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Articles 271 - 299 of 299

Full-Text Articles in Computer Sciences

Artificial Agents In Corporate Boardrooms, Sergio Alberto Gramitto Ricci Mar 2020

Artificial Agents In Corporate Boardrooms, Sergio Alberto Gramitto Ricci

Faculty Works

Thousands of years ago, Roman businessmen often ran joint businesses through commonly owned, highly intelligent slaves. Roman slaves did not have full legal capacity and were considered property of their co-owners. Now business corporations are looking to delegate decision-making to uber intelligent machines through the use of artificial intelligence in boardrooms. Artificial intelligence in boardrooms could assist, integrate, or even replace human directors. However, the concept of using artificial intelligence in boardrooms is largely unexplored and raises several issues. This Article sheds light on legal and policy challenges concerning artificial agents in boardrooms. The arguments revolve around two fundamental questions: …


Exploring Artificial Intelligence-Mediated Communication (Aimc) As A Sub-Field Of Communication Studies. A Textual Examination, Md Nurul Karim Bhuiyan Jan 2020

Exploring Artificial Intelligence-Mediated Communication (Aimc) As A Sub-Field Of Communication Studies. A Textual Examination, Md Nurul Karim Bhuiyan

All Graduate Theses, Dissertations, and Other Capstone Projects

From the book "Speaking into the Air: A History of the Idea of Communication," written by John Durham Peters, we understand a notion about developing one’s destiny; people have the freedom to choose multiple paths to follow (Peters, 2012). If we reject this idea, it is also easy for people to come up with distinct explanations. Even though the meaning of the same issues might vary subject to who is interpreting them, the primary concepts can be interpreted as more or less the same. If we study these two--"artificial intelligence" and "communication"- simultaneously, we can assume some characteristics. Thus, this …


You Might Be A Robot, Bryan Casey, Mark A. Lemley Jan 2020

You Might Be A Robot, Bryan Casey, Mark A. Lemley

Cornell Law Review

As robots and artificial intelligence (Al) increase their influence over society, policymakers are increasingly regulating them. But to regulate these technologies, we first need to know what they are. And here we come to a problem. No one has been able to offer a decent definition of robots arid AI-not even experts. What's more, technological advances make it harder and harder each day to tell people from robots and robots from "dumb" machines. We have already seen disastrous legal definitions written with one target in mind inadvertently affecting others. In fact, if you are reading this you are (probably) not …


Law, Artificial Intelligence, And Natural Language Processing: A Funny Thing Happened On The Way To My Search Results, Paul D. Callister Jan 2020

Law, Artificial Intelligence, And Natural Language Processing: A Funny Thing Happened On The Way To My Search Results, Paul D. Callister

Faculty Works

Renowned legal educator Roscoe Pound stated, “Law must be stable and yet it cannot stand still.” Yet, as Susan Nevelow Mart has demonstrated in a seminal article that the different online research services (Westlaw, Lexis Advance, Fastcase, Google Scholar, Ravel and Casetext) produce significantly different results when researching case law. Furthermore, a recent study of 325 federal courts of appeals decisions, revealed that only 16% of the cases cited in appellate briefs make it into the courts’ opinions. This does not exactly inspire confidence in legal research or its tools to maintain stability of the law. As Robert Berring foresaw, …


Potential Impacts Of Artificial Intelligence On Spine Imaging Interpretation And Diagnosis, David Howard Durrant Jan 2020

Potential Impacts Of Artificial Intelligence On Spine Imaging Interpretation And Diagnosis, David Howard Durrant

Walden Dissertations and Doctoral Studies

Spine and related disorders represent one of the most common causes of pain and disability in the United States. Imaging represents an important diagnostic procedure in spine care. Imaging studies contain actionable data and insights undetectable through routine visual analysis. Convergent advances in imaging, artificial intelligence (AI), and radiomic methods has revealed the potential of multiscale in vivo interrogation to improve the assessment and monitoring of pathology. AI offers various types of decision support through the analysis of structured and unstructured data. The primary purpose of this qualitative exploratory case study was to identify the potential impacts of AI solutions …


