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Artificial intelligence

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Articles 151 - 173 of 173

Full-Text Articles in Computer Engineering

Responses To Catastrophic Agi Risk: A Survey, Kaj Sotala, Roman V. Yampolskiy Dec 2014

Responses To Catastrophic Agi Risk: A Survey, Kaj Sotala, Roman V. Yampolskiy

Faculty and Staff Scholarship

Many researchers have argued that humanity will create artificial general intelligence (AGI) within the next twenty to one hundred years. It has been suggested that AGI may inflict serious damage to human well-being on a global scale ('catastrophic risk'). After summarizing the arguments for why AGI may pose such a risk, we review the fields proposed responses to AGI risk. We consider societal proposals, proposals for external constraints on AGI behaviors and proposals for creating AGIs that are safe due to their internal design.

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Reasoning Across Language And Vision In Machines And Humans, Andrei Barbu Oct 2013

Reasoning Across Language And Vision In Machines And Humans, Andrei Barbu

Open Access Dissertations

Humans not only outperform AI and computer-vision systems, but use an unknown computational mechanism to perform tasks for which no suitable approaches exist. I present work investigating both novel tasks and how humans approach them in the context of computer vision and linguistics. I demonstrate a system which, like children, acquires high-level linguistic knowledge about the world. Robots learn to play physically-instantiated board games and use that knowledge to engage in physical play. To further integrate language and vision I develop an approach which produces rich sentential descriptions of events depicted in videos. I then show how to simultaneously detect …

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Modeling Learner Mood In Realtime Through Biosensors For Intelligent Tutoring Improvements, Keith Brawner Jan 2013

Modeling Learner Mood In Realtime Through Biosensors For Intelligent Tutoring Improvements, Keith Brawner

Electronic Theses and Dissertations

Computer-based instructors, just like their human counterparts, should monitor the emotional and cognitive states of their students in order to adapt instructional technique. Doing so requires a model of student state to be available at run time, but this has historically been difficult. Because people are different, generalized models have not been able to be validated. As a person’s cognitive and affective state vary over time of day and seasonally, individualized models have had differing difficulties. The simultaneous creation and execution of an individualized model, in real time, represents the last option for modeling such cognitive and affective states. This …

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Cancer Risk Analysis By Fuzzy Logic Approach And Performance Status Of The Model, Atinç Yilmaz, Kürşat Ayan Jan 2013

Cancer Risk Analysis By Fuzzy Logic Approach And Performance Status Of The Model, Atinç Yilmaz, Kürşat Ayan

Turkish Journal of Electrical Engineering and Computer Sciences

Cancer is the leading life-threatening disease for people in today's world. Although cancer formation is different for each type of cancer, it has been determined by studies and research that stress also triggers cancer types. Early precaution is very important for people who have not fallen ill yet with a disease like cancer that has a high mortality rate and expensive treatment. With this study, we expound that the possibility of developing such disease may be decreased and people could take measures against it. For the 3 cancer types selected as pilot work by introducing a fuzzy logic model, the …

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A New Intelligent Classifier For Breast Cancer Diagnosis Based On A Rough Set And Extreme Learning Machine: Rs + Elm, Yilmaz Kaya Jan 2013

A New Intelligent Classifier For Breast Cancer Diagnosis Based On A Rough Set And Extreme Learning Machine: Rs + Elm, Yilmaz Kaya

Turkish Journal of Electrical Engineering and Computer Sciences

Breast cancer is one of the leading causes of death among women all around the world. Therefore, true and early diagnosis of breast cancer is an important problem. The rough set (RS) and extreme learning machine (ELM) methods were used collectively in this study for the diagnosis of breast cancer. The unnecessary attributes were discarded from the dataset by means of the RS approach. The classification process by means of ELM was performed using the remaining attributes. The Wisconsin Breast Cancer dataset (WBCD), derived from the University of California Irvine machine learning database, was used for the purpose of testing …

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Energy Efficiency Performance Improvements For Ant-Based Routing Algorithm In Wireless Sensor Networks, A. M. Zungeru, Kah Phooi Seng, Li-Minn Ang, W.C. Chia Jan 2013

