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Artificial Intelligence and Robotics

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Articles 7921 - 7950 of 8483

Full-Text Articles in Physical Sciences and Mathematics

Enhanced Indoor Locationing In A Congested Wi-Fi Environment, Hsiuping Lin, Ying Zhang, Martin Griss, Ilya Landa Jan 2011

Enhanced Indoor Locationing In A Congested Wi-Fi Environment, Hsiuping Lin, Ying Zhang, Martin Griss, Ilya Landa

Martin L Griss

Many context-aware mobile applications require a reasonably accurate and stable estimate of a user’s location. While the Global Positioning System (GPS) works quite well world-wide outside of buildings and urban canyons, locating an indoor user in a real-world environment is much more problematic. Several different approaches and technologies have been explored, some involving specialized sensors and appliances, and others using increasingly ubiquitous Wi- Fi and Bluetooth radios. In this project, we want to leverage existing Wi-Fi access points (AP) and seek efficient approaches to gain usefully high room-level accuracy of the indoor location prediction of a mobile user. The Redpin …

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Punctuated Anytime Learning And The Xpilot-Ai Combat Environment, Phillip Fritzsche Jan 2011

Punctuated Anytime Learning And The Xpilot-Ai Combat Environment, Phillip Fritzsche

Computer Science Honors Papers

In this paper, research is presented on an application of Punctuated Anytime Learning with Fitness Biasing, a type of computational intelligence and evolutionary learning, for real-­time learning of autonomous agents controllers in the space combat game Xpilot. Punctuated Anytime Learning was originally developed as a means of effective learning in the field of evolutionary robotics. An analysis was performed on the game environment to determine optimal environmental settings for use during learning, and Fitness Biasing is employed using this information to learn intelligent behavior for a video game agent controller in real-­time. Xpilot-­AI, an Xpilot add-­on designed for testing learning …

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A Pattern Based Approach For The Derivation Of Base Forms Of Verbs From Participles And Tenses For Flexible Nlp, Ram Gopal Raj Jan 2011

A Pattern Based Approach For The Derivation Of Base Forms Of Verbs From Participles And Tenses For Flexible Nlp, Ram Gopal Raj

Ram Gopal Raj

Natural Language Processing (NLP) is an integral part of a conversation and by proxy an integral part of a chatterbot. Building a complete vocabulary for a chatterbot is a prohibitively time and effort intensive endeavor and thus makes a learning chatterbot a much more efficient alternative. Learning can be performed from many facets including individual words to phrases and concepts. From the perspective of words, the grammatical parts of speech become important since they allow meaning and structure to be derived from a sentence. Verbs tend to be unique since they have different forms, namely participles and tenses. As such …

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A Model For Determining The Degree Of Contradictions In Information, Ram Gopal Raj Jan 2011

A Model For Determining The Degree Of Contradictions In Information, Ram Gopal Raj

Ram Gopal Raj

Conversational systems are gaining popularity rapidly. Consequently, the believability of the conversational systems or chatterbots is becoming increasingly important. Recent research has proven that learning chatterbots tend to be rated as being more believable by users. Based on Raj’s Model for Chatterbot Trust, we present a model for allowing chatterbots to determine the degree of contradictions in contradictory statements when learning thereby allowing them to potentially learn more accurately via a form of discourse. Some information that is learnt by a chatterbot may be contradicted by other information presented subsequently. Choosing correctly which information to use is critical in chatterbot …

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A One-Mode-For-All Predictor For Text Messaging, Ram Gopal Raj Jan 2011

A One-Mode-For-All Predictor For Text Messaging, Ram Gopal Raj

Ram Gopal Raj

This paper discusses the enhancements made on the current mobile phone messaging software, namely the predictive text entry. In addition, the application also has a facility to abbreviate any unabbreviated words that exist in the dictionary, so that the message length can be reduced. The application was tested in a computer-simulated mobile environment and the results of the tests are presented here. These additional features will potentially enable users to send messages at a reduced length and thus reduce the cost of sending messages. Moreover, users who are not adept in using the abbreviations can now do so with features …

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A Simple Approach For Education Using Virtual Human Dataset, Chaw Seng Woo Dr. Jan 2011

A Simple Approach For Education Using Virtual Human Dataset, Chaw Seng Woo Dr.

Chaw Seng Woo Dr.

