Digital Commons Network^™

A Multimodal Problem For Competitive Coevolution, Philip Hingston, Tirtha Ranjeet, Chiou Peng Lam, Martin Masek

Research outputs 2012

Coevolutionary algorithms are a special kind of evolutionary algorithm with advantages in solving certain specific kinds of problems. In particular, competitive coevolutionary algorithms can be used to study problems in which two sides compete against each other and must choose a suitable strategy. Often these problems are multimodal - there is more than one strong strategy for each side. In this paper, we introduce a scalable multimodal test problem for competitive coevolution, and use it to investigate the effectiveness of some common coevolutionary algorithm enhancement techniques.

Modeling And Analysis Of Multiple Engine Aircraft Configurations For Fault Tolerant Control, Frederick M. Beamer

Graduate Theses, Dissertations, and Problem Reports (ETD)

A formal framework is presented that allows for the analysis of the potential for using engine thrust control for aircraft actuator failure accommodation. Three sets of parameters have been identified as critical: number of engines and their position, engine thrust and throttle dynamics, and type and severity of the actuator failure. A mathematical model was developed that allows for the determination of the values of some of the parameters when the others are imposed such as determining the thrust control authority when the engine locations and Euler angles are known. Additionally, the engine locations can be determined when the thrust …

Report On Advances In The Field Of Artificial Intelligence Attributed To Captcha, Craig M. Schow

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

A CAPTCHA is a specialized human interaction proof that exploits gaps between human and computer recognition abilities. By design, the hardness of a CAPTCHA is based on the difficulty of advancing the underlying artificial intelligence [AI] technology to a level that eliminates any exploitable gap. Due to this fact computer scientists have concluded that the widespread use of CAPTCHA would accelerate research in the underlying fields of AI eventually leading to near-­‐human capabilities in certain AI systems. Despite these predictions no attempt has been made to identify advances in AI which can be attributed to the use of CAPTCHA.

The …

Chatbots In The Library: Is It Time?, Deeann Allison

University of Nebraska-Lincoln Libraries: Faculty Publications

This paper describes a pilot at the University of Nebraska-Lincoln for a chatbot that answers questions about the library and library resources. The chatbot was developed using a SQL database to store the question and answers using Artificial Intelligence Mark-up Language metadata. The user interface was built using PHP, adapted from Program-O. The open source PHP program was modified to support better display and the launching of URLs within the chatbot screen. Database content was created by “mining” library websites for information, and analyzing chat logs.

The chatbot answers questions from a variety of users from around the world. It …

Evolving Machine Morality Strategies Through Multiagent Simulations, David Burke

Systems Science Friday Noon Seminar Series

There is a general consensus among robotics researchers that the world of the future will be filled with autonomous and semi-autonomous machines. There is less of a consensus, though, on the best approach to instilling a sense of 'machine morality' in these systems so that they will be able to have effective interactions with humans in an increasingly complex world. In my talk, we take a brief look at some existing approaches to computational ethics, and then describe work we've undertaken creating multiagent simulations involving moral decision-making during strategic interactions. In these simulations, agents make choices about whether to cooperate …

Design Of Fault Tolerant Control System For Individual Blade Control Helicopters, Sergio Tamayo

Graduate Theses, Dissertations, and Problem Reports (ETD)

This dissertation presents the development of a fault tolerant control scheme for helicopters fitted with individually controlled blades. This novel approach attempts to improve fault tolerant capabilities of helicopter control system by increasing control redundancy using additional actuators for individual blade input and software re-mixing to obtain nominal or close to nominal conditions under failure. An advanced interactive simulation environment has been developed including modeling of sensor failure, swashplate actuator failure, individual blade actuator failure, and blade delamination to support the design, testing, and evaluation of the control laws. This simulation environment is based on the blade element theory for …

Parameter Estimation Analysis For Hybrid Adaptive Fault Tolerant Control, Peter B. Eshak

Graduate Theses, Dissertations, and Problem Reports (ETD)

Research efforts have increased in recent years toward the development of intelligent fault tolerant control laws, which are capable of helping the pilot to safely maintain aircraft control at post failure conditions. Researchers at West Virginia University (WVU) have been actively involved in the development of fault tolerant adaptive control laws in all three major categories: direct, indirect, and hybrid. The first implemented design to provide adaptation was a direct adaptive controller, which used artificial neural networks to generate augmentation commands in order to reduce the modeling error. Indirect adaptive laws were implemented in another controller, which utilized online PID …

Intelligent Controls For A Semi-Active Hydraulic Prosthetic Knee, Timothy Allen Wilmot