Energy Efficiency Performance Improvements For Ant-Based Routing Algorithm In Wireless Sensor Networks, A. M. Zungeru, Kah Phooi Seng, Li-Minn Ang, W.C. Chia

Research outputs 2013

The main problem for event gathering in wireless sensor networks (WSNs) is the restricted communication range for each node. Due to the restricted communication range and high network density, event forwarding in WSNs is very challenging and requires multihop data forwarding. Currently, the energy-efficient ant based routing (EEABR) algorithm, based on the ant colony optimization (ACO) metaheuristic, is one of the state-of-the-art energy-aware routing protocols. In this paper, we propose three improvements to the EEABR algorithm to further improve its energy efficiency. The improvements to the original EEABR are based on the following: (1) a new scheme to intelligently initialize …

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Novelty-Assisted Interactive Evolution Of Control Behaviors, Brian G. Woolley Jan 2012

Novelty-Assisted Interactive Evolution Of Control Behaviors, Brian G. Woolley

Electronic Theses and Dissertations

The field of evolutionary computation is inspired by the achievements of natural evolution, in which there is no final objective. Yet the pursuit of objectives is ubiquitous in simulated evolution because evolutionary algorithms that can consistently achieve established benchmarks are lauded as successful, thus reinforcing this paradigm. A significant problem is that such objective approaches assume that intermediate stepping stones will increasingly resemble the final objective when in fact they often do not. The consequence is that while solutions may exist, searching for such objectives may not discover them. This problem with objectives is demonstrated through an experiment in this …

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Evolving Machine Morality Strategies Through Multiagent Simulations, David Burke Jun 2011

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 …

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Developing An Effective And Efficient Real Time Strategy Agent For Use As A Computer Generated Force, Kurt Weissgerber Mar 2010

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 …

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Controlling The Uncontrollable: A New Approach To Digital Storytelling Using Autonomous Virtual Actors And Environmental Manipulation, Matthew J. Colon Mar 2010

Controlling The Uncontrollable: A New Approach To Digital Storytelling Using Autonomous Virtual Actors And Environmental Manipulation, Matthew J. Colon

Master's Theses

In most video games today that focus on a single story, scripting languages are used for controlling the artificial intelligence of the virtual actors. While scripting is a great tool for reliably performing a story, it has many disadvantages; mainly, it is limited by only being able to respond to those situations that were explicitly declared, causing unreliable responses to unknown situations, and the believability of the virtual actor is hindered by possible conflicts between scripted actions and appropriate responses as perceived by the viewer. This paper presents a novel method of storytelling by manipulating the environment, whether physically or …

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Episodic Memory Model For Embodied Conversational Agents, Miguel Elvir Jan 2010

Episodic Memory Model For Embodied Conversational Agents, Miguel Elvir

Electronic Theses and Dissertations

Embodied Conversational Agents (ECA) form part of a range of virtual characters whose intended purpose include engaging in natural conversations with human users. While works in literature are ripe with descriptions of attempts at producing viable ECA architectures, few authors have addressed the role of episodic memory models in conversational agents. This form of memory, which provides a sense of autobiographic record-keeping in humans, has only recently been peripherally integrated into dialog management tools for ECAs. In our work, we propose to take a closer look at the shared characteristics of episodic memory models in recent examples from the field. …

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Least Squares Support Vector Machine Based Classification Of Abnormalities In Brain Mr Images, S. Thamarai Selvi, D. Selvathi, R. Ramkumar, Henry Selvaraj Mar 2006

Least Squares Support Vector Machine Based Classification Of Abnormalities In Brain Mr Images, S. Thamarai Selvi, D. Selvathi, R. Ramkumar, Henry Selvaraj

Electrical & Computer Engineering Faculty Research

The manual interpretation of MRI slices based on visual examination by radiologist/physician may lead to missing diagnosis when a large number of MRIs are analyzed. To avoid the human error, an automated intelligent classification system is proposed. This research paper proposes an intelligent classification technique to the problem of classifying four types of brain abnormalities viz. Metastases, Meningiomas, Gliomas, and Astrocytomas. The abnormalities are classified based on Two/Three/ Four class classification using statistical and textural features. In this work, classification techniques based on Least Squares Support Vector Machine (LS-SVM) using textural features computed from the MR images of patient are …

