Physical Sciences and Mathematics Commons^™

Towards Personalised Web Intelligence, Ah-Hwee Tan, Hwee-Leng Ong, Hong Pan, Jamie Ng, Qiu-Xiang Li

Research Collection School Of Computing and Information Systems

The Flexible Organizer for Competitive Intelligence (FOCI) is a personalised web intelligence system that provides an integrated platform for gathering, organising, tracking, and disseminating competitive information on the web. FOCI builds personalised information portfolios through a novel method called User-Configurable Clustering, which allows a user to personalise his/her portfolios in terms of the content as well as the organisational structure. This paper outlines the key challenges we face in personalised information management and gives a detailed account of FOCI’s underlying personalisation mechanism. For a quantitative evaluation of the system’s performance, we propose a set of performance indices based on information …

Taking Dcop To The Real World: Efficient Complete Solutions For Distributed Event Scheduling, Rajiv Maheswaran, Milind Tambe, Emma Bowring, Jonathan Pearce, Pradeep Varakantham

Research Collection School Of Computing and Information Systems

Distributed Constraint Optimization (DCOP) is an elegant formalism relevant to many areas in multiagent systems, yet complete algorithms have not been pursued for real world applications due to perceived complexity. To capably capture a rich class of complex problem domains, we introduce the Distributed Multi-Event Scheduling (DiMES) framework and design congruent DCOP formulations with binary constraints which are proven to yield the optimal solution. To approach real-world efficiency requirements, we obtain immense speedups by improving communication structure and precomputing best case bounds. Heuristics for generating better communication structures and calculating bound in a distributed manner are provided and tested on …

Notes On Equilibria In Symmetric Games, Shih-Fen Cheng, Daniel M. Reeves, Yevgeniy Vorobeychik, Michael P. Wellman

Research Collection School Of Computing and Information Systems

In a symmetric game, every player is identical with respect to the game rules. We show that a symmetric 2strategy game must have a pure-strategy Nash equilibrium. We also discuss Nash’s original paper and its generalized notion of symmetry in games. As a special case of Nash’s theorem, any finite symmetric game has a symmetric Nash equilibrium. Furthermore, symmetric infinite games with compact, convex strategy spaces and continuous, quasiconcave utility functions have symmetric pure-strategy Nash equilibria. Finally, we discuss how to exploit symmetry for more efficient methods of finding Nash equilibria.

Tournament Versus Fitness Uniform Selection, Shane Legg, Marcus Hutter, Akshat Kumar

Research Collection School Of Computing and Information Systems

In evolutionary algorithms a critical parameter that must be tuned is that of selection pressure. If it is set too low then the rate of convergence towards the optimum is likely to be slow. Alternatively if the selection pressure is set too high the system is likely to become stuck in a local optimum due to a loss of diversity in the population. The recent Fitness Uniform Selection Scheme (FUSS) is a conceptually simple but somewhat radical approach to addressing this problem - rather than biasing the selection towards higher fitness, FUSS biases selection towards sparsely populated fitness levels. In …

Multi-Period Multi-Dimensional Knapsack Problem And Its Application To Available-To-Promise, Hoong Chuin Lau, M. K. Lim

Research Collection School Of Computing and Information Systems

This paper is motivated by a recent trend in logistics scheduling, called Available-to-Promise. We model this problem as the multi-period multi-dimensional knapsack problem. We provide some properties for a special case of a single-dimensional problem. Based on insights obtained from these properties, we propose a two-phase heuristics for solving the multi-dimensional problem. We also propose a novel time-based ant colony optimization algorithm. The quality of the solutions generated is verified through experiments, where we demonstrate that the computational time is superior compared with integer programming to achieve solutions that are within a small percentage of the upper bounds.

Cognitive Robot Mapping With Polylines And An Absolute Space Representation, Kennard R. Laviers, Gilbert L. Peterson

Faculty Publications

Robot mapping even today is one of the most challenging problems in robot programming. Most successful methods use some form of occupancy grid to represent a mapped region. This approach becomes problematic if the robot is mapping a large environment, the map quickly becomes too large for processing and storage. Rather than storing the map as an occupancy grid, our robot (equipped with sonars) sees the world as a series of connected spaces. These spaces are initially mapped as an occupancy grid in a room by room fashion. As the robot leaves a space, denoted by passing through a doorway, …

Development Approaches Coupled With Verification And Validation Methodologies For Agent-Based Mission-Level Analytical Combat Simulations, Lance E. Champagne

