Artificial Intelligence and Robotics Commons^™

Drift Detection Using Uncertainty Distribution Divergence, Patrick Lindstrom, Brian Mac Namee, Sarah Jane Delany

Conference papers

Concept drift is believed to be prevalent inmost data gathered from naturally occurring processes andthus warrants research by the machine learning community.There are a myriad of approaches to concept drift handlingwhich have been shown to handle concept drift with varyingdegrees of success.

However, most approaches make the keyassumption that the labelled data will be available at nolabelling cost shortly after classification, an assumption whichis often violated. The high labelling cost in many domainsprovides a strong motivation to reduce the number of labelledinstances required to handle concept drift. Explicit detectionapproaches that do not require labelled instances to detectconcept drift show great …

Mobile Phone Graph Evolution: Findings, Model And Interpretation, Siyuan Liu, Lei Li, Christos Faloutsos, Lionel M. Ni

LARC Research Publications

What are the features of mobile phone graph along the time? How to model these features? What are the interpretation for the evolutional graph generation process? To answer the above challenging problems, we analyze a massive who-call-whom networks as long as a year, gathered from records of two large mobile phone communication networks both with 2 million users and 2 billion of calls. We examine the calling behavior distribution at multiple time scales (e.g. day, week, month and quarter), and find that the distribution is not only skewed with a heavy tail, but also changing at different time scales. How …

Capir: Collaborative Action Planning With Intention Recognition, Nguyen T., Hsu D., Lee W., Tze-Yun Leong, Kaelbling L., Lozano-Perez T., Grant A.

Research Collection School Of Computing and Information Systems

We apply decision theoretic techniques to construct nonplayer characters that are able to assist a human player in collaborative games. The method is based on solving Markov decision processes, which can be difficult when the game state is described by many variables. To scale to more complex games, the method allows decomposition of a game task into subtasks, each of which can be modelled by a Markov decision process. Intention recognition is used to infer the subtask that the human is currently performing, allowing the helper to assist the human in performing the correct task. Experiments show that the method …

Automating Construction And Selection Of A Neural Network Using Stochastic Optimization, Jason Lee Hurt

UNLV Theses, Dissertations, Professional Papers, and Capstones

An artificial neural network can be used to solve various statistical problems by approximating a function that provides a mapping from input to output data. No universal method exists for architecting an optimal neural network. Training one with a low error rate is often a manual process requiring the programmer to have specialized knowledge of the domain for the problem at hand.

A distributed architecture is proposed and implemented for generating a neural network capable of solving a particular problem without specialized knowledge of the problem domain. The only knowledge the application needs is a training set that the network …

Contributions Of Financial Sector Reforms And Credit Supply To Nigerian Agricultural Sector (1978-2009), Anthony O. Onoja, M. E. Onu, S. Ajodo-Ohiemi

CBN Journal of Applied Statistics (JAS)

This study analyzed the trends and pattern of institutional credit supply to agriculture during pre- and post-financial reforms along with their determinants. It then compared the effects of reform policies on access to institutional credits in Nigerian agricultural sector before and after the reforms (1978 - 1985; and 1986 -2009). Relying mainly on time series data from CBN and NBS, it used ordinary least squares method (linear, semi-log and double log) to model the determinants of banking sector lending to the agricultural sector during the review period. The models were subjected to several econometric tests before accepting one. Chow test …

Determinants Of Foreign Reserves In Nigeria: An Autoregressive Distributed Lag Approach, David Irefin, Baba N. Yaaba

CBN Journal of Applied Statistics (JAS)

On global scale, central banks’ holdings of foreign reserves have escalated sharply in recent years. World international reserves holdings have risen significantly from US$1.2 trillion in 1995 to nearly US$10.0 trillion in June 2011. Dominant among these reserves are concentrated in the hands of few countries. Ten major holders of foreign reserves are mostly from Asia. Oil exporting countries in Africa and the Middle East are not left out in this trend. Nigeria’s foreign reserves rose from US$5.5 billion in 1999 to US$62.40 billion in July 2008, making Nigeria the twenty-fourth largest reserves holder in the world. This pace of …