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Salient Closed Boundary Extraction With Ratio Contour, Song Wang, Toshiro Kubota, Jeffrey Mark Siskind, Jun Wang Apr 2005

Salient Closed Boundary Extraction With Ratio Contour, Song Wang, Toshiro Kubota, Jeffrey Mark Siskind, Jun Wang

Faculty Publications

We present ratio contour, a novel graph-based method for extracting salient closed boundaries from noisy images. This method operates on a set of boundary fragments that are produced by edge detection. Boundary extraction identifies a subset of these fragments and connects them sequentially to form a closed boundary with the largest saliency. We encode the Gestalt laws of proximity and continuity in a novel boundary-saliency measure based on the relative gap length and average curvature when connecting fragments to form a closed boundary. This new measure attempts to remove a possible bias toward short boundaries. We present a polynomial-time algorithm …

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Automation Laboratory Development With Design Implementation Scheme And Simulation Software, Cheng Y. Lin, Gary R. Crossman Jan 2004

Automation Laboratory Development With Design Implementation Scheme And Simulation Software, Cheng Y. Lin, Gary R. Crossman

Engineering Technology Faculty Publications

This paper describes the development of the Automation Control Lab in the Mechanical Engineering Technology Program of the Engineering Technology Department at Old Dominion University. The reorganization goal of the development is to help students design, test, and implement their automation designs effectively. Three processes are adopted to achieve this goal: (1) floor-plan design and inventory control of the components, (2) using Automation Studio to dynamically check each design, and (3) using industrial Programmable Logic Controllers (PLC) controllers to download PLC programs.

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The Sentient Web, Michael N. Huhns Jan 2003

The Sentient Web, Michael N. Huhns

Faculty Publications

In a startling revelation, a team of university scientists has reported that a network of computers has become conscious and sentient, and is beginning to assume control of online information system. In spite of the ominous tone typically chosen for dramatic effect, a sentient Web would be more helpful and much easier for people to use. An agent is an active, persistent software component that perceives, reasons, and acts, and whose actions include communication. Agents inherently take intentional actions based on sensory information and memories of past actions. All agents have necessary communication ability, but they do not necessarily possess …

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Massive Deliberation, William H. Turkett Jr., John R. Rose, Michael N. Huhns Jan 2003

Massive Deliberation, William H. Turkett Jr., John R. Rose, Michael N. Huhns

Faculty Publications

Agents are proliferating on the Web, making it conceivable that their collective reasoning ability might someday be harnessed for robust decision-making. The hope is that massive deliberation power can soon help solve problems that require knowledge, reasoning, and intelligence. Until recently, working individually or in small groups, agents across the Web could barely communicate and could only reason under conditions of severely bounded rationality. Projects such as Agentcities showed that widespread heterogeneous agents could collaborate on specific predefined tasks and provide diverse agent-based services. When the tasks are dynamic, of long duration, and ill defined, however, success requires planning that …

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Diagnostics Of Bar And End-Ring Connector Breakage Faults In Polyphase Induction Motors Through A Novel Dual Track Of Time-Series Data Mining And Time-Stepping Coupled Fe-State Space Modeling, Richard J. Povinelli, John F. Bangura, Nabeel Demerdash, Ronald H. Brown Mar 2002

Diagnostics Of Bar And End-Ring Connector Breakage Faults In Polyphase Induction Motors Through A Novel Dual Track Of Time-Series Data Mining And Time-Stepping Coupled Fe-State Space Modeling, Richard J. Povinelli, John F. Bangura, Nabeel Demerdash, Ronald H. Brown

Electrical and Computer Engineering Faculty Research and Publications

This paper develops the fundamental foundations of a technique for detection of faults in induction motors that is not based on the traditional Fourier transform frequency domain approach. The technique can extensively and economically characterize and predict faults from the induction machine adjustable speed drive design data. This is done through the development of dual-track proof-of-principle studies of fault simulation and identification. These studies are performed using our proven Time Stepping Coupled Finite Element-State Space method to generate fault case data. Then, the fault cases are classified by their inherent characteristics, so-called “signatures” or “fingerprints.” These fault signatures are extracted …

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Information Domain Modeling Of Emergent Phenomena, Ron Fulbright Jan 2002

