Learning to play Pac-Man: An evolutionary, rule-based approach

Pac-Man is a well-known, real-time computer game that provides an interesting platform for research. We describe an initial approach to developing an artificial agent that replaces the human to play a simplified version of Pac-Man. The agent is specified as a simple finite state machine and ruleset. with parameters that control the probability of movement by the agent given the constraints of the maze at some instant of time. In contrast to previous approaches, the agent represents a dynamic strategy for playing Pac-Man, rather than a pre-programmed maze-solving method. The agent adaptively "learns" through the application of population-based incremental learning (PBIL) to adjust the agents' parameters. Experimental results are presented that give insight into some of the complexities of the game, as well as highlighting the limitations and difficulties of the representation of the agent.

Visual data mining: integrating machine learning with information visualization

Today, the data available to tackle many scientific challenges is vast in quantity and diverse in nature. The exploration of heterogeneous information spaces requires suitable mining algorithms as well as effective visual interfaces. Most existing systems concentrate either on mining algorithms or on visualization techniques. Though visual methods developed in information visualization have been helpful, for improved understanding of a complex large high-dimensional dataset, there is a need for an effective projection of such a dataset onto a lower-dimension (2D or 3D) manifold. This paper introduces a flexible visual data mining framework which combines advanced projection algorithms developed in the machine learning domain and visual techniques developed in the information visualization domain. The framework follows Shneiderman’s mantra to provide an effective user interface. The advantage of such an interface is that the user is directly involved in the data mining process. We integrate principled projection methods, such as Generative Topographic Mapping (GTM) and Hierarchical GTM (HGTM), with powerful visual techniques, such as magnification factors, directional curvatures, parallel coordinates, billboarding, and user interaction facilities, to provide an integrated visual data mining framework. Results on a real life high-dimensional dataset from the chemoinformatics domain are also reported and discussed. Projection results of GTM are analytically compared with the projection results from other traditional projection methods, and it is also shown that the HGTM algorithm provides additional value for large datasets. The computational complexity of these algorithms is discussed to demonstrate their suitability for the visual data mining framework.

Accessing networked services : a user interface design problem

This research investigates the general user interface problems in using networked services. Some of the problems are: users have to recall machine names and procedures to. invoke networked services; interactions with some of the services are by means of menu-based interfaces which are quite cumbersome to use; inconsistencies exist between the interfaces for different services because they were developed independently. These problems have to be removed so that users can use the services effectively. A prototype system has been developed to help users interact with networked services. This consists of software which gives the user an easy and consistent interface with the various services. The prototype is based on a graphical user interface and it includes the following appJications: Bath Information & Data Services; electronic mail; file editor. The prototype incorporates an online help facility to assist users using the system. The prototype can be divided into two parts: the user interface part that manages interactlon with the user; the communicatIon part that enables the communication with networked services to take place. The implementation is carried out using an object-oriented approach where both the user interface part and communication part are objects. The essential characteristics of object-orientation, - abstraction, encapsulation, inheritance and polymorphism - can all contribute to the better design and implementation of the prototype. The Smalltalk Model-View-Controller (MVC) methodology has been the framework for the construction of the prototype user interface. The purpose of the development was to study the effectiveness of users interaction to networked services. Having completed the prototype, tests users were requested to use the system to evaluate its effectiveness. The evaluation of the prototype is based on observation, i.e. observing the way users use the system and the opinion rating given by the users. Recommendations to improve further the prototype are given based on the results of the evaluation. based on the results of the evah:1ation. . .'. " "', ':::' ,n,<~;'.'

Some aspects of the dynamic performance of machine tool structural joints

The work presented in this thesis is concerned with the dynamic behaviour of structural joints which are both loaded, and excited, normal to the joint interface. Since the forces on joints are transmitted through their interface, the surface texture of joints was carefully examined. A computerised surface measuring system was developed and computer programs were written. Surface flatness was functionally defined, measured and quantised into a form suitable for the theoretical calculation of the joint stiffness. Dynamic stiffness and damping were measured at various preloads for a range of joints with different surface textures. Dry clean and lubricated joints were tested and the results indicated an increase in damping for the lubricated joints of between 30 to 100 times. A theoretical model for the computation of the stiffness of dry clean joints was built. The model is based on the theory that the elastic recovery of joints is due to the recovery of the material behind the loaded asperities. It takes into account, in a quantitative manner, the flatness deviations present on the surfaces of the joint. The theoretical results were found to be in good agreement with those measured experimentally. It was also found that theoretical assessment of the joint stiffness could be carried out using a different model based on the recovery of loaded asperities into a spherical form. Stepwise procedures are given in order to design a joint having a particular stiffness. A theoretical model for the loss factor of dry clean joints was built. The theoretical results are in reasonable agreement with those experimentally measured. The theoretical models for the