Artificial Intelligence and Robotics Commons^™

Unified Behavior Framework For Discrete Event Simulation Systems, Alexander J. Kamrud

Theses and Dissertations

Intelligent agents provide simulations a means to add lifelike behavior in place of manned entities. Generally when developed, a single intelligent agent model is chosen, such as rule based, behavior trees, etc. This choice introduces restrictions into what behaviors agents can manifest, and can require significant testing in edge cases. This thesis presents the use of the UBF in the AFSIM environment. The UBF provides the flexibility to implement any and all intelligent agent models, allowing the developer to choose the model he/she feels best fits the experiment at hand. Furthermore, the UBF demonstrates several key software engineering principles through …

Tactical Ai In Real Time Strategy Games, Donald A. Gruber

Theses and Dissertations

The real time strategy (RTS) tactical decision making problem is a difficult problem. It is generally more complex due to its high degree of time sensitivity. This research effort presents a novel approach to this problem within an educational, teaching objective. Particular decision focus is target selection for a artificial intelligence (AI) RTS game model. The use of multi-objective evolutionary algorithms (MOEAs) in this tactical decision making problem allows an AI agent to make fast, effective solutions that do not require modification to the current environment. This approach allows for the creation of a generic solution building tool that is …

Experimental Investigation Of Stochastic Parafoil Guidance Using A Graphics Processing Unit, Nathan Slegers, Andrew Brown, Jonathan Rogers

Faculty Publications - Biomedical, Mechanical, and Civil Engineering

Control of autonomous systems subject to stochastic uncertainty is a challenging task. In guided airdrop applications, random wind disturbances play a crucial role in determining landing accuracy and terrain avoidance. This paper describes a stochastic parafoil guidance system which couples uncertainty propagation with optimal control to protect against wind and parameter uncertainty in the presence of impact area obstacles. The algorithm uses real-time Monte Carlo simulation performed on a graphics processing unit (GPU) to evaluate robustness of candidate trajectories in terms of delivery accuracy, obstacle avoidance, and other considerations. Building upon prior theoretical developments, this paper explores performance of the …

A Study Of Decision Process In Mcdm Problems With Large Number Of Criteria, Jian Liu, Peng Liu, Si Feng Liu, Xian Zhong Zhou, Tao Zhang

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, an effective decision process method is proposed to address the challenge in a multiple criteria decision-making (MCDM) problem because of large number of criteria. This method is based on the criteria reduction, tolerance relation, and prospect theory (PT). By building a discernibility matrix for tolerance relation (DMTR) in an MCDM problem with numerical values or interval numbers, this method first allows us to recognize a set of critical criteria from a large criteria pool and ignore the other criteria. Next, it establishes the criteria weights through the DMTR as they are usually not indicated in the data. …

Using Infrastructure-Provided Context Filters For Efficient Fine-Grained Activity Sensing, Vigneshwaran Subbaraju, Sougata Sen, Archan Misra, Satyadip Chakraborty, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

While mobile and wearable sensing can capture unique insights into fine-grained activities (such as gestures and limb-based actions) at an individual level, their energy overheads are still prohibitive enough to prevent them from being executed continuously. In this paper, we explore practical alternatives to addressing this challenge-by exploring how cheap infrastructure sensors or information sources (e.g., BLE beacons) can be harnessed with such mobile/wearable sensors to provide an effective solution that reduces energy consumption without sacrificing accuracy. The key idea is that many fine-grained activities that we desire to capture are specific to certain location, movement or background context: infrastructure …

A Proposed Model For The Approach To Augmented Reality Deployment In Marketing Communications, Stephen O'Mahony

Dept. of Marketing & International Business Conference Material

In the contemporary landscape, human interaction is characterized by the pervasive mediation of intelligent agents. Owing to advances in computer science and engineering, phenomena once limited to fixed locations are metamorphosing from extraneous entities to implicit components of the everyday. Computing power has simultaneously enhanced and miniaturized to the extent that contemporary consumer devices demonstrate power equivalent to or greater than that of personal computers of recent memory. At the same time, network connectivity has proliferated to ubiquitous levels, reflected in the fact that the amount of inanimate objects connected to the Internet has recently surpassed the human population of …

A Heuristic Evolutionary Method For The Complementary Cell Suppression Problem, Hira B. Herrington

CCAC Theses and Dissertations

Cell suppression is a common method for disclosure avoidance used to protect sensitive information in two-dimensional tables where row and column totals are published along with non-sensitive data. In tables with only positive cell values, cell suppression has been demonstrated to be non-deterministic NP-hard. Therefore, finding more efficient methods for producing low-cost solutions is an area of active research.