The virtual tour of human body is a system which is able to generate a three – dimensional image of a human bodybased on the human dataset. Virtual human body systems prepare an environment for medical practitioners to treat certainmedical conditions especially those which require surgery, precision and planning according to individual patients. Currentvirtual human body systems have some drawbacks and shortages especially as a study aid system, so the proposed system inthis research tries to fulfill the shortages as a proper study aid system. The objective of this research is to develop a systemthat can simulate fly – through …

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Automatic Annotation Of Referring Expression In Situated Dialogues, Niels Schütte, John D. Kelleher, Brian Mac Namee Jan 2011

Automatic Annotation Of Referring Expression In Situated Dialogues, Niels Schütte, John D. Kelleher, Brian Mac Namee

Articles

To apply machine learning techniques to the production and interpretation of natural language, we need large amounts of annotated language data. Manual annotation, however, is an expensive and time consuming process since it involves human annotators looking at the data and explicitly adding information that is implicitly contained in the data, based on their judgment. This work presents an approach to automatically annotating referring expressions in situated dialogues by exploiting the interpretation of language by the participants in the dia- logue. We associate instructions concerning objects in the environment with automatically detected events involving these objects and predict the referents …

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Feasibility Study Of Utility-Directed Behaviour For Computer Game Agents, Colm Sloan, John D. Kelleher, Brian Mac Namee Jan 2011

Feasibility Study Of Utility-Directed Behaviour For Computer Game Agents, Colm Sloan, John D. Kelleher, Brian Mac Namee

Conference papers

Utility-based control (UBC) hasn’t been widely adopted for commercial game AI. Some of the reasons for this are that UBC is perceived to be: (1) resource intensive, (2) difficult to design complex behaviours with, and (3) difficult to scale for use in complex environments. This paper investigates these perceptions to see if UBC is suitable for controlling the behaviour of non-player characters in commercial games. The investigation compares agents using a UBC system against two control systems that are more frequently used in commercial games: finite state machines (FSMs), considered a simple control system, and goal-oriented action planning (GOAP), considered …

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Autonomous Entropy-Based Intelligent Experimental Design, Nabin Kumar Malakar Jan 2011

Autonomous Entropy-Based Intelligent Experimental Design, Nabin Kumar Malakar

Legacy Theses & Dissertations (2009 - 2024)

The aim of this thesis is to explore the application of probability and information theory in experimental design, and to do so in a way that combines what we know about inference and inquiry in a comprehensive and consistent manner.

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An Exploration Of Multi-Agent Learning Within The Game Of Sheephead, Brady Brau Jan 2011

An Exploration Of Multi-Agent Learning Within The Game Of Sheephead, Brady Brau

All Graduate Theses, Dissertations, and Other Capstone Projects

In this paper, we examine a machine learning technique presented by Ishii et al. used to allow for learning in a multi-agent environment and apply an adaptation of this learning technique to the card game Sheephead. We then evaluate the effectiveness of our adaptation by running simulations against rule-based opponents. Multi-agent learning presents several layers of complexity on top of a single-agent learning in a stationary environment. This added complexity and increased state space is just beginning to be addressed by researchers. We utilize techniques used by Ishii et al. to facilitate this multi-agent learning. We model the environment of …

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Marine Buoy Detection Using Circular Hough Transform, Loc Tran, Justin Selfridge, Gene Hou, Jiang Li Jan 2011

Marine Buoy Detection Using Circular Hough Transform, Loc Tran, Justin Selfridge, Gene Hou, Jiang Li

Electrical & Computer Engineering Faculty Publications

A low cost method for buoy detection in maritime settings is presented using inexpensive digital cameras. In this method, the circular Hough transform is applied to an edge image to circular objects in the image. The center of these circles will signify the locations of each buoy. The known color information of the buoys is also used to enhance the performance by removing false detections. The algorithm is compared to an approach that locates buoys purely on color information. In order to validate the method, we test the approach synthetically and also with real images captured from a small surface …

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Improving Service Through Just-In-Time Concept In A Dynamic Operational Environment, Kar Way Tan, Hoong Chuin Lau, Na Fu Jan 2011

Improving Service Through Just-In-Time Concept In A Dynamic Operational Environment, Kar Way Tan, Hoong Chuin Lau, Na Fu