ETD Archive

We discuss open loop control development and simulation results for a semi-active above-knee prosthesis. The control signal consists of two hydraulic valve settings. These valves control a rotary actuator that provides torque to the prosthetic knee. We develop open loop control using biogeography-based optimization (BBO), which is a recently developed evolutionary algorithm, and gradient descent. We use gradient descent to show that the control generated by BBO is locally optimal. This research contributes to the field of evolutionary algorithms by demonstrating that BBO is successful at finding optimal solutions to complex, real-world, nonlinear, time varying control problems. The research contributes …

Immune System Based Control And Intelligent Agent Design For Power System Applications, Rabie Belkacemi

Graduate Theses, Dissertations, and Problem Reports (ETD)

The National Academy of Engineering has selected the US Electric Power Grid as the supreme engineering achievement of the 20th century. Yet, this same grid is struggling to keep up with the increasing demand for electricity, its quality and cost. A growing recognition of the need to modernize the grid to meet future challenges has found articulation in the vision of a Smart Grid in using new control strategies that are intelligent, distributed, and adaptive. The objective of this work is to develop smart control systems inspired from the biological Human Immune System to better manage the power grid at …

Real-Time Acquisition Of Multi-View Face Images To Support Robust Face Recognition Using A Wireless Camera Network, Srikanth Parupati

Graduate Theses, Dissertations, and Problem Reports (ETD)

Recent terror attacks, intrusion attempts and criminal activities have necessitated a transition to modern biometric systems that are capable of identifying suspects in real time. But real-time biometrics is challenging given the computationally intensive nature of video processing and the potential occlusions and variations in pose of a subject in an unconstrained environment. The objective of this dissertation is to utilize the robustness and parallel computational abilities of a distributed camera network for fast and robust face recognition.;In order to support face recognition using a camera network, a collaborative middle-ware service is designed that enables the rapid extraction of multi-view …

Optimal Control For Autonomous Motor Behavior, Tom Erez

All Theses and Dissertations (ETDs)

This dissertation presents algorithms that allow robots to generate optimal behavior from first principles. Instead of hard-coding every desired behavior, we encode the task as a cost function, and use numerical optimization to find action sequences that can accomplish the task. Using the theoretical framework of optimal control, we develop methods for generating autonomous motor behavior in high-dimensional domains of legged locomotion. We identify three foundational problems that limit the application of existing optimal control algorithms, and present guiding principles that address these issues. First, some traditional algorithms use global optimization, where every possible state is considered. This approach cannot …

Hierarchical Temporal Memory Cortical Learning Algorithm For Pattern Recognition On Multi-Core Architectures, Ryan William Price

Dissertations and Theses

Strongly inspired by an understanding of mammalian cortical structure and function, the Hierarchical Temporal Memory Cortical Learning Algorithm (HTM CLA) is a promising new approach to problems of recognition and inference in space and time. Only a subset of the theoretical framework of this algorithm has been studied, but it is already clear that there is a need for more information about the performance of HTM CLA with real data and the associated computational costs. For the work presented here, a complete implementation of Numenta's current algorithm was done in C++. In validating the implementation, first and higher order sequence …

Single And Multiobjective Approaches To Clustering With Point Symmetry., Sriparna Saha Dr.

Doctoral Theses

In our every day life, we make decisions consciously or unconsciously. This decision can be very simple such as selecting the color of dress or deciding the menu for lunch, or may be as difficult as those involved in designing a missile or in selecting a career. The former decision is easy to take, while the latter one might take several years due to the level of complexity involved in it. The main goal of most kinds of decision-making is to optimize one or more criteria in order to achieve the desired result. In other words, problems related to optimization …

Fuzzy Logic Based Iedsss For Environmental Risk Assessment And Management, A. Zabeo, Elena Semenzin, S. Torresan, Stefania Gottardo, L. Pizzol, J. Rizzi, S. Giove, A. Critto, Antonio Marcomini

International Congress on Environmental Modelling and Software

Environmental problems and the related adaptation strategies have grown in importance and complexity during the last years. The large amount of data and information that needs to be handled and integrated requires specific methodologies and tools. Several research and application activities are undergoing worldwide for the development of Decision Support Systems (DSSs) that allow management of multiple and different data in order to aid decision-making. In this paper the following DSSs using fuzzy models based Artificial Intelligence to address environmental problems will be presented. SYRIADE is a Spatial DSS for Regional Risk Assessment of degraded land supporting the inventory and …

Fuzzy Logic Based Iedsss For Environmental Risk Assessment And Management, A. Zabeo, Elena Semenzin, S. Torresan, Stefania Gottardo, L. Pizzol, J. Rizzi, S. Giove, A. Critto, Antonio Marcomini