Genetic algorithms (GA) have shown to be effective in finding good solutions to the cell suppression problem. However, these methods have the shortcoming that they tend to produce a large proportion of infeasible solutions. The primary goal of this research was …

A Defeasible Reasoning Framework For Human Mental Workload Representation And Assessment, Luca Longo

Conference papers

Human mental workload (MWL) has gained importance in the last few decades as an important design concept. It is a multifaceted complex construct mainly applied in cognitive sciences and has been defined in many different ways. Although measuring MWL has potential advantages in interaction and interface design, its formalisation as an operational and computational construct has not sufficiently been addressed. This research contributes to the body of knowledge by providing an extensible framework built upon defeasible reasoning, and implemented with argumentation theory (AT), in which MWL can be better defined, measured, analysed, explained and applied in different human–computer interactive contexts. …

Introducing Machine Learning Via Baseball's Hall Of Fame, David Hansen

Faculty Publications - Department of Electrical Engineering and Computer Science

Machine Learning via Artificial Neural Networks (ANNs) is often introduced in a one-semester course on Artificial Intelligence. Baseball’s annual Hall of Fame election provides a simple, tractable, data-rich domain for learning how to use ANNs for predictive analytics. We describe how we use the Fast Artificial Neural Network (FANN) toolkit for a course assignment that predicts which players are likely to be elected to Baseball’s Hall of Fame.

Potential Of Cognitive Computing And Cognitive Systems, Ahmed K. Noor

Computational Modeling & Simulation Engineering Faculty Publications

Cognitive computing and cognitive technologies are game changers for future engineering systems, as well as for engineering practice and training. They are major drivers for knowledge automation work, and the creation of cognitive products with higher levels of intelligence than current smart products. This paper gives a brief review of cognitive computing and some of the cognitive engineering systems activities. The potential of cognitive technologies is outlined, along with a brief description of future cognitive environments, incorporating cognitive assistants - specialized proactive intelligent software agents designed to follow and interact with humans and other cognitive assistants across the environments. The …

Isolation In Synchronized Drone Formations, Andrew P. Brunner

Electronic Theses and Dissertations

This paper expands on a theoretical model that is used for aerial robots that are working cooperatively to complete a task. In certain situations, such as when multiple robots have catastrophic failures, the surviving robots could become isolated so that they never again communicate with another robot. We prove some properties about isolated robots flying in a grid formation, and we present an algorithm that determines how many robots need to fail to isolate at least one robot. Finally, we propose a strategy that eliminates the possibility of isolation altogether.

Facial Expression Analysis Via Transfer Learning, Xiao Zhang

Electronic Theses and Dissertations

Automated analysis of facial expressions has remained an interesting and challenging research topic in the field of computer vision and pattern recognition due to vast applications such as human-machine interface design, social robotics, and developmental psychology. This dissertation focuses on developing and applying transfer learning algorithms - multiple kernel learning (MKL) and multi-task learning (MTL) - to resolve the problems of facial feature fusion and the exploitation of multiple facial action units (AUs) relations in designing robust facial expression recognition systems. MKL algorithms are employed to fuse multiple facial features with different kernel functions and tackle the domain adaption problem …

Generating Plans In Concurrent, Probabilistic, Over-Subscribed Domains, Li Li

Dissertations, Master's Theses and Master's Reports - Open

Planning in realistic domains typically involves reasoning under uncertainty, operating under time and resource constraints, and finding the optimal subset of goals to work on. Creating optimal plans that consider all of these features is a computationally complex, challenging problem. This dissertation develops an AO* search based planner named CPOAO* (Concurrent, Probabilistic, Over-subscription AO*) which incorporates durative actions, time and resource constraints, concurrent execution, over-subscribed goals, and probabilistic actions. To handle concurrent actions, action combinations rather than individual actions are taken as plan steps. Plan optimization is explored by adding two novel aspects to plans. First, parallel steps that serve …

