Physical Sciences and Mathematics Commons^™

Multi-Agent Narrative Experience Management As Story Graph Pruning, Edward T. Garcia

University of New Orleans Theses and Dissertations

In this thesis I describe a method where an experience manager chooses actions for non-player characters (NPCs) in intelligent interactive narratives through story graph representation and pruning. The space of all stories can be represented as a story graph where nodes are states and edges are actions. By shaping the domain as a story graph, experience manager decisions can be made by pruning edges. Starting with a full graph, I apply a set of pruning strategies that will allow the narrative to be finishable, NPCs to act believably, and the player to be responsible for how the story unfolds. By …

Liability For Ai Decision-Making: Some Legal And Ethical Considerations, Iria Giuffrida

Faculty Publications

No abstract provided.

Artificial Intelligence And The Challenge For Rural Medicine, James Denvir

Marshall Journal of Medicine

Recent advances in artificial intelligence, machine learning, and deep learning are beginning to have an impact on everyday experiences, from natural language processing used in automated telephone call centers to semi-autonomous vehicles. These techniques have also been applied to medical care. In this editorial we discuss applications of AI to medicine and argue for a proactive approach to include rural medicine in this paradigm shift.

Court Record In The Age Of Artificial Intelligence, Fredric I. Lederer

Popular Media

No abstract provided.

Designing Women: Essentializing Femininity In Ai Linguistics, Ellianie S. Vega

Student Publications

Since the eighties, feminists have considered technology a force capable of subverting sexism because of technology’s ability to produce unbiased logic. Most famously, Donna Haraway’s “A Cyborg Manifesto” posits that the cyborg has the inherent capability to transcend gender because of its removal from social construct and lack of loyalty to the natural world. But while humanoids and artificial intelligence have been imagined as inherently subversive to gender, current artificial intelligence perpetuates gender divides in labor and language as their programmers imbue them with traits considered “feminine.” A majority of 21st century AI and humanoids are programmed to fit female …

Implementing Facial Recognition Technology In A Municipal Archives Digitization Project, Rebecca Bakker

Works of the FIU Libraries

This poster at the 2019 annual meeting of the South Florida Archivists highlights a project where the facial recognition technology of Adobe Lightroom CC is used to identify individuals in photographs held by a local municipal archive. The photographs contain hundreds of images showing unnamed commissioners and city workers from the 1970s to the 1990s, with most of the images lacking metadata or information. Various strategies are employed to identify key city officials in the photographs, allowing their names to be added to the metadata of the records hosted in a digital repository. The poster demonstrates the potential and limitations …

Abstractions In Reasoning For Long-Term Autonomy, Kyle Hollins Wray

Doctoral Dissertations

The path to building adaptive, robust, intelligent agents has led researchers to develop a suite of powerful models and algorithms for agents with a single objective. However, in recent years, attempts to use this monolithic approach to solve an ever-expanding set of complex real-world problems, which increasingly include long-term autonomous deployments, have illuminated challenges in its ability to scale. Consequently, a fragmented collection of hierarchical and multi-objective models were developed. This trend continues into the algorithms as well, as each approximates an optimal solution in a different manner for scalability. These models and algorithms represent an attempt to solve pieces …

A Study On Large-Scale Deep Learning In Bioinformatics And Biomedical Applications, Shayan Shams

LSU Doctoral Dissertations

Recent advances in Artificial Intelligence and deep learning have provided researchers in various fields insights into the analysis of multiple datasets. These applications include image analysis, text analysis, and many more. However, the effectiveness of deep learning in some areas, such as biomedical imaging and genomic research, has been overshadowed by the variance in the types and complexity of data. This is in addition to the expensive labeling process and the limited size of datasets in these fields. These challenges require advanced deep learning models capable of learning from a small dataset and also from a small number of labeled …