Research Collection School Of Computing and Information Systems

This paper is concerned with the problem of Just-In-Time (JIT) job scheduling in a dynamic environment under uncertainty to attain timely service. We provide an approach, based on robust scheduling concepts, to analytically evaluate the expected cost of earliness and tardiness for each job and also the project. In addition, we search for a schedule execution policy with the minimum robust cost such that for a given risk level (epsilon), the actual realized schedule has (1 - epsilon) probability of completing with less than or equal to this robust cost. Our method is quite generic, and can be applied to …

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Fine-Tuning Algorithm Parameters Using The Design Of Experiments Approach, Aldy Gunawan, Hoong Chuin Lau, Linda Lindawati Jan 2011

Fine-Tuning Algorithm Parameters Using The Design Of Experiments Approach, Aldy Gunawan, Hoong Chuin Lau, Linda Lindawati

Research Collection School Of Computing and Information Systems

Optimizing parameter settings is an important task in algorithm design. Several automated parameter tuning procedures/configurators have been proposed in the literature, most of which work effectively when given a good initial range for the parameter values. In the Design of Experiments (DOE), a good initial range is known to lead to an optimum parameter setting. In this paper, we present a framework based on DOE to find a good initial range of parameter values for automated tuning. We use a factorial experiment design to first screen and rank all the parameters thereby allowing us to then focus on the parameter …

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Would Price Limits Have Made Any Difference To The 'Flash Crash' On May 6, 2010, Wing Bernard Lee, Shih-Fen Cheng, Annie Koh Jan 2011

Would Price Limits Have Made Any Difference To The 'Flash Crash' On May 6, 2010, Wing Bernard Lee, Shih-Fen Cheng, Annie Koh

Research Collection School Of Computing and Information Systems

On May 6, 2010, the U.S. equity markets experienced a brief but highly unusual drop in prices across a number of stocks and indices. The Dow Jones Industrial Average (see Figure 1) fell by approximately 9% in a matter of minutes, and several stocks were traded down sharply before recovering a short time later. The authors contend that the events of May 6, 2010 exhibit patterns consistent with the type of "flash crash" observed in their earlier study (2010). This paper describes the results of nine different simulations created by using a large-scale computer model to reconstruct the critical elements …

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An Integrated Computer-Aided Robotic System For Dental Implantation, Xiaoyan Sun, Yongki Yoon, Jiang Li, Frederic D. Mckenzie Jan 2011

An Integrated Computer-Aided Robotic System For Dental Implantation, Xiaoyan Sun, Yongki Yoon, Jiang Li, Frederic D. Mckenzie

Electrical & Computer Engineering Faculty Publications

This paper describes an integrated system for dental implantation including both preoperative planning utilizing computer-aided technology and automatic robot operation during the intra-operative stage. A novel two-step registration procedure was applied for transforming the preoperative plan to the operation of the robot, with the help of a Coordinate Measurement Machine (CMM). Experiments with a patient-specific phantom were carried out to evaluate the registration error for both position and orientation. After adopting several improvements, registration accuracy of the system was significantly improved. Sub-millimeter accuracy with the Target Registration Errors (TREs) of 0.38±0.16 mm (N=5) was achieved. The target orientation errors after …

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Real-Time Behavior-Based Robot Control, Brian G. Wooley, Gilbert L. Peterson, Jared T. Kresge Jan 2011

Real-Time Behavior-Based Robot Control, Brian G. Wooley, Gilbert L. Peterson, Jared T. Kresge

Faculty Publications

Behavior-based systems form the basis of autonomous control for many robots, but there is a need to ensure these systems respond in a timely manner. Unexpected latency can adversely affect the quality of an autonomous system’s operations, which in turn can affect lives and property in the real-world. A robots ability to detect and handle external events is paramount to providing safe and dependable operation. This paper presents a concurrent version of a behavior-based system called the Real-Time Unified Behavior Framework, which establishes a responsive basis of behavior-based control that does not bind the system developer to any single behavior …

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Simulation, Application, And Resilience Of An Organic Neuromorphic Architecture, Made With Organic Bistable Devices And Organic Field Effect Transistors, Robert A. Nawrocki Jan 2011

Simulation, Application, And Resilience Of An Organic Neuromorphic Architecture, Made With Organic Bistable Devices And Organic Field Effect Transistors, Robert A. Nawrocki