Effects Of Exchange Rate Movements On Economic Growth In Nigeria, Eme O. Akpan, Johnson A. Atan

CBN Journal of Applied Statistics (JAS)

This study investigates the effect of exchange rate movements on real output growth in Nigeria. Based on quarterly series for the period 1986 to 2010, the paper examines the possible direct and indirect relationship between exchange rates and GDP growth. The relationship is derived in two ways using a simultaneous equations model within a fully specified (but small) macroeconomic model. A Generalised Method of Moments (GMM) technique was explored. The estimation results suggest that there is no evidence of a strong direct relationship between changes in exchange rate and output growth. Rather, Nigeria’s economic growth has been directly affected by …

Exchange Rate Volatility In Nigeria: Consistency, Persistency & Severity Analyses, Babatunde Adeoye, Akinwande A. Atanda

CBN Journal of Applied Statistics (JAS)

The adoption of the International Monetary Fund (IMF) Structural Adjustment Programme (SAP) in 1986 resulted in the transition from fixed exchange rate regime to floating exchange rate regime in Nigeria. Ever since, the exchange rate of naira vis-à-vis the U.S dollar has attained varying rates all through different time horizons. On this basis, this study examines the consistency, persistency, and severity (degree) of volatility in exchange rate of Nigerian currency (naira) vis-a-vis the United State dollar using monthly time series data from 1986 to 2008. The standard Purchasing Power Parity (PPP) model was used to analyze the long-run consistency of …

Foreign Private Investment And Economic Growth In Nigeria: A Cointegrated Var And Granger Causality Analysis, F. Z. Abdullahi, S. Ladan, Haruna R. Bakari

CBN Journal of Applied Statistics (JAS)

This research uses a cointegration VAR model to study the contemporaneous long-run dynamics of the impact of Foreign Private Investment (FPI), Interest Rate (INR) and Inflation rate (IFR) on Growth Domestic Products (GDP) in Nigeria for the period January 1970 to December 2009. The Unit Root Test suggests that all the variables are integrated of order 1. The VAR model was appropriately identified using AIC information criteria and the VECM model has exactly one cointegration relation. The study further investigates the causal relationship using the Granger causality analysis of VECM which indicates a uni-directional causality relationship between GDP and FDI …

Banking Sector Credit And Economic Growth In Nigeria: An Empirical Investigation, Aniekan O. Akpansung, Sikiru J. Babalola

CBN Journal of Applied Statistics (JAS)

The paper examines the relationship between banking sector credit and economic growth in Nigeria over the period 1970-2008. The causal links between the pairs of variables of interest were established using Granger causality test while a Two-Stage Least Squares (TSLS) estimation technique was used for the regression models. The results of Granger causality test show evidence of unidirectional causal relationship from GDP to private sector credit (PSC) and from industrial production index (IND) to GDP. Estimated regression models indicate that private sector credit impacts positively on economic growth over the period of coverage in this study. However, lending (interest) rate …

Towards Textually Describing Complex Video Contents With Audio-Visual Concept Classifiers, Chun Chet Tan, Yu-Gang Jiang, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Automatically generating compact textual descriptions of complex video contents has wide applications. With the recent advancements in automatic audio-visual content recognition, in this paper we explore the technical feasibility of the challenging issue of precisely recounting video contents. Based on cutting-edge automatic recognition techniques, we start from classifying a variety of visual and audio concepts in video contents. According to the classification results, we apply simple rule-based methods to generate textual descriptions of video contents. Results are evaluated by conducting carefully designed user studies. We find that the state-of-the-art visual and audio concept classification, although far from perfect, is able …