Theses and Dissertations

This research investigated the applicability of agent-based combat simulations to real-world combat operations. An agent-based simulation of the Allied offensive search for German U-Boats in the Bay of Biscay during World War II was constructed, extending the state-of-the-art in agent-based combat simulations, bridging the gap between the current level of agent-like combat simulations and the concept of agent-based simulations found in the broader literature. The proposed simulation advances agent-based combat simulations to “validateable” mission-level military operations. Simulation validation is a complex task with numerous, diverse techniques available and levels of validation differing significantly among simulations and applications. This research presents …

Concurrent Cognitive Mapping And Localization Using Expectation Maximization, Kennard R. Laviers

Theses and Dissertations

Robot mapping remains one of the most challenging problems in robot programming. Most successful methods use some form of occupancy grid for representing a mapped region. An occupancy grid is a two dimensional array in which the array cells represents (x,y) coordinates of a cartesian map. This approach becomes problematic in mapping large environments as the map quickly becomes too large for processing and storage. Rather than storing the map as an occupancy grid, our robot (equipped with ultrasonic sonars) views the world as a series of connected spaces. These spaces are initially mapped as an occupancy grid in a …

Miniaturen. Studien Zu Kalkül Und Kreativität 1998-2002, Rudolf Kaehr

Rudolf Kaehr

Informatik, künstlerische Praktik und Kunsttheorie der digitalen Bildtechnologien NULL&NICHTS; weder leer, noch nicht – oder Kraut und Rüben Gedanken zu einer autonomen Medienwissenschaft Das Menschenbild aus der Sicht einer polykontexturalen Systemtheorie Thesen zum trans-klassischen Menschenbild Gebaute Phantasien, unkontrollierbare Schwankungen Kreativität und Kalkül Ver_Endungen in/der Programmierbarkeit Diagrammatik: Denken a la Carte Zur Verstörung des (H)ortes der Zerstörung Zur Kenogrammatik der Medientheorie

Dynamic Semantic Web, Rudolf Kaehr

Rudolf Kaehr

Dynamic Semantic Web (DSW) is based at first on the techniques, methods and paradigms of the emerging Semantic Web movement and its applications. DSW is advancing one fundamental step further from a static to a dynamic concept of the Semantic Web with extended flexibility in the navigation between ontologies and more profound transparency of the informational system. Web Services are now redefinded by Semantic Web. To proof the advantages of DSW, it is the main aim of this project to develop the tools and methods necessary to develop a DSW based Web Service (DSW business application). The existing framework of …

Capturing The Dialectic Between Principles And Cases, Kevin D. Ashley

Articles

Theorists in ethics and law posit a dialectical relationship between principles and cases; abstract principles both inform and are informed by the decisions of specific cases. Until recently, however, it has not been possible to investigate or confirm this relationship empirically. This work involves a systematic study of a set of ethics cases written by a professional association's board of ethical review. Like judges, the board explains its decisions in opinions. It applies normative standards, namely principles from a code of ethics, and cites past cases. We hypothesized that the board's explanations of its decisions elaborated upon the meaning and …

Investigation Of Implementation Techniques For Backpropagation Neural Networks, John Culloty

Theses

Artificial neural networks are biologically inspired computational methods that have the ability to approximate discrete, real and vector valued target functions. For some problem domains this ability makes neural networks a more appealing solution than traditional computational techniques. Such problem domains typically contain a large number of parameters that are interrelated in a complex and often unknown manner. This makes rule based solutions all but impossible. However another feature of such problem domains is the presence of large volumes of real world data that can be used to tram a neural network until it learns the solution.

One of the …

E-Rulemaking: Information Technology And The Regulatory Process: New Directions In Digital Government Research, Cary Coglianese

All Faculty Scholarship

Electronic rulemaking, or e-rulemaking, offers the potential to overcome some of the informational challenges associated with developing regulations. E-rulemaking refers to the use of digital technologies in the development and implementation of regulations. The use of these technologies may help streamline and improve regulatory management, such as by helping agency staff retrieve and analyze vast quantities of information from diverse sources. By taking better advantage of advances in digital technologies, agencies might also be able to increase the public's access to and involvement in rulemaking. Part I of this article details the rulemaking process, outlining the procedures agencies must currently …

Integrating Perception, Language And Problem Solving In A Cognitive Agent For A Mobile Robot., Deryle W. Lonsdale, D. Paul Benjamin, Damian M. Lyons

Faculty Publications

We are implementing a unified cognitive architecture for a mobile robot. Our goal is to endow a robot agent with the full range of cognitive abilities, including perception, use of natural language, learning and the ability to solve complex problems. The perspective of this work is that an architecture based on a unified theory of robot cognition has the best chance of attaining human-level performance.

