narrative events. This paper begins with an analysis and statement of the problem of creating interactive stories. From here, various attempts to solve this problem, ranging from commercial video games to academic research, are given a brief overview to give context to what paths have already been forged. With the background set, the model of interactive storytelling that the research behind LudoNarrare led to is exposed in detail. The section exploring this model contains explanations on what storyworlds are and how they are structured. It then discusses the way these storyworlds can be brought to life. The exposition on the LudoNarrare model finally wraps up by considering the way storyworlds created around this model can be designed. After the concepts of LudoNarrare are explored in the abstract, the story of the engine's research and development and the specifics of its software implementation are given. With LudoNarrare fully explained, the focus then turns to plans for evaluation of its quality in terms of entertainment value, robustness, and performance. To conclude, possible further paths of investigation for LudoNarrare and its model of interactive storytelling are proposed to inspire those who wish to continue in the spirit of the project.
ContributorsStark, Joshua Matthew (Author) / VanLehn, Kurt (Thesis director) / Wetzel, Jon (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2015-12
Description
Introspective awareness refers to direct access to one’s own internal and subjective thoughts and feelings (Wimmer & Hartl, 1991). Two theories, simulation theory and theory-theory, have been used to understand our access to our mental states. Simulation theory (Harris, 1991) involves imagining yourself in another person’s situation, reading off of your mental state, and attributing that state to the other person. Theory-theory (Gopnik, 1993) involves an interrelated body of knowledge, based on core mental-state constructs, including beliefs and desires, that may be applied to everyone—self and others (Gopnik & Wellman, 1994). Introspection is taken for granted by simulation theory, and explicitly denied by theory-theory. This study is designed to test for evidence of introspection in young children using simple perception and knowledge task. The current evidence is against introspective awareness in children because the data suggest that children cannot report their own false beliefs and they cannot report their on-going thoughts (Flavell, Green & Flavell, 1993; Gopnik & Astington, 1988). The hypothesis in this study states that children will perform better on Self tasks compared to Other tasks, which will be evidence for introspection. The Other-Perception tasks require children to calculate the other’s line of sight and determine if there is something obscuring his or her vision. The Other-Knowledge tasks require children to reason that the other’s previous looking inside a box means that he or she will know what is inside the box when it is closed. The corresponding Self tasks could be answered either by using the same reasoning for the self or by introspection to determine what it is they see and do not see, and know and do not know. Children performing better on Self tasks compared to Other tasks will be an indication of introspection. Tests included Yes/No and Forced Choice questions, which was initially to ensure that the results will not be caused by a feature of a single method of questioning. I realized belatedly, however, that Forced Choice was not a valid measure of introspection as children could introspect in both the Self and Other conditions. I also expect to replicate previous findings that reasoning about Perception is easier for children than reasoning about Knowledge.
ContributorsAamed, Mati (Author) / Fabricius, William (Thesis director) / Glenberg, Arthur (Committee member) / Kupfer, Anne (Committee member) / Department of Psychology (Contributor) / Barrett, The Honors College (Contributor) / T. Denny Sanford School of Social and Family Dynamics (Contributor)
Created2013-12
Description
This research looked at the effects unemployment had on children. A searched of the previous research few studies on the effects unemployment had on children. The leading research article, or genesis of the later studies found on the topic, was the 1938 study done by Einsenburg and Lazafeld. In that study, they found that children experience many negative effects from having an unemployed parent. In the current study, a total of 111 participants, (79 females and 32 males), in the study most of the volunteers came from Arizona State University, and the surrounding area. The research hypothesis (H1) was that individuals who had an unemployed parent as a child (Children/child for this study was defined being between the ages of 10-15) were more likely to be depressed, isolated, bullied, have an increase of illness, be less optimistic about the future and experience a decline in school performance than individuals whose parents were never unemployed. The current study found that having an unemployed parent led to being more depressed, isolated, optimistic, and having lower school performance and self-esteem in adolescence. Interestingly the study also found that as an adult the child of unemployed parents was more likely to be bullied as an adult. The results of this study furthered the research on the effects of unemployment had on children, and recommendations were made for future studies on the effects of parents unemployment has on children.
ContributorsBearden, Christian (Author) / Lewis, Stephen (Thesis director) / Miller, Paul (Committee member) / Lane, Jennifer (Committee member) / Barrett, The Honors College (Contributor) / Department of Psychology (Contributor) / W. P. Carey School of Business (Contributor)
Created2013-05
Description
The author examined the relationship between social intelligence and attachment style, specifically how attachment style affects how individuals respond to social intelligence training. Students at the Herberger Young Scholars Academy, a school for the highly gifted, completed an online social intelligence training program through the Social Intelligence Institute and were assessed on a number of items. These items include the Tromso Social Intelligence Scale (TSIS), the Attachment Questionnaire for Children (AQ-C), and a daily diary measure in which they recorded and rated their social interactions day to day. All participants were found to be either securely or insecurely attached, and those that were insecurely attached were further divided into insecure anxious attachment style and insecure avoidant attachment style. It was hypothesized that those with a secure attachment style would have higher initial TSIS scores than those with an insecure attachment style. It was also hypothesized that insecurely attached individuals would benefit more from the social intelligence training program than securely attached individuals indicated by "In tune" scores from the daily diaries, and insecure avoidant individuals would benefit more from the program than insecure anxious individuals indicated by "In tune" scores from the daily diaries. None of these hypotheses were supported by the data, as there was no significant difference between the initial social intelligence scores of the three attachment styles, and none of the variables measured were found to be significant predictors of "In tune" scores. Key Words: social intelligence, social intelligence training, attachment, attachment style, children, adolescents, gifted, IQ, high IQ
ContributorsPrice, Christina Nicole (Author) / Zautra, Alex (Thesis director) / Knight, George (Committee member) / Mickelson, Kristin (Committee member) / Barrett, The Honors College (Contributor) / T. Denny Sanford School of Social and Family Dynamics (Contributor) / Department of Psychology (Contributor)
Created2014-12
Description
This paper is centered on the use of generative adversarial networks (GANs) to convert or generate RGB images from grayscale ones. The primary goal is to create sensible and colorful versions of a set of grayscale images by training a discriminator to recognize failed or generated images and training a generator to attempt to satisfy the discriminator. The network design is described in further detail below; however there are several potential issues that arise including the averaging of a color for certain images such that small details in an image are not assigned unique colors leading to a neutral blend. We attempt to mitigate this issue as much as possible.
ContributorsMasud, Abdullah Bin (Co-author) / Koleber, Keith (Co-author) / Lobo, Ian (Co-author) / Markabawi, Jah (Co-author) / Yang, Yingzhen (Thesis director) / Wang, Yancheng (Committee member) / Computer Science and Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05