A Brain-Inspired Model Of Hierarchical Planner, Budhitama Subagdja, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Hierarchical planning is an approach of planning by composing and executing hierarchically arranged plans to solve some problems. Most symbolic-based hierarchical planners have been devised to allow the knowledge to be described expressively. However, a great challenge is to automatically seek and acquire new plans on the fly. This paper presents a novel neural-based model of hierarchical planning that can seek and acquired new plans on-line if the necessary knowledge are lacking. Inspired by findings in neuropsychology, plans can be inherently learnt, retrieved, and manipulated simultaneously rather than discretely processed like in most symbolic approaches. Using a multi-channel adaptive resonance …

A Pomdp Model For Guiding Taxi Cruising In A Congested Urban City, Lucas Agussurja, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

We consider a partially observable Markov decision process (POMDP) model for improving a taxi agent cruising decision in a congested urban city. Using real-world data provided by a large taxi company in Singapore as a guide, we derive the state transition function of the POMDP. Specifically, we model the cruising behavior of the drivers as continuous-time Markov chains. We then apply dynamic programming algorithm for finding the optimal policy of the driver agent. Using a simulation, we show that this policy is significantly better than a greedy policy in congested road network.

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 …

Influence Diagrams With Memory States: Representation And Algorithms, Xiaojian Wu, Akshat Kumar, Shlomo Zilberstein

Research Collection School Of Computing and Information Systems

Influence diagrams (IDs) offer a powerful framework for decision making under uncertainty, but their applicability has been hindered by the exponential growth of runtime and memory usage--largely due to the no-forgetting assumption. We present a novel way to maintain a limited amount of memory to inform each decision and still obtain near-optimal policies. The approach is based on augmenting the graphical model with memory states that represent key aspects of previous observations--a method that has proved useful in POMDP solvers. We also derive an efficient EM-based message-passing algorithm to compute the policy. Experimental results show that this approach produces highquality …

Allocating Resources In Multiagent Flowshops With Adaptive Auctions, Hoong Chuin Lau, Zhengyi Zhao, Sam Shuzhi Ge, Thong Heng Lee

Research Collection School Of Computing and Information Systems

In this paper, we consider the problem of allocating machine resources among multiple agents, each of which is responsible to solve a flowshop scheduling problem. We present an iterated combinatorial auction mechanism in which bid generation is performed within each agent, while a price adjustment procedure is performed by a centralized auctioneer. While this approach is fairly well-studied in the literature, our primary innovation is in an adaptive price adjustment procedure, utilizing variable step-size inspired by adaptive PID-control theory coupled with utility pricing inspired by classical microeconomics. We compare with the conventional price adjustment scheme proposed in Fisher (1985), and …

Improving Occupancy Grid Fastslam By Integrating Navigation Sensors, Christopher Weyers, Gilbert L. Peterson

Faculty Publications

When an autonomous vehicle operates in an unknown environment, it must remember the locations of environmental objects and use those object to maintain an accurate location of itself. This vehicle is faced with Simultaneous Localization and Mapping (SLAM), a circularly defined robotics problem of map building with no prior knowledge. The SLAM problem is a difficult but critical component of autonomous vehicle exploration with applications to search and rescue missions. This paper presents the first SLAM solution combining stereo cameras, inertial measurements, and vehicle odometry into a Multiple Integrated Navigation Sensor (MINS) path. The FastSLAM algorithm, modified to make use …

Implementation Of A New Sigmoid Function In Backpropagation Neural Networks., Jeffrey A. Bonnell

Electronic Theses and Dissertations

This thesis presents the use of a new sigmoid activation function in backpropagation artificial neural networks (ANNs). ANNs using conventional activation functions may generalize poorly when trained on a set which includes quirky, mislabeled, unbalanced, or otherwise complicated data. This new activation function is an attempt to improve generalization and reduce overtraining on mislabeled or irrelevant data by restricting training when inputs to the hidden neurons are sufficiently small. This activation function includes a flattened, low-training region which grows or shrinks during back-propagation to ensure a desired proportion of inputs inside the low-training region. With a desired low-training proportion of …

Taxisim: A Multiagent Simulation Platform For Evaluating Taxi Fleet Operations, Shih-Fen Cheng, Thi Duong Nguyen