International Congress on Environmental Modelling and Software

Environmental problems and the related adaptation strategies have grown in importance and complexity during the last years. The large amount of data and information that needs to be handled and integrated requires specific methodologies and tools. Several research and application activities are undergoing worldwide for the development of Decision Support Systems (DSSs) that allow management of multiple and different data in order to aid decision-making. In this paper the following DSSs using fuzzy models based Artificial Intelligence to address environmental problems will be presented. SYRIADE is a Spatial DSS for Regional Risk Assessment of degraded land supporting the inventory and …

Collective Belief Models For Representing Consensus And Divergence In Communities Of Bayesian Decision-Makers, Kshanti Greene

Computer Science ETDs

Bayesian belief aggregation is the process of forming a consensus model from the probabilistic beliefs of multiple individuals. Preference aggregation attempts to find an optimal solution for a population considering each individual's beliefs, desires and objectives. Belief and preference aggregation approaches that form a single consensus average away any diversity in a population. In the process they may fail to uphold a set of mathematical properties for rational aggregation defined by social choice theorists. This dissertation introduces a new aggregation approach that maintains the diversity of a population and allows the competitive aspects of a situation to emerge, enabling game …

Partitioning Of Minimotifs Based On Function With Improved Prediction Accuracy, Sanguthevar Rajasekaran, Tian Mi, Jerlin Camilus Merlin, Aaron Oommen, Patrick R. Gradie, Martin R. Schiller

Life Sciences Faculty Research

Background

Minimotifs are short contiguous peptide sequences in proteins that are known to have a function in at least one other protein. One of the principal limitations in minimotif prediction is that false positives limit the usefulness of this approach. As a step toward resolving this problem we have built, implemented, and tested a new data-driven algorithm that reduces false-positive predictions.

Methodology/Principal Findings

Certain domains and minimotifs are known to be strongly associated with a known cellular process or molecular function. Therefore, we hypothesized that by restricting minimotif predictions to those where the minimotif containing protein and target protein have …

Neural Network Approach To Classification Of Infrasound Signals, Dong-Chang Lee

Physics

As part of the International Monitoring Systems of the Preparatory Commissions for the Comprehensive Nuclear Test-Ban Treaty Organization, the Infrasound Group at the University of Alaska Fairbanks maintains and operates two infrasound stations to monitor global nuclear activity. In addition, the group specializes in detecting and classifying the man-made and naturally produced signals recorded at both stations by computing various characterization parameters (e.g. mean of the cross correlation maxima, trace velocity, direction of arrival, and planarity values) using the in-house developed weighted least-squares algorithm. Classifying commonly observed low-frequency (0.015--0.1 Hz) signals at out stations, namely mountain associated waves and high …

Using Quality Attributes And Computational Intelligence To Generate And Evaluate System Architecture Alternatives, Atmika Singh, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

This paper proposes an evolutionary algorithm based approach for evolving architecture alternatives using quality attributes as design drivers. A novel fuzzy architecture assessment approach is presented to quantitatively evaluate the set of possible solutions based on linguistic assessments of architecture quality attributes elicited from the stakeholders. The proposed approach makes a valuable contribution to the systems architecting knowledge base by presenting a measurable and quantifiable approach to architecture design and evaluation.

Artificial Intelligence: Soon To Be The World’S Greatest Intelligence, Or Just A Wild Dream?, Edward R. Kollett

Academic Symposium of Undergraduate Scholarship

The purpose of the paper was to examine the field of artificial intelligence. In particular, the paper focused on what has been accomplished towards the goal of making a machine that can think like a human, and the hardships that researchers in the field has faced. It also touched upon the potential outcomes of success. Why is this paper important? As computers become more powerful, the common conception is that they are becoming more intelligent. As computers become more integrated with society and more connected with each other, people again believe they are becoming smarter. Therefore, it is important that …

Developing An Effective And Efficient Real Time Strategy Agent For Use As A Computer Generated Force, Kurt Weissgerber

Theses and Dissertations

Computer Generated Forces (CGF) are used to represent units or individuals in military training and constructive simulation. The use of CGF significantly reduces the time and money required for effective training. For CGF to be effective, they must behave as a human would in the same environment. Real Time Strategy (RTS) games place players in control of a large force whose goal is to defeat the opponent. The military setting of RTS games makes them an excellent platform for the development and testing of CGF. While there has been significant research in RTS agent development, most of the developed agents …

Evolutionary Artificial Neural Network Weight Tuning To Optimize Decision Making For An Abstract Game, Corey M. Miller