Electronic Theses and Dissertations

This thesis presents work done simulating a type of organic neuromorphic architecture, modeled after Artificial Neural Network, and termed Synthetic Neural Network, or SNN. The first major contribution of this thesis is development of a single-transistor-single-organic-bistable-device-per-input circuit that approximates behavior of an artificial neuron. The efficacy of this design is validated by comparing the behavior of a single synthetic neuron to that of an artificial neuron as well as two examples involving a network of synthetic neurons. The analysis utilizes electrical characteristics of polymer electronic elements, namely Organic Bistable Device and Organic Field Effect Transistor, created in the laboratory at …

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Prediction Of Brain Tumor Progression Using Multiple Histogram Matched Mri Scans, Debrup Banerjee, Loc Tran, Jiang Li, Yuzhong Shen, Frederic Mckenzie, Jihong Wang, Ronald M. Summers (Ed.), Bram Van Ginneken (Ed.) Jan 2011

Prediction Of Brain Tumor Progression Using Multiple Histogram Matched Mri Scans, Debrup Banerjee, Loc Tran, Jiang Li, Yuzhong Shen, Frederic Mckenzie, Jihong Wang, Ronald M. Summers (Ed.), Bram Van Ginneken (Ed.)

Electrical & Computer Engineering Faculty Publications

In a recent study [1], we investigated the feasibility of predicting brain tumor progression based on multiple MRI series and we tested our methods on seven patients' MRI images scanned at three consecutive visits A, B and C. Experimental results showed that it is feasible to predict tumor progression from visit A to visit C using a model trained by the information from visit A to visit B. However, the trained model failed when we tried to predict tumor progression from visit B to visit C, though it is clinically more important. Upon a closer look at the MRI scans …

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Robotics In Hazardous Environments- Real Deployments By The Savannah River National Lab, Steven Tibrea, Thomas Nance, Eric Kriikku Jan 2011

Robotics In Hazardous Environments- Real Deployments By The Savannah River National Lab, Steven Tibrea, Thomas Nance, Eric Kriikku

Journal of the South Carolina Academy of Science

No abstract provided.

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Instance-Based Parameter Tuning Via Search Trajectory Similarity Clustering, Linda Lindawati, Hoong Chuin Lau, David Lo Jan 2011

Instance-Based Parameter Tuning Via Search Trajectory Similarity Clustering, Linda Lindawati, Hoong Chuin Lau, David Lo

Research Collection School Of Computing and Information Systems

This paper is concerned with automated tuning of parameters in local-search based meta-heuristics. Several generic approaches have been introduced in the literature that returns a ”one-size-fits-all” parameter configuration for all instances. This is unsatisfactory since different instances may require the algorithm to use very different parameter configurations in order to find good solutions. There have been approaches that perform instance-based automated tuning, but they are usually problem-specific. In this paper, we propose CluPaTra, a generic (problem-independent) approach to perform parameter tuning, based on CLUstering instances with similar PAtterns according to their search TRAjectories. We propose representing a search trajectory as …

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Imbalanced Learning For Functional State Assessment, Feng Li, Frederick Mckenzie, Jiang Li, Guanfan Zhang, Roger Xu, Carl Richey, Tom Schnell, Thomas E. Pinelli (Ed.) Jan 2011

Imbalanced Learning For Functional State Assessment, Feng Li, Frederick Mckenzie, Jiang Li, Guanfan Zhang, Roger Xu, Carl Richey, Tom Schnell, Thomas E. Pinelli (Ed.)

Electrical & Computer Engineering Faculty Publications

This paper presents results of several imbalanced learning techniques applied to operator functional state assessment where the data is highly imbalanced, i.e., some function states (majority classes) have much more training samples than other states (minority classes). Conventional machine learning techniques usually tend to classify all data samples into majority classis and perform poorly for minority classes. In this study, we implemented five imbalanced learning techniques, including random under-sampling, random over-sampling, synthetic minority over-sampling technique (SMOTE), borderline-SMOTE and adaptive synthetic sampling (ADASYN) to solve this problem. Experimental results on a benchmark driving test dataset show that accuracies for minority classes …

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Eeg Artifact Removal Using A Wavelet Neural Network, Hoang-Anh T. Nguyen, John Musson, Jiang Li, Frederick Mckenzie, Guangfan Zhang, Roger Xu, Carl Richey, Tom Schnell, Thomas E. Pinelli (Ed.) Jan 2011

Eeg Artifact Removal Using A Wavelet Neural Network, Hoang-Anh T. Nguyen, John Musson, Jiang Li, Frederick Mckenzie, Guangfan Zhang, Roger Xu, Carl Richey, Tom Schnell, Thomas E. Pinelli (Ed.)