Deep Learning Based Real Time Devanagari Character Recognition, Aseem Chhabra

Master's Projects

The revolutionization of the technology behind optical character recognition (OCR) has helped it to become one of those technologies that have found plenty of uses in the entire industrial space. Today, the OCR is available for several languages and have the capability to recognize the characters in real time, but there are some languages for which this technology has not developed much. All these advancements have been possible because of the introduction of concepts like artificial intelligence and deep learning. Deep Neural Networks have proven to be the best choice when it comes to a task involving recognition. There are …

Intelligent Technology Of Command And Control System In The Rts Perspective, Wenfeng Wu, Zhang Yu, Rong Ming

Journal of System Simulation

Abstract: Real-Time Strategy (RTS) games have important reference value for studying the intelligent technology of command and control systems. The similarities between RTS games and the strategic battle level command and control systems are described according to the decision process. The challenges brought by the problems of planning, learning, uncertainty and space-time reasoning in the intelligent technology of RTS games are analyzed. The key technologies and latest research progress of action sequence planning, plan recognition, state assessment, multi-agent collaboration and multi-scale AI are studied. The trend of intelligent technology development of strategic and operational level command and control systems is …

Exploring Cyber-Physical Systems, Misbah Uddin Mohammed

Graduate Research Theses & Dissertations

The advances in IOT, Computer Vision, AI and Machine Learning have made these technologies ubiquitous to our daily lives. From Smart Phones to Connected Vehicles, Cyber Physical systems have been interspersed into everything we interact in today’s world. The aim or this thesis was to explore these advances in Cyber Physical Systems and analyze the different sectors they were affecting. We then hand-picked certain domains and explored further by carrying out practical projects using some of the latest software and hardware resources available. Technologies like Amazon Alexa services, NVIDIA Jetson boards, TensorFlow, OpenCV, NodeJS were heavily employed in our various …

Capso: A Multi-Objective Cultural Algorithm System To Predict Locations Of Ancient Sites, Samuel Dustin Stanley

Wayne State University Dissertations

ABSTRACT

CAPSO: A MULTI-OBJECTIVE CULTURAL ALGORITHM SYSTEM TO PREDICT LOCATIONS OF ANCIENT SITES

by

SAMUEL DUSTIN STANLEY

August 2019

Advisor: Dr. Robert Reynolds

Major: Computer Science

Degree: Doctor of Philosophy

The recent archaeological discovery by Dr. John O’Shea at University of Michigan of prehistoric caribou remains and Paleo-Indian structures underneath the Great Lakes has opened up an opportunity for Computer Scientists to develop dynamic systems modelling these ancient caribou routes and hunter-gatherer settlement systems as well as the prehistoric environments that they existed in. The Wayne State University Cultural Algorithm team has been interested assisting Dr. O’Shea’s archaeological team by …

Integration Of Robotic Perception, Action, And Memory, Li Yang Ku

Doctoral Dissertations

In the book "On Intelligence", Hawkins states that intelligence should be measured by the capacity to memorize and predict patterns. I further suggest that the ability to predict action consequences based on perception and memory is essential for robots to demonstrate intelligent behaviors in unstructured environments. However, traditional approaches generally represent action and perception separately---as computer vision modules that recognize objects and as planners that execute actions based on labels and poses. I propose here a more integrated approach where action and perception are combined in a memory model, in which a sequence of actions can be planned based on …

Deep Machine Learning For Mechanical Performance And Failure Prediction, Elijah Reber, Nickolas D. Winovich, Guang Lin

The Summer Undergraduate Research Fellowship (SURF) Symposium

Deep learning has provided opportunities for advancement in many fields. One such opportunity is being able to accurately predict real world events. Ensuring proper motor function and being able to predict energy output is a valuable asset for owners of wind turbines. In this paper, we look at how effective a deep neural network is at predicting the failure or energy output of a wind turbine. A data set was obtained that contained sensor data from 17 wind turbines over 13 months, measuring numerous variables, such as spindle speed and blade position and whether or not the wind turbine experienced …

Mind The Gap: Situated Spatial Language A Case-Study In Connecting Perception And Language, John D. Kelleher

Other

This abstract reviews the literature on computational models of spatial semantics and the potential of deep learning models as an useful approach to this challenge.