Theses and Dissertations

Abstract strategy games present a deterministic perfect information environment with which to test the strategic capabilities of artificial intelligence systems. With no unknowns or random elements, only the competitors’ performances impact the results. This thesis takes one such game, Lines of Action, and attempts to develop a competitive heuristic. Due to the complexity of Lines of Action, artificial neural networks are utilized to model the relative values of board states. An application, pLoGANN (Parallel Lines of Action with Genetic Algorithm and Neural Networks), is developed to train the weights of this neural network by implementing a genetic algorithm over a …

Mythic Game Project Addition Of Artificial Intelligence And Quest System Components, Christopher Alan Ballinger

Theses Digitization Project

This study will describe the design decisions and principles behind the artificial intelligence (AI) for a multiplayer online role playing game and the use of an expert system to implement it. Mythic is an active project focused on the development of all aspects of a multiplayer online role playing game (MORPG). The goal of Mythic is to develop a system with the capacity to offer similar capabilities as current MORPG games available on the market, as well as providing new innovative features to distinguish it from other MORPG games and make it attractive to potential players.

Robust Dialog Management Through A Context-Centric Architecture, Victor C. Hung

Electronic Theses and Dissertations

This dissertation presents and evaluates a method of managing spoken dialog interactions with a robust attention to fulfilling the human user’s goals in the presence of speech recognition limitations. Assistive speech-based embodied conversation agents are computer-based entities that interact with humans to help accomplish a certain task or communicate information via spoken input and output. A challenging aspect of this task involves open dialog, where the user is free to converse in an unstructured manner. With this style of input, the machine’s ability to communicate may be hindered by poor reception of utterances, caused by a user’s inadequate command of …

A New Design For A Turing Test For Bots, Philip Hingston

Research outputs pre 2011

Interesting, human-like opponents add to the entertainment value of a video game, and creating such opponents is a difficult challenge for programmers. Can artificial intelligence and computational intelligence provide the means to convincingly simulate a human opponent? Or are simple programming tricks and deceptions more effective? To answer these questions, the author designed and organised a game bot programming competition, the BotPrize, in which competitors submit bots that try to pass a “Turing Test for Bots”. In this paper, we describe a new design for the competition, which will make it simpler to run, and, we hope, open up new …

Redtnet: A Network Model For Strategy Games, Philip Hingston, Mike Preuss, Daniel Spierling

Research outputs pre 2011

In this work, we develop a simple, graph-based framework, RedTNet, for computational modeling of strategy games and simulations. The framework applies the concept of red teaming as a means by which to explore alternative strategies. We show how the model supports computer-based red teaming in several applications: realtime strategy games and critical infrastructure protection, using an evolutionary algorithm to automatically detect good and often surprising strategies.

Manipulation Of Elections By Minimal Coalitions, Christopher Connett

Theses

Social choice is the study of the issues arising when a population of individuals attempts to combine its views with the objective of determining a collective policy. Recent research in artificial intelligence raises concerns of articial intelligence agents applying computational resources to attack an election. If we think of voting as a way to combine honest preferences, it would be undesirable for some voters cast ballots that differ from their true preferences and achieve a better result for themselves at the expense of the general social welfare. Such an attack is called manipulation. The Gibbard-Satterthwaite theorem holds that all reasonable …

Computer-Guided Solutions To Physics Problems Using Prolog, Thomas J. Bensky, Catherine A. Taff

Physics

By posing a continual stream of pertinent questions, a nonmathematical computer program can prod freshman physics students toward an analytical solution to one-dimensional kinematics problems.

Measuring The Discriminative Capability Of Metrology In Human Recognition, Rakesh Sepuri

Graduate Theses, Dissertations, and Problem Reports (ETD)

Biometrics is now a more established and sophisticated field. It studies the use of physiological characteristics or behavioral traits to identify and recognize a person automatically. It facilitates theft control and increased security.;Metrology has been one of the well-studied topics in computer vision. Absolute measurement values of humans can be obtained from a fully calibrated camera. These measurements are stored as a database and studied in detail to assess their significance as a biometric. In this thesis we want to assess the performance of human body measurements as a soft biometric. Every human has distinct biometric characters. They can be …

A Computational Analysis Of Cognitive Effort, Luca Longo, Stephen Barrett

Books/Book Chapters

Cognitive effort is a concept of unquestionable utility in understanding human behaviour. However, cognitive effort has been defined in several ways in literature and in everyday life, suffering from a partial understanding. It is common to say “Pay more attention in studying that subject” or “How much effort did you spend in resolving that task?”, but what does it really mean? This contribution tries to clarify the concept of cognitive effort, by introducing its main influencing factors and by presenting a formalism which provides us with a tool for precise discussion. The formalism is implementable as a computational concept and …