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Noise, Delays, And Resonance In A Neural Network, Austin Quan 2011 Harvey Mudd College

Noise, Delays, And Resonance In A Neural Network, Austin Quan

HMC Senior Theses

A stochastic-delay differential equation (SDDE) model of a small neural network with recurrent inhibition is presented and analyzed. The model exhibits unexpected transient behavior: oscillations that occur at the boundary of the basins of attraction when the system is bistable. These are known as delay-induced transitory oscillations (DITOs). This behavior is analyzed in the context of stochastic resonance, an unintuitive, though widely researched phenomenon in physical bistable systems where noise can play in constructive role in strengthening an input signal. A method for modeling the dynamics using a probabilistic three-state model is proposed, and supported with numerical evidence. The potential …


Adaptive Decision Support For Structured Organizations: A Case For Orgpomdps, Pradeep Reddy VARAKANTHAM, Nathan Schurr, Alan Carlin, Christopher Amato 2011 Singapore Management University

Adaptive Decision Support For Structured Organizations: A Case For Orgpomdps, Pradeep Reddy Varakantham, Nathan Schurr, Alan Carlin, Christopher Amato

Research Collection School Of Computing and Information Systems

In today's world, organizations are faced with increasingly large and complex problems that require decision-making under uncertainty. Current methods for optimizing such decisions fall short of handling the problem scale and time constraints. We argue that this is due to existing methods not exploiting the inherent structure of the organizations which solve these problems. We propose a new model called the OrgPOMDP (Organizational POMDP), which is based on the partially observable Markov decision process (POMDP). This new model combines two powerful representations for modeling large scale problems: hierarchical modeling and factored representations. In this paper we make three key contributions: …


Distributed Model Shaping For Scaling To Decentralized Pomdps With Hundreds Of Agents, Prasanna VELAGAPUDI, Pradeep Reddy VARAKANTHAM, Katia Sycara, Paul Scerri 2011 Carnegie Mellon University

Distributed Model Shaping For Scaling To Decentralized Pomdps With Hundreds Of Agents, Prasanna Velagapudi, Pradeep Reddy Varakantham, Katia Sycara, Paul Scerri

Research Collection School Of Computing and Information Systems

The use of distributed POMDPs for cooperative teams has been severely limited by the incredibly large joint policy- space that results from combining the policy-spaces of the individual agents. However, much of the computational cost of exploring the entire joint policy space can be avoided by observing that in many domains important interactions between agents occur in a relatively small set of scenarios, previously defined as coordination locales (CLs) [11]. Moreover, even when numerous interactions might occur, given a set of individual policies there are relatively few actual interactions. Exploiting this observation and building on an existing model shaping algorithm, …


Message-Passing Algorithms For Large Structured Decentralized Pomdps, Akshat KUMAR, Shlomo ZILBERSTEIN 2011 Singapore Management University

Message-Passing Algorithms For Large Structured Decentralized Pomdps, Akshat Kumar, Shlomo Zilberstein

Research Collection School Of Computing and Information Systems

Decentralized POMDPs provide a rigorous framework for multi-agent decision-theoretic planning. However, their high complexity has limited scalability. In this work, we present a promising new class of algorithms based on probabilistic inference for infinite-horizon ND-POMDPs---a restricted Dec-POMDP model. We first transform the policy optimization problem to that of likelihood maximization in a mixture of dynamic Bayes nets (DBNs). We then develop the Expectation-Maximization (EM) algorithm for maximizing the likelihood in this representation. The EM algorithm for ND-POMDPs lends itself naturally to a simple message-passing paradigm guided by the agent interaction graph. It is thus highly scalable w.r.t. the number of …


Decentralized Decision Support For An Agent Population In Dynamic And Uncertain Domains, Pradeep Reddy VARAKANTHAM, Shih-Fen CHENG, Thi Duong NGUYEN 2011 Singapore Management University

Decentralized Decision Support For An Agent Population In Dynamic And Uncertain Domains, Pradeep Reddy Varakantham, Shih-Fen Cheng, Thi Duong Nguyen

Research Collection School Of Computing and Information Systems

This research is motivated by problems in urban transportation and labor mobility, where the agent flow is dynamic, non-deterministic and on a large scale. In such domains, even though the individual agents do not have an identity of their own and do not explicitly impact other agents, they have implicit interactions with other agents. While there has been much research in handling such implicit effects, it has primarily assumed controlled movements of agents in static environments. We address the issue of decision support for individual agents having involuntary movements in dynamic environments . For instance, in a taxi fleet serving …