This agent architecture is an integration of three theories: a theory of cognition embodied in the Soar system, the RS formal model of sensorimotor activity and an algebraic theory of decomposition and reformulation.

These three …

Logistics Outsourcing And 3pl Challenges, Michelle L. F. Cheong

Research Collection School Of Computing and Information Systems

Logistics has been an important part of every economy and every business entity. The worldwide trend in globalization has led to many companies outsourcing their logistics function to Third-Party Logistics (3PL) companies, so as to focus on their core competencies. This paper attempts to broadly identify and categorize the challenges faced by 3PL companies and discover potential gaps for future research. Some of the challenges will be related with the experience and information collected from interviews with two 3PL companies.

Imagery In Sentence Comprehension: An Fmri Study, Marcel Just, Sharlene Newman, Timothy Keller, Alice Mceleney, Patricia Carpenter

Marcel Adam Just

No abstract provided.

How The Brain Processes Causal Inferences In Text: A Theoretical Account Of Generation And Integration Component Processes Utilizing Both Cerebral Hemispheres, Robert Mason, Marcel Just

Marcel Adam Just

No abstract provided.

Learning To Decode Cognitive States From Brain Images, Tom M. Mitchell, Rebecca Hutchinson, Radu S. Niculescu, Francisco Pereira, Xuerui Wang, Marcel Adam Just, Sharlene D. Newman

Marcel Adam Just

No abstract provided.

Cortical Activation And Synchronization During Sentence Comprehension In High-Functioning Autism: Evidence Of Underconnectivity, Marcel Adam Just, Vladimir L. Cherkassky, Timothy A. Keller, Nancy J. Minshew

Marcel Adam Just

No abstract provided.

Pyro: A Python-Based Versatile Programming Environment For Teaching Robotics, D. Blank, D. Kumar, Lisa A. Meeden, H. Yanco

Computer Science Faculty Works

In this article we describe a programming framework called Pyro, which provides a set of abstractions that allows students to write platform-independent robot programs. This project is unique because of its focus on the pedagogical implications of teaching mobile robotics via a top-down approach. We describe the background of the project, its novel abstractions, its library of objects, and the many learning modules that have been created from which curricula for different types of courses can be drawn. Finally, we explore Pyro from the students' perspective in a case study.

Predicting Nonlinear Network Traffic Using Fuzzy Neural Network, Zhaoxia Wang, Tingzhu Hao, Zengqiang Chen, Zhuzhi Yuan

Research Collection School Of Computing and Information Systems

Network traffic is a complex and nonlinear process, which is significantly affected by immeasurable parameters and variables. This paper addresses the use of the five-layer fuzzy neural network (FNN) for predicting the nonlinear network traffic. The structure of this system is introduced in detail. Through training the FNN using back-propagation algorithm with inertia] terms the traffic series can be well predicted by this FNN system. We analyze the performance of the FNN in terms of prediction ability as compared with solely neural network. The simulation demonstrates that the proposed FNN is superior to the solely neural network systems. In addition, …

Task Allocation Via Multi-Agent Coalition Formation: Taxonomy, Algorithms And Complexity, Hoong Chuin Lau, L. Zhang

Research Collection School Of Computing and Information Systems

Coalition formation has become a key topic in multiagent research. In this paper, we propose a preliminary classification for the coalition formation problem based on three driving factors (demands, resources and profit objectives). We divide our analysis into 5 cases. For each case, we present algorithms and complexity results. We anticipate that with future research, this classification can be extended in similar fashion to the comprehensive classification for the job scheduling problem.

Safe Robot Driving In Cluttered Environments, Chuck Thorpe, Justin Carlson, Dave Duggins, Jay Gowdy, Rob Maclachlan, Christoph Mertz, Arne Suppe, Bob Wang

Research Collection School Of Computing and Information Systems

The Navlab group at Carnegie Mellon University has a long history of development of automated vehicles and intelligent systems for driver assistance. The earlier work of the group concentrated on road following, cross-country driving, and obstacle detection. The new focus is on short-range sensing, to look all around the vehicle for safe driving. The current system uses video sensing, laser rangefinders, a novel light-stripe rangefinder, software to process each sensor individually, and a map-based fusion system. The complete system has been demonstrated on the Navlab 11 vehicle for monitoring the environment of a vehicle driving through a cluttered urban environment, …

Multi-Agent Coalition Via Autonomous Price Negotiation In A Real-Time Web Environment, Hoong Chuin Lau, Wei Sian Lim

Research Collection School Of Computing and Information Systems

In e-marketplaces, customers specify job requests in real-time and agents form coalitions to service them. This paper proposes a protocol for self-interested agents to negotiate prices in forming successful coalitions. We propose and experiment with two negotiation schemes: one allows information sharing while the other does not.