Energy Cost Forecasting For Event Venues, Katarina Grolinger, Andrea Zagar, Miriam Am Capretz, Luke Seewald

Electrical and Computer Engineering Publications

Electricity price, consumption, and demand forecasting has been a topic of research interest for a long time. The proliferation of smart meters has created new opportunities in energy prediction. This paper investigates energy cost forecasting in the context of entertainment event-organizing venues, which poses significant difficulty due to fluctuations in energy demand and wholesale electricity prices. The objective is to predict the overall cost of energy consumed during an entertainment event. Predictions are carried out separately for each event category and feature selection is used to select the most effective combination of event attributes for each category. Three machine learning …

The Value Of Diagnostic Software And Doctors' Decision Making, Babatunde Ayodele Alaofin

Walden Dissertations and Doctoral Studies

The prevalence of medical misdiagnosis has remained high despite the adoption of diagnostic software. This ongoing controversy about the role of technology in mitigating the problem of misdiagnosis centers on the question of whether diagnostic software does reduce the incidence of misdiagnosis if properly relied upon by physicians. The purpose of this quantitative, cross-sectional study based on planned behavior theory was to measure doctors' opinions of diagnostic technology's medical utility. Recruitment e-mails were sent to 3,100 AMA-accredited physicians through their database that yielded a sample of 99 physicians for the study. One-sample t tests and, where appropriate because of non-normal …

Research Agenda Into Human-Intelligence/Machine-Intelligence Governance, Teddy Steven Cotter

Engineering Management & Systems Engineering Faculty Publications

Since the birth of modern artificial intelligence (AI) at the 1956 Dartmouth Conference, the AI community has pursued modeling and coding of human intelligence into AI reasoning processes (HI Þ MI). The Dartmouth Conference's fundamental assertion was that every aspect of human learning and intelligence could be so precisely described that it could be simulated in AI. With the exception of knowledge specific areas (such as IBM's Big Blue and a few others), sixty years later the AI community is not close to coding global human intelligence into AI. In parallel, the knowledge management (KM) community has pursued understanding of …

Integrated Intelligence For Human-Robot Teams, Jean Oh, Et. Al.

Research Collection School Of Computing and Information Systems

With recent advances in robotics technologies and autonomous systems, the idea of human-robot teams is gaining ever-increasing attention. In this context, our research focuses on developing an intelligent robot that can autonomously perform non-trivial, but specific tasks conveyed through natural language. Toward this goal, a consortium of researchers develop and integrate various types of intelligence into mobile robot platforms, including cognitive abilities to reason about high-level missions, perception to classify regions and detect relevant objects in an environment, and linguistic abilities to associate instructions with the robot’s world model and to communicate with human teammates in a natural way. This …

Designing A Portfolio Of Parameter Configurations For Online Algorithm Selection, Aldy Gunawan, Hoong Chuin Lau, Mustafa Misir

Research Collection School Of Computing and Information Systems

Algorithm portfolios seek to determine an effective set of algorithms that can be used within an algorithm selection framework to solve problems. A limited number of these portfolio studies focus on generating different versions of a target algorithm using different parameter configurations. In this paper, we employ a Design of Experiments (DOE) approach to determine a promising range of values for each parameter of an algorithm. These ranges are further processed to determine a portfolio of parameter configurations, which would be used within two online Algorithm Selection approaches for solving different instances of a given combinatorial optimization problem effectively. We …

Metalogic Notes, Saverio Perugini

Computer Science Working Papers

A collection of notes, formulas, theorems, postulates and terminology in symbolic logic, syntactic notions, semantic notions, linkages between syntax and semantics, soundness and completeness, quantified logic, first-order theories, Goedel's First Incompleteness Theorem and more.

Statistics Notes, Saverio Perugini

Computer Science Working Papers

A collection of terms, definitions, formulas and explanations about statistics.