Electrical & Computer Engineering Faculty Publications

In this paper we developed a wavelet neural network. (WNN) algorithm for Electroencephalogram (EEG) artifact removal without electrooculographic (EOG) recordings. The algorithm combines the universal approximation characteristics of neural network and the time/frequency property of wavelet. We compared the WNN algorithm with the ICA technique and a wavelet thresholding method, which was realized by using the Stein's unbiased risk estimate (SURE) with an adaptive gradient-based optimal threshold. Experimental results on a driving test data set show that WNN can remove EEG artifacts effectively without diminishing useful EEG information even for very noisy data.

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Hayek's Philosophical Psychology, Leslie Marsh Dec 2010

Hayek's Philosophical Psychology, Leslie Marsh

Leslie Marsh

Hayek's philosophical psychology as set out in his The Sensory Order (1952) has, for the most part, been neglected. Despite being lauded by computer scientist grandee Frank Rosenblatt and by Nobel prize-winning biologist Gerald Edelman, cognitive scientists -- with a few exceptions -- have yet to discover Hayek's philosophical psychology. On the other hand, social theorists, Hayek's traditional disciplinary constituency, have only recently begun to take note and examine the importance of psychology in the complete Hayek corpus. This volume brings together for the first time state-of-the-art contributions from neuroscientists and philosophers of mind as well as economists and social …

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Differentiable Cortical Networks For Inferences Concerning People’S Intentions Versus Physical Causality, Robert Mason, Marcel Just Dec 2010

Differentiable Cortical Networks For Inferences Concerning People’S Intentions Versus Physical Causality, Robert Mason, Marcel Just

Marcel Adam Just

No abstract provided.

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Autonomy Of Lower-Level Perception From Global Processing In Autism: Evidence From Brain Activation And Functional Connectivity, Yanni Liu, Vladimir L. Cherkassky, Nancy J. Minshew, Marcel Adam Just Dec 2010

Autonomy Of Lower-Level Perception From Global Processing In Autism: Evidence From Brain Activation And Functional Connectivity, Yanni Liu, Vladimir L. Cherkassky, Nancy J. Minshew, Marcel Adam Just

Marcel Adam Just

No abstract provided.

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Inter-Regional Brain Communication And Its Disturbance In Autism, Sarah E. Schipul, Timothy A. Keller, Marcel Adam Just Dec 2010

Inter-Regional Brain Communication And Its Disturbance In Autism, Sarah E. Schipul, Timothy A. Keller, Marcel Adam Just

Marcel Adam Just

No abstract provided.

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Computational Style Processing, Foaad Khosmood Dec 2010

Computational Style Processing, Foaad Khosmood

Foaad Khosmood

Our main thesis is that computational processing of natural language styles can be accomplished using corpus analysis methods and language transformation rules. We demonstrate this first by statistically modeling natural language styles, and second by developing tools that carry out style processing, and finally by running experiments using the tools and evaluating the results. Specifically, we present a model for style in natural languages, and demonstrate style processing in three ways: Our system analyzes styles in quantifiable terms according to our model (analysis), associates documents based on stylistic similarity to known corpora (classification) and manipulates texts to match a desired …

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Quantitative Modeling Of The Neural Representation Of Objects: How Semantic Feature Norms Can Account For Fmri Activation, Kai-Min Kevin Chang, Tom Mitchell, Marcel Adam Just Dec 2010

Quantitative Modeling Of The Neural Representation Of Objects: How Semantic Feature Norms Can Account For Fmri Activation, Kai-Min Kevin Chang, Tom Mitchell, Marcel Adam Just

Marcel Adam Just

No abstract provided.

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Individual Differences In The Neural Basis Of Causal Inferencing, Chantel S. Prat, Robert A. Mason, Marcel Adam Just Dec 2010

Individual Differences In The Neural Basis Of Causal Inferencing, Chantel S. Prat, Robert A. Mason, Marcel Adam Just

Marcel Adam Just

No abstract provided.

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Commonality Of Neural Representations Of Words And Pictures, Svetlana V. Shinkareva, Vincente L. Malave, Robert A. Mason, Tom M. Mitchell, Marcel Adam Just Dec 2010

Commonality Of Neural Representations Of Words And Pictures, Svetlana V. Shinkareva, Vincente L. Malave, Robert A. Mason, Tom M. Mitchell, Marcel Adam Just

Marcel Adam Just

No abstract provided.

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