A Mathematical Analysis Of The Game Of Santorini, Carson Clyde Geissler Jan 2020

A Mathematical Analysis Of The Game Of Santorini, Carson Clyde Geissler

Senior Independent Study Theses

Santorini is a two player combinatorial board game. Santorini bears resemblance to the graph theory game of Geography, a game of moving and deleting vertices on a graph. We explore Santorini with game theory, complexity theory, and artificial intelligence. We present David Lichtenstein’s proof that Geography is PSPACE-hard and adapt the proof for generalized forms of Santorini. Last, we discuss the development of an AI built for a software implementation of Santorini and present a number of improvements to that AI.


Ai Leverage In Easing The 5g Complexity And Enhancing 5g Intelligent Connectivity, Xhafer Krasniqi Oct 2019

Ai Leverage In Easing The 5g Complexity And Enhancing 5g Intelligent Connectivity, Xhafer Krasniqi

UBT International Conference

As 5G era is approaching fast and pre-commercial 5G tests and trials are happening everywhere around the world, one of the key challenges for carriers and 5G providers is to maintain and operate the network complexity required to meet diverse services and personalized user experience requirements. This maintenance and operation have to be smarter and more agile in 5G than it was in previous generations. AI and ML can be leveraged in this case to ease 5G complexity and at the same time enhance the intelligent connectivity between diverse devices and diverse tiny end points, e.g. IoT sensors.

Machine learning …


Is Ai Intelligent, Really?, Bruce D. Baker Aug 2019

Is Ai Intelligent, Really?, Bruce D. Baker

SPU Works

The question of intelligence opens up a bouquet of interrelated questions:

Suppose that some future AGI systems (on-screen or robots) equaled human performance. Would they have real intelligence, real understanding, real creativity? Would they have selves, moral standing, free choice? Would they be conscious? And without consciousness, could they have any of those other properties?[1]

The only way out of the morass is to recognize that truth claims do not stand on their own, aloof and cut off from the sea of meaning which grants epistemic access. In other words, truth presumes access to: (1) a way of knowing, …


Online Learning And Planning For Crowd-Aware Service Robot Navigation, Anoop Aroor May 2019

Online Learning And Planning For Crowd-Aware Service Robot Navigation, Anoop Aroor

Dissertations, Theses, and Capstone Projects

Mobile service robots are increasingly used in indoor environments (e.g., shopping malls or museums) among large crowds of people. To efficiently navigate in these environments, such a robot should be able to exhibit a variety of behaviors. It should avoid crowded areas, and not oppose the flow of the crowd. It should be able to identify and avoid specific crowds that result in additional delays (e.g., children in a particular area might slow down the robot). and to seek out a crowd if its task requires it to interact with as many people as possible. These behaviors require the ability …


An Evaluation Of Training Size Impact On Validation Accuracy For Optimized Convolutional Neural Networks, Jostein Barry-Straume, Adam Tschannen, Daniel W. Engels, Edward Fine Jan 2019

An Evaluation Of Training Size Impact On Validation Accuracy For Optimized Convolutional Neural Networks, Jostein Barry-Straume, Adam Tschannen, Daniel W. Engels, Edward Fine

SMU Data Science Review

In this paper, we present an evaluation of training size impact on validation accuracy for an optimized Convolutional Neural Network (CNN). CNNs are currently the state-of-the-art architecture for object classification tasks. We used Amazon’s machine learning ecosystem to train and test 648 models to find the optimal hyperparameters with which to apply a CNN towards the Fashion-MNIST (Mixed National Institute of Standards and Technology) dataset. We were able to realize a validation accuracy of 90% by using only 40% of the original data. We found that hidden layers appear to have had zero impact on validation accuracy, whereas the neural …


Artificial Intelligence: How Knowledge Is Created, Transferred, And Used, Jörg Hellwig Phd, Sarah Huggett, Mark Siebert, Bamini Jayabalasingham Phd Jan 2019

Artificial Intelligence: How Knowledge Is Created, Transferred, And Used, Jörg Hellwig Phd, Sarah Huggett, Mark Siebert, Bamini Jayabalasingham Phd

Public Reports

This document summarizes Key Findings from the full report "Artificial Intelligence: how knowledge is created, transferred, and used", available alongside other relevant material on the Elsevier Artificial Intelligence resource centre.The RELX group has extensive data assets, powerful computing capabilities, and a vast technological talent base. These allow Elsevier to provide unique insights on AI through this report. We hope these will be of interest to research evaluators, research funders, policy makers, and researchers, as they seek to navigate this complex, evolving, and fast-growing field.