Information Domain Modeling Of Emergent Phenomena, Ron Fulbright

Theses and Dissertations

Study in fields such as distributed artificial intelligence (DAI), decentralized artificial intelligence (DzAI), parallel artificial intelligence (PAl), multiagent systems (MAS), computer supported cooperative work (CSCW), artificial life (AL), and complex adaptive systems (CAS) is concerned with the cooperation, coordination, communication, and coherence of multiple agents working together to achieve a common goal. The notion that the ability of a collective can exceed the sum of the individuals is a fundamental concept and a generally accepted truth. However, no general theoretical explanation exists as to why this could or should be the case. This dissertation explores such an explanation by considering …

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Development Of Self-Adaptive Back Propagation And Derivative Free Training Algorithms In Artificial Neural Networks, Shamsuddin Ahmed Jan 2000

Development Of Self-Adaptive Back Propagation And Derivative Free Training Algorithms In Artificial Neural Networks, Shamsuddin Ahmed

Theses: Doctorates and Masters

Three new iterative, dynamically self-adaptive, derivative-free and training parameter free artificial neural network (ANN) training algorithms are developed. They are defined as self-adaptive back propagation, multi-directional and restart ANN training algorithms. The descent direction in self-adaptive back propagation training is determined implicitly by a central difference approximation scheme, which chooses its step size according to the convergence behavior of the error function. This approach trains an ANN when the gradient information of the corresponding error function is not readily available. The self- adaptive variable learning rates per epoch are determined dynamically using a constrained interpolation search. As a result, appropriate …

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Constructive Induction Machines For Data Mining, Marek Perkowski, Stanislaw Grygiel, Qihong Chen, Dave Mattson Mar 1999

Constructive Induction Machines For Data Mining, Marek Perkowski, Stanislaw Grygiel, Qihong Chen, Dave Mattson

Electrical and Computer Engineering Faculty Publications and Presentations

"Learning Hardware" approach involves creating a computational network based on feedback from the environment (for instance, positive and negative examples from the trainer), and realizing this network in an array of Field Programmable Gate Arrays (FPGAs). Computational networks can be built based on incremental supervised learning (Neural Net training) or global construction (Decision Tree design). Here we advocate the approach to Learning Hardware based on Constructive Induction methods of Machine Learning (ML) using multivalued functions. This is contrasted with the Evolvable Hardware (EHW) approach in which learning/evolution is based on the genetic algorithm only.

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Hardware Implementation Of The Complex Hopfield Neural Network, Chih Kang Cheng Jan 1995

Hardware Implementation Of The Complex Hopfield Neural Network, Chih Kang Cheng

Theses Digitization Project

No abstract provided.

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An Intelligent Real-Time System Architecture Implemented In Ada, Michael A. Whelan Dec 1992

An Intelligent Real-Time System Architecture Implemented In Ada, Michael A. Whelan

Theses and Dissertations

Conventional real-time systems are fully deterministic allowing for off-line, optimal, task scheduling under all circumstances. Real-time intelligent systems add non-deterministic task execution times and non- deterministic task sets for scheduling purposes. Non-deterministic task sets force intelligent real-time systems to trade-off execution time with solution quality during run-time and perform dynamic task scheduling. Four basic design considerations addressing those tradeoffs have been identified: control reasoning, focus of attention, parallelism, and algorithm efficacy. Non-real- time intelligent systems contain an environment sensor, a model of the environment, a reasoning process, and a large collection of procedural processes. Real-time intelligent systems add to these …

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Boolean Reasoning And Informed Search In The Minimization Of Logic Circuits, James J. Kainec Mar 1992

Boolean Reasoning And Informed Search In The Minimization Of Logic Circuits, James J. Kainec

Theses and Dissertations

The minimization of logic circuits has been an important area of research for more than a half century. The approaches taken in this field, however, have for the most part been ad hoc. Boolean techniques have been employed to manipulate formulas, but not to perform symbolic reasoning. Boolean equations are employed principally as icons; they are never solved. The first objective of this dissertation is to apply Boolean reasoning systematically and uniformly to the minimization problem. Boolean reasoning entails the reduction of systems of Boolean equations to a single equation; the single equation is an abstraction, independent of the form …

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