A Computer-Based Articulation Training Aid For Short Words (Cata), Mukund Devarajan

Electrical & Computer Engineering Theses & Dissertations

Several improvements in the vowel articulation training aid (VATA) are described, as well as the efforts to extend the visual feedback system to operate with short words in the form of consonant, vowel and consonant (CVC). The extended version of the visual feedback system is referred to as CATA (Computer-based Articulation Training Aid); the vowel version of the aid (VATA) only operates with ten American English monopthong vowels. Improvements in VATA include the use of a neural network (NN) recognizer method to prune a large database of vowel recordings to eliminate noisy and/or mispronounced tokens. The spectral jitter problem, previously …

Solving Multi-Objective Multi-Constrained Optimization Problems Using Hybrid Ants System And Tabu Search, Hoong Chuin Lau, Min Kwang Lim, Wee Chong Wan, Hui Wang, Xiaotao Wu

Research Collection School Of Computing and Information Systems

Many real-world optimization problems today are multi-objective multi-constraint generalizations of NP-hard problems. A classic case we study in this paper is the Inventory Routing Problem with Time Windows (IRPTW). IRPTW considers inventory costs across multiple instances of Vehicle Routing Problem with Time Windows (VRPTW). The latter is in turn extended with time-windows constraints from the Vehicle Routing Problem (VRP), which is extended with optimal fleet size objective from the single-objective Traveling Salesman Problem (TSP). While single-objective problems like TSP are solved effectively using meta-heuristics, it is not obvious how to cope with the increasing complexity systematically as the problem is …

A Generic Object-Oriented Tabu Search Framework, Hoong Chuin Lau, Wee Chong Wan, Xiaomin Jia

Research Collection School Of Computing and Information Systems

Presently, most tabu search designers devise their applications without considering the potential of design and code reuse, which consequently prolong the development of subsequent applications. In this paper, we propose a software solution known as Tabu Search Framework (TSF), which is a generic C++ software framework for tabu search implementation. The framework excels in code recycling through the use of a welldesigned set of generic abstract classes that clearly define their collaborative roles in the algorithm. Additionally, the framework incorporates a centralized process and control mechanism that enhances the search with intelligence. This results in a generic framework that is …

A Generic Object-Oriented Tabu Search Framework, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Presently, most tabu search designers devise their applications without considering the potential of design and code reuse, which consequently prolong the development of subsequent applications. In this paper, we propose a software solution known as Tabu Search Framework (TSF), which is a generic C++ software framework for tabu search implementation. The framework excels in code recycling through the use of a welldesigned set of generic abstract classes that clearly define their collaborative roles in the algorithm. Additionally, the framework incorporates a centralized process and control mechanism that enhances the search with intelligence. This results in a generic framework that is …

On Machine Learning Methods For Chinese Document Classification, Ji He, Ah-Hwee Tan, Chew-Lim Tan

Research Collection School Of Computing and Information Systems

This paper reports our comparative evaluation of three machine learning methods, namely k Nearest Neighbor (kNN), Support Vector Machines (SVM), and Adaptive Resonance Associative Map (ARAM) for Chinese document categorization. Based on two Chinese corpora, a series of controlled experiments evaluated their learning capabilities and efficiency in mining text classification knowledge. Benchmark experiments showed that their predictive performance were roughly comparable, especially on clean and well organized data sets. While kNN and ARAM yield better performances than SVM on small and clean data sets, SVM and ARAM significantly outperformed kNN on noisy data. Comparing efficiency, kNN was notably more costly …

Machine Learning Approaches For Determining Effective Seeds For K -Means Algorithm, Kaveephong Lertwachara

Doctoral Dissertations

In this study, I investigate and conduct an experiment on two-stage clustering procedures, hybrid models in simulated environments where conditions such as collinearity problems and cluster structures are controlled, and in real-life problems where conditions are not controlled. The first hybrid model (NK) is an integration between a neural network (NN) and the k-means algorithm (KM) where NN screens seeds and passes them to KM. The second hybrid (GK) uses a genetic algorithm (GA) instead of the neural network. Both NN and GA used in this study are in their simplest-possible forms.

In the simulated data sets, I investigate two …