The New Legal Landscape For Text Mining And Machine Learning, Matthew Sag Jan 2019

The New Legal Landscape For Text Mining And Machine Learning, Matthew Sag

Faculty Articles

Now that the dust has settled on the Authors Guild cases, this Article takes stock of the legal context for TDM research in the United States. This reappraisal begins in Part I with an assessment of exactly what the Authors Guild cases did and did not establish with respect to the fair use status of text mining. Those cases held unambiguously that reproducing copyrighted works as one step in the process of knowledge discovery through text data mining was transformative, and thus ultimately a fair use of those works. Part I explains why those rulings followed inexorably from copyright's most …


Al Planning Assistant For Scheduling Daily Activities, Priyanka Ahuja May 2018

Al Planning Assistant For Scheduling Daily Activities, Priyanka Ahuja

Theses and Dissertations

Artificial conversational agents are software agents that can interact with humans in the way humans do. Siri Cortana, and Alexa are examples of intelligent agents that can help us with almost all the basic tasks. These agents are smart enough to do the basic tasks, but not as much when it comes to complex tasks, such as analyzing traffic data, reviewing scheduling conflicts, rescheduling meetings while resolving conflicts, and offering suggestions based upon data analyses (e.g. traffic patterns, weather, etc.) The actual potential of dialogue-based task agent potential remains untapped. The reason is the fact agents lack the ability to …


Will Artificial Intelligence Have Free-Will?, Guadalupe Rodriguez May 2018

Will Artificial Intelligence Have Free-Will?, Guadalupe Rodriguez

Frankenstein @ 200: Student Posters

Will Artificial Intelligence have free will the way the Creature did?


Elephant 2000: A Programming Language For Remembering The Past And Building On It, Kerry J. Holmes Jan 2018

Elephant 2000: A Programming Language For Remembering The Past And Building On It, Kerry J. Holmes

Williams Honors College, Honors Research Projects

Elephant 2000 is a programming language to specify programs that accept user speech as text inputs and outputs speech text. The inputs and outputs are based on Dialogue Act theory which describes several forms of speech outputs, such as requests, questions, and answers. The language also relies on Named Entity Recognition to determine what types of objects a user references. These entities include persons, locations, times and so on. Using these attributes of user speech, a program is able to perform simple rule matching and pattern recognition to respond to input. The result is a programming language with English like …


The Transformation Of Science With Hpc, Big Data, And Ai, Jeffrey Kirk Oct 2017

The Transformation Of Science With Hpc, Big Data, And Ai, Jeffrey Kirk

Commonwealth Computational Summit

High performance computing has matured into an indispensable tool for not only academic research and government labs and agencies, but also for many industry sectors: energy, manufacturing, healthcare, financial services, even digital content creation. More recently, the advent of Big Data has enabled the use of HPC techniques for large scale data analysis, expanding the scope of HPC and the reach of it into more research and enterprise use cases. Since 2012, a new regime of data-driven analytics, deep learning, has erupted in popularity, fueled by both the massive performance increases in HPC technologies and in the explosive rate of …


Neural Network Ai For Fightingice, Alan D. Robison Jun 2017

Neural Network Ai For Fightingice, Alan D. Robison

Computer Engineering

Game AI in the fighting game genre, along the lines of Street Fighter, Mortal Kombat and Tekken, is traditionally script-based, with hard-coded reactions to various situations. Though this approach is often easy to understand and tweak, it requires substantial time and understanding of the game to implement in a way that is challenging and satisfying for the player due to the very large possibility space. This paper explores the use of neural networks as an alternative approach by implementing and training a network to select an action to take each frame based on the game state.