Random Keys Genetic Algorithms Scheduling And Rescheduling Systems For Common Production Systems, Elkin Rodriguez-Velasquez 2011 Old Dominion University

Random Keys Genetic Algorithms Scheduling And Rescheduling Systems For Common Production Systems, Elkin Rodriguez-Velasquez

Engineering Management & Systems Engineering Theses & Dissertations

The majority of scheduling research deals with problems in specific production environments with specific objective functions. However, in many cases, more than one problem type and/or objective function exists, resulting in the need for a more generic and flexible system to generate schedules. Furthermore, most of the published scheduling research focuses on creating an optimal or near optimal initial schedule during the planning phase. However, after production processes start, circumstances like machine breakdowns, urgent jobs, and other unplanned events may render the schedule suboptimal, obsolete or even infeasible resulting in a "rescheduling" problem, which is typically also addressed for a …


Holistic Network Defense: Fusing Host And Network Features For Attack Classification, Jenny W. Ji 2011 Air Force Institute of Technology

Holistic Network Defense: Fusing Host And Network Features For Attack Classification, Jenny W. Ji

Theses and Dissertations

This work presents a hybrid network-host monitoring strategy, which fuses data from both the network and the host to recognize malware infections. This work focuses on three categories: Normal, Scanning, and Infected. The network-host sensor fusion is accomplished by extracting 248 features from network traffic using the Fullstats Network Feature generator and from the host using text mining, looking at the frequency of the 500 most common strings and analyzing them as word vectors. Improvements to detection performance are made by synergistically fusing network features obtained from IP packet flows and host features, obtained from text mining port, processor, logon …


Kernelized Locality-Sensitive Hashing For Fast Image Landmark Association, Mark A. Weems 2011 Air Force Institute of Technology

Kernelized Locality-Sensitive Hashing For Fast Image Landmark Association, Mark A. Weems

Theses and Dissertations

As the concept of war has evolved, navigation in urban environments where GPS may be degraded is increasingly becoming more important. Two existing solutions are vision-aided navigation and vision-based Simultaneous Localization and Mapping (SLAM). The problem, however, is that vision-based navigation techniques can require excessive amounts of memory and increased computational complexity resulting in a decrease in speed. This research focuses on techniques to improve such issues by speeding up and optimizing the data association process in vision-based SLAM. Specifically, this work studies the current methods that algorithms use to associate a current robot pose to that of one previously …


Recognition Situations Using Extended Dempster-Shafer Theory, Susan McKeever 2011 Technological University Dublin

Recognition Situations Using Extended Dempster-Shafer Theory, Susan Mckeever

Other resources

Weiser’s [111] vision of pervasive computing describes a world where technology seamlessly integrates into the environment, automatically responding to peoples’ needs. Underpinning this vision is the ability of systems to automatically track the situation of a person. The task of situation recognition is critical and complex: noisy and unreliable sensor data, dynamic situations, unpredictable human behaviour and changes in the environment all contribute to the complexity. No single recognition technique is suitable in all environments. Factors such as availability of training data, ability to deal with uncertain information and transparency to the user will determine which technique to use in …


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

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 …


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

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 …


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

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 …


A Model For Determining The Degree Of Contradictions In Information, Ram Gopal Raj 2011 University of Malaya

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 …


A One-Mode-For-All Predictor For Text Messaging, Ram Gopal Raj 2011 University of Malaya

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 …


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

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 …


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

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 …


Corrective Gradient Refinement For Mobile Robot Localization, Joydeep Biswas, Manuela M. Veloso, Brian Coltin 2011 University of Massachusetts Amherst

Corrective Gradient Refinement For Mobile Robot Localization, Joydeep Biswas, Manuela M. Veloso, Brian Coltin

Computer Science Department Faculty Publication Series

Particle filters for mobile robot localization must balance computational requirements and accuracy of localization. Increasing the number of particles in a particle filter improves accuracy, but also increases the computational requirements. Hence, we investigate a different paradigm to better utilize particles than to increase their numbers. To this end, we introduce the Corrective Gradient Refinement (CGR) algorithm that uses the state space gradients of the observation model to improve accuracy while maintaining low computational requirements. We develop an observation model for mobile robot localization using point cloud sensors (LIDAR and depth cameras) with vector maps. This observation model is then …


An Integrated Computer-Aided Robotic System For Dental Implantation, Xiaoyan Sun, Yongki Yoon, Jiang Li, Frederic D. McKenzie 2011 Old Dominion University

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 …


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

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.


Real-Time Behavior-Based Robot Control, Brian G. Wooley, Gilbert L. Peterson, Jared T. Kresge 2011 Air Force Institute of Technology

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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