Research Collection School Of Computing and Information Systems

Taxi service is an important mode of public transportation in most metropolitan areas since it provides door-to-door convenience in the public domain. Unfortunately, despite all the convenience taxis bring, taxi fleets are also extremely inefficient to the point that over 50% of its operation time could be spent in idling state. Improving taxi fleet operation is an extremely challenging problem, not just because of its scale, but also due to fact that taxi drivers are self-interested agents that cannot be controlled centrally. To facilitate the study of such complex and decentralized system, we propose to construct a multiagent simulation platform …

Networks - I: Computational Intelligence Based Optimization In Wireless Sensor Network, Rabia Iram, Muhammad Irfan Sheikh, Sohail Jabbar, Abid Ali Minhas

International Conference on Information and Communication Technologies

There are only two ways to live your life. One is as though nothing is a miracle. The other is as though everything is a miracle and so the technology advancement which proved to be a miracle of the miracles. Wireless Sensor Network (WSN) is one such miracle of the wireless technology which opens up the new dimensions for the researchers to write the technology of the future i.e. ubiquitous computing and intelligence. Nevertheless nature has played its ultimate role as well to give an idea of perfection in optimizing the teething issues in any field and so in WSN. …

Artificial Intelligence - I: Design, Low Cost Implementation And Comparison Of Mimo Mamdani Fuzzy Logic Controllers For Wall Tracking Behavior Of Mobile Robot, Umar Farooq, K. M. Hasan, Ghulam Abbas, Muhammad Usman Asad, Syed Omer Saleh

International Conference on Information and Communication Technologies

This paper describes the design, implementation and comparison of two Mamdani Fuzzy Logic Controllers for wall tracking behavior of mobile robot. Both the controllers take inputs from two ultrasonic sensors and generate motion commands for left and right motors. The controllers are designed using MATLAB and implemented in real time using an inexpensive and readily available microcontroller, AT89C52. The controllers differ in membership functions and the rule base which provides a mean for their comparison. Experimental results have validated both the controllers; however they exhibit different settling time and percentage overshoot due to the difference in the membership functions and …

Artificial Intelligence – I: Usability Studies In Haptic Systems, Muzafar Khan, Suziah Sulaiman, Abas M. Said, Muhammad Tahir

International Conference on Information and Communication Technologies

Haptic systems that deal with force and tactile feedback are widely used in different domains. Usability evaluation plays an important role to assess these systems and user's experience. Many usability evaluation studies for haptic systems have been reported but no effort is made to effectively summarize those works; thus, little is known on the extent in which the methods applied are useful for these systems. Literature survey is performed to find out the patterns related to different evaluation methods and haptic devices used in various domains. The survey findings indicate for a need of new usability methods that would be …

Artificial Intelligence – I: A Preliminary Framework For Human-Agent Communication In Electronic Negotiations, Moez Ur Rehman, Nosheen Riaz

International Conference on Information and Communication Technologies

Electronic negotiations are business negotiations conducted via electronic means using information and communications technologies (ICT). Two dominant types of electronic negotiation systems are automated negotiation systems for software agents and negotiation support systems (NSSs) for humans. However, the integration of two types for human-agent negotiations is an important task. In this paper, an extended communication model for human-agent business negotiations is presented. For this purpose, the underlying communication models of automated negotiations and NSSs are analyzed. The extended communication model is based on a common negotiation ontology which captures the negotiation agenda and paves the way for such hybrid communication, …

Finding Robust-Under-Risk Solutions For Flowshop Scheduling, Steven O. Kimbrough, Ann Kuo, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

We propose and explore, in the context of benchmark problems for flowshop scheduling, a risk-based concept of robustness for optimization problems. This risk-based concept is in distinction to, and complements, the uncertainty-based concept employed in the field known as robust optimization. Implementation of our concept requires problem solution methods that sample the solution space intelligently and that produce large numbers of distinct sample points. With these solutions to hand, their robustness scores are easily obtained and heuristically robust solutions found. We find evolutionary computation to be effective for this purpose on these problems.