An Improved Algorithm For Learning To Perform Exception-Tolerant Abduction, Mengxue Zhang May 2017

An Improved Algorithm For Learning To Perform Exception-Tolerant Abduction, Mengxue Zhang

McKelvey School of Engineering Graduate Student Theses & Dissertations

Abstract

Inference from an observed or hypothesized condition to a plausible cause or explanation for this condition is known as abduction. For many tasks, the acquisition of the necessary knowledge by machine learning has been widely found to be highly effective. However, the semantics of learned knowledge are weaker than the usual classical semantics, and this necessitates new formulations of many tasks. We focus on a recently introduced formulation of the abductive inference task that is thus adapted to the semantics of machine learning. A key problem is that we cannot expect that our causes or explanations will be perfect, …


Exploring Algorithms To Recognize Similar Board States In Arimaa, Malik Khaleeque Ahmed Feb 2017

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 …


Monte Carlo Approaches To Parameterized Poker Squares, Todd W. Neller, Zuozhi Yang, Colin M. Messinger, Calin Anton, Karo Castro-Wunsch, William Maga, Steven Bogaerts, Robert Arrington, Clay Langely Jun 2016

Monte Carlo Approaches To Parameterized Poker Squares, Todd W. Neller, Zuozhi Yang, Colin M. Messinger, Calin Anton, Karo Castro-Wunsch, William Maga, Steven Bogaerts, Robert Arrington, Clay Langely

Computer Science Faculty Publications

The paper summarized a variety of Monte Carlo approaches employed in the top three performing entries to the Parameterized Poker Squares NSG Challenge competition. In all cases AI players benefited from real-time machine learning and various Monte Carlo game-tree search techniques.


Machines And The Moral Community, Erica L. Neely Jun 2013

Machines And The Moral Community, Erica L. Neely

Philosophy and Religion Faculty Scholarship

A key distinction in ethics is between members and nonmembers of the moral community. Over time, our notion of this community has expanded as we have moved from a rationality criterion to a sentience criterion for membership. I argue that a sentience criterion is insufficient to accommodate all members of the moral community; the true underlying criterion can be understood in terms of whether a being has interests. This may be extended to conscious, self-aware machines, as well as to any autonomous intelligent machines. Such machines exhibit an ability to formulate desires for the course of their own existence; this …


Practical Tractability Of Csps By Higher Level Consistency And Tree Decomposition, Shant Karakashian May 2013

Practical Tractability Of Csps By Higher Level Consistency And Tree Decomposition, Shant Karakashian

School of Computing: Dissertations, Theses, and Student Research

Constraint Satisfaction is a flexible paradigm for modeling many decision problems in Engineering, Computer Science, and Management. Constraint Satisfaction Problems (CSPs) are in general NP-complete and are usually solved with search. Research has identified various islands of tractability, which enable solving certain CSPs with backtrack-free search. For example, one sufficient condition for tractability relates the consistency level of a CSP to treewidth of the CSP's constraint network. However, enforcing higher levels of consistency on a CSP may require the addition of constraints, thus altering the topology of the constraint network and increasing its treewidth. This thesis addresses the following question: …


Using Ant Colonization Optimization To Control Difficulty In Video Game Ai., Joshua Courtney May 2010

Using Ant Colonization Optimization To Control Difficulty In Video Game Ai., Joshua Courtney

Undergraduate Honors Theses

Ant colony optimization (ACO) is an algorithm which simulates ant foraging behavior. When ants search for food they leave pheromone trails to tell other ants which paths to take to find food. ACO has been adapted to many different problems in computer science: mainly variations on shortest path algorithms for graphs and networks.