An Investigation Into The Effects Of Multiple Kernel Combinations On Solutions Spaces In Support Vector Machines, Paul Kelly, Luca Longo

Conference papers

The use of Multiple Kernel Learning (MKL) for Support Vector Machines (SVM) in Machine Learning tasks is a growing field of study. MKL kernels expand on traditional base kernels that are used to improve performance on non-linearly separable datasets. Multiple kernels use combinations of those base kernels to develop novel kernel shapes that allow for more diversity in the generated solution spaces. Customising these kernels to the dataset is still mostly a process of trial and error. Guidelines around what combinations to implement are lacking and usually they requires domain specific knowledge and understanding of the data. Through a brute …

A Legal Perspective On The Trials And Tribulations Of Ai: How Artificial Intelligence, The Internet Of Things, Smart Contracts, And Other Technologies Will Affect The Law, Iria Giuffrida, Fredric Lederer, Nicolas Vermeys

Faculty Publications

No abstract provided.

Target Detection Using Convolutional Neural Networks, Robert P. Loibl

Theses and Dissertations

This research explores the use of Convolutional Neural Networks (CNNs) to classify targets of interest within satellite imagery. Methods were specifically devised for the classification of airports within Landsat-8 scenes. A novel automated dataset generation technique was developed to create labeled datasets from satellite imagery using only coordinate metadata. Using this approach a very large dataset of over 132,000 labeled images was created without human input. This dataset was used to evaluate the effects of color and resolution on airport classification accuracy. Two experiments were run with the first experiment classifying large airports with 96.8% accuracy, and the second classifying …

Model Ai Assignments 2018, Todd W. Neller, Zack Butler, Nate Derbinsky, Heidi Furey, Fred Martin, Michael Guerzhoy, Ariel Anders, Joshua Eckroth

Computer Science Faculty Publications

The Model AI Assignments session seeks to gather and disseminate the best assignment designs of the Artificial Intelligence (AI) Education community. Recognizing that assignments form the core of student learning experience, we here present abstracts of seven AI assignments from the 2018 session that are easily adoptable, playfully engaging, and flexible for a variety of instructor needs. Assignment specifications and supporting resources may be found at http://modelai.gettysburg.edu.

New Trends In Second Language Learning And Teaching Through The Lens Of Ict, Networked Learning, And Artificial Intelligence, Jaya Kannan, Pilar Munday

Languages Faculty Publications

In the last few decades, Information and Communications Technology (ICT) applications have been shaping the field of Computer Assisted Language Learning (CALL). Mobile Assisted Language Learning (MALL) paved the way for ubiquitous learning. The advent of new technologies in the early 21st century also added a social dimension to ICT that allowed for Networked Learning (NL). Given that language learning is fundamentally a socio-cultural experience, networked learning capabilities have provided the potential for language learning in community settings. This has revitalized the earlier frameworks provided by CALL. NL has empowered language learners today to connect globally, to access Open Educational …

Mitigation Of Environmental Hazards Of Sulfide Mineral Flotation With An Insight Into Froth Stability And Flotation Performance, Muhammad Badar Hayat

Doctoral Dissertations

"Today's major challenges facing the flotation of sulfide minerals involve constant variability in the ore composition; environmental concerns; water scarcity and inefficient plant performance. The present work addresses these challenges faced by the flotation process of complex sulfide ore of Mississippi Valley type with an insight into the froth stability and the flotation performance. The first project in this study was aimed at finding the optimum conditions for the bulk flotation of galena (PbS) and chalcopyrite (CuFeS₂) through Response Surface Methodology (RSM). In the second project, an attempt was made to replace toxic sodium cyanide (NaCN) with the biodegradable chitosan …

Bibliography For Interstices 2018: Beyond Human: Emotion And Ai, Kristin Laughtin-Dunker