Learning Author’S Writing Pattern System By Automata, Qun Yu

Master's Projects

The purpose of the report is to document our project’s theory, implementation and test results. The project works on an automata-based learning system which models authors’ writing characters with automatons. Since there were pervious works done by Dr. T.Y. Lin and Ms. S.X. Zhang, we continue on ALERGIA algorithm analysis and initial common pattern study in this project. Although every author has his/her own writing style, such as sentence length and word frequency etc, there are always some similarities in writing style. We hypothesize that common strings fogged the expected test result, just like the noise in radio wave. This …

Solution Pluralism And Metaheuristics, Steven O. Kimbrough, Ann Kuo, Hoong Chuin Lau, Frederic H. Murphy, David Harlan Wood

Research Collection School Of Computing and Information Systems

Solution pluralism is an approach to problem solving and deliberation. It employs a plurality of distinct solutions for a decision problem for aiding decision making. The concept is well established in existing practice, although perhaps not recognized as such. This paper: (1) presents the concept as a generalization of established practice, (2) briefly describes successful uses of the concept in practice, and (3) presents several areas that appear would benefit from application of the concept. Throughout, the role of metaheuristics in finding the pluralities of solutions is emphasized.

Scalable Multiagent Planning Using Probabilistic Inference, Akshat Kumar, Shlomo Zilberstein, Marc Toussaint

Research Collection School Of Computing and Information Systems

Multiagent planning has seen much progress with the development of formal models such as Dec-POMDPs. However, the complexity of these models -- NEXP-Complete even for two agents -- has limited scalability. We identify certain mild conditions that are sufficient to make multiagent planning amenable to a scalable approximation w.r.t. the number of agents. This is achieved by constructing a graphical model in which likelihood maximization is equivalent to plan optimization. Using the Expectation-Maximization framework for likelihood maximization, we show that the necessary inference can be decomposed into processes that often involve a small subset of agents, thereby facilitating scalability. We …

Message-Passing Algorithms For Quadratic Programming Formulations Of Map Estimation, Akshat Kumar, Shlomo Zilberstein

Research Collection School Of Computing and Information Systems

Computing maximum a posteriori (MAP) estimation in graphical models is an important inference problem with many applications. We present message-passing algorithms for quadratic programming (QP) formulations of MAP estimation for pairwise Markov random fields. In particular, we use the concave-convex procedure (CCCP) to obtain a locally optimal algorithm for the non-convex QP formulation. A similar technique is used to derive a globally convergent algorithm for the convex QP relaxation of MAP. We also show that a recently developed expectation-maximization (EM) algorithm for the QP formulation of MAP can be derived from the CCCP perspective. Experiments on synthetic and real-world problems …

Real-World Parameter Tuning Using Factorial Design With Parameter Decomposition, Aldy Gunawan, Hoong Chuin Lau, Elaine Wong

Research Collection School Of Computing and Information Systems

In this paper, we explore the idea of improving the efficiency of factorial design for parameter tuning of metaheuristics. In a standard full factorial design, the number of runs increases exponentially as the number of parameters. To reduce the parameter search space, one option is to first partition parameters into disjoint categories. While this may be done manually based on user guidance, an automated approach proposed in this paper is to apply a fractional factorial design to partition parameters based on their main effects where each partition is then tuned independently. With a careful choice of fractional design, our approach …

A Novel Methodology For Evaluating User Interfaces In Health Care, Luca Longo, Bridget Kane

Conference papers

A pilot study is reported to identify an improved method of evaluating digital user interfaces in health care. Experience and developments from the aviation industry and the NASA-TLX mental workload assessment tools are applied in conjunction with Nielsen heuristics for evaluating an Electronic Health Record System in an Irish hospital. The NASA-TLX performs subjective workload assessments on operators working with various human-computer systems. Results suggest that depending on the cognitive workload and the working context of users, the usability will differ for the same digital interface. We conclude that incorporating the NASA-TLX with Nielsen's heuristics offers a more reliable method …