ACO can be adapted to work as a form of communication between separate agents in a video game AI. By controlling the effectiveness of this communication, the difficulty of the game should be able to be controlled. Experimentation has shown that ACO works effectively as a form …


Beyond Home Automation: Designing More Effective Smart Home Systems, Paolo Carner Oct 2009

Beyond Home Automation: Designing More Effective Smart Home Systems, Paolo Carner

9th. IT & T Conference

This paper outlines a Smart Home Proof-of-Concept system that uses a Bayesian Network to predict the likelihood of a monitored event to occur. Firstly, this paper will provide an introduction to the concept of a smart home system; then it will outline how Artificial Intelligence concepts can be used to make such systems more effective. Finally, it will detail the implementation of a smart home system, which uses an inference engine to determine the likelihood of a fire. The system prototype has implemented using a LonWorks™ hardware kit and a Netica™ Bayesian Network engine from Norsys.


Energetic Path Finding Across Massive Terrain Data, Andrew N. Tsui Jun 2009

Energetic Path Finding Across Massive Terrain Data, Andrew N. Tsui

Master's Theses

Before there were airplanes, cars, trains, boats, or bicycles, the primary means of transportation was on foot. Unfortunately, many of the trails used by ancient travelers have long since been abandoned. We present a software tool which can help visualize and predict where these forgotten trails might lie through the use of a human-centered cost metric. By comparing the paths generated by our software with known historical trails, we demonstrate how the tool can indicate likely trails used by ancient travelers. In addition, this new tool provides novel visualizations to better help the user understand alternate paths, effect of terrain, …


Simulation And Visualization Of Environments With Multidimensional Time, Luther A. Tychonievich Jan 2008

Simulation And Visualization Of Environments With Multidimensional Time, Luther A. Tychonievich

Theses and Dissertations

This work introduces the notion of computational hypertime, or the simulation and visualization of hypothetical environments possessing multidimensional time. An overview of hypertime is provided,including an intuitive visualization paradigm and a discussion of the failure of common simulation techniques when extended to include multidimensional time. A condition for differential equations describing hypertime motion to be amenable to standard time-iterative simulation techniques is provided,but is not satisfied by any known model of physics. An alternate simulation algorithm involving iterative refinement of entire equations of motion is presented,with an example implementation to solve elastic collisions in hypertime. An artificial intelligence algorithm for …


Self-Adjusting Finite State Machines: An Approach To Real-Time Autonomous Behavior In Robots, Scott Schwartz Aug 2005

Self-Adjusting Finite State Machines: An Approach To Real-Time Autonomous Behavior In Robots, Scott Schwartz

Computer Science Honors Theses

In the Robotics industry, it is a frequent requirement that robots operate in real-time. The usual approach to this issue involves creating robots driven entirely by direct environmental input rather than complicated planning and decision-making AI. This approach means that the current state of the robot in relation to its environment exclusively determines the actions of the robot. In the simplest terms, this approach creates a Finite State Machine (FSM). Clearly, a standard FSM is completely pre-deterministic upon its creation. This is a drawback which immediately disallows the robot to cope with dynamic environments in an autonomous manner. This research …


Koala: An Object-Agent Design System, Kym J. Pohl, Jens G. Pohl Aug 1996

Koala: An Object-Agent Design System, Kym J. Pohl, Jens G. Pohl

Collaborative Agent Design (CAD) Research Center

This paper describes KOALA, a design system with primary focus on the predesign stage of architectural design. KOALA combines object-agent technology with high level representation to form a partnership between the human designer and the computer-based design environment. A diverse taxonomy of agents including Domain agents. Space agents, and Monitor agents work in a collaborative fashion to provide the human designer with expert evaluation and assistance in developing a design solution. Spaces, in their roles as agents attempt to formulate various design solutions based on individual perspectives through negotiation with other agents. The result is a highly interactive design environment …


A Philosophical Critique Of Artificial Intelligence, David Miller Apr 1990

A Philosophical Critique Of Artificial Intelligence, David Miller

Mahurin Honors College Capstone Experience/Thesis Projects

The term "Artificial Intelligence" creates fantastic images of robots and omniscient machines. Of all the technological pursuits, Artificial Intelligence best epitomizes man's thirst for technology. The science of making machines think stands at the apex of man's mission, reflecting not only his desire for control over his world but also his quest to control himself. To create a machine capable of thought -- rational life -- would mean that man would have achieved a dream as old as technology itself.