Library Displays and Bibliographies

An annotated list of materials in the Leatherby Libraries to accompany the Interstices 2018: Beyond Human: Emotion and AI event held at Chapman University in February 2018. The event featured Lisa Joy, co-creator and executive producer of HBO’s Emmy winning hit series Westworld, Jon Gratch, Director for Virtual Human Research at the University of Southern California’s (USC) Institute for Creative Technologies and Caroline Bainbridge, a Professor of Psychoanalysis and Culture in the Department of Media, Culture and Language at the University of Roehampton London. The Leatherby Libraries also hosted two book club discussions of The Positronic …

Designing An Ai That Cares

SIGNED: The Magazine of The Hong Kong Design Institute

The breakthrough that could change AI from being a plaything to being a playmate with which humans can have meaningful interations may be about to come from a seemingly unlikely source.

3½ Problems For Digital Assistants

SIGNED: The Magazine of The Hong Kong Design Institute

Digital home assistants promise to make life easier and happier. But a few problems stand in their way

Ai Centaurs

SIGNED: The Magazine of The Hong Kong Design Institute

As artificial intelligence outstrips human intelligence, AIs can now beat humans at any game. A pessimist might claim that this marks the end of the line for play. But a mythical beast has come to save playtime from the robots.

How Artificial Intelligence Is Impacting Manufacturing Industry, Deepak Srinivasan, Maitreyi Ramesh Swaroop, Balaji Rajaram, Sri Krishan Iyer

Research Collection School Of Computing and Information Systems

In this survey, we study the impact of Artificial Intelligence (AI) on manufacturing sector. AI methods can be utilized to make new thoughts several ways: by delivering novel mixes of wellknown thoughts; by investigating the capability of theoretical spaces; and by making changes that empower the era of unexplored thoughts. AI will have less trouble in displaying the era of new thoughts than in automating their assessment. We describe the advances that have been made on AI in manufacturing industry. We close with how to overcome the issues in this area.

Knowing How: A Computational Approach, Joseph A. Roman

Student Publications

With advances in Artificial Intelligences being achieved through the use of Artificial Neural Networks, we are now at the point where computers are able to do tasks that were previously only able to be accomplished by humans. These advancements must cause us to reconsider our previous understanding of how people come to know how to do a particular task. In order to unpack this question, I will first look to an account of knowing how presented by Jason Stanley in his book Know How. I will then look towards criticisms of this view before using evidence presented by the existence …

Exploring Algorithms To Recognize Similar Board States In Arimaa, Malik Khaleeque Ahmed

Theses and Dissertations

The game of Arimaa was invented as a challenge to the field of game-playing artificial intelligence, which had grown somewhat haughty after IBM's supercomputer Deep Blue trounced world champion Kasparov at chess. Although Arimaa is simple enough for a child to learn and can be played with an ordinary chess set, existing game-playing algorithms and techniques have had a difficult time rising up to the challenge of defeating the world's best human Arimaa players, mainly due to the game's impressive branching factor. This thesis introduces and analyzes new algorithms and techniques that attempt to recognize similar board states based on …

Ai Education: Open-Access Educational Resources On Ai, Todd W. Neller

Computer Science Faculty Publications

Open-access AI educational resources are vital to the quality of the AI education we offer. Avoiding the reinvention of wheels is especially important to us because of the special challenges of AI Education. AI could be said to be “the really interesting miscellaneous pile of Computer Science”. While “artificial” is well-understood to encompass engineered artifacts, “intelligence” could be said to encompass any sufficiently difficult problem as would require an intelligent approach and yet does not fall neatly into established Computer Science subdisciplines. Thus AI consists of so many diverse topics that we would be hard-pressed to individually create quality learning …

Ai Education: Deep Neural Network Learning Resources, Todd W. Neller

Computer Science Faculty Publications

In this column, we focus on resources for learning and teaching deep neural network learning. Many exciting advances have been made in this area of late, and so many resources have become available online that the flood of relevant concepts and techniques can be overwhelming. Here, we hope to provide a sampling of high-quality resources to guide the newcomer into this booming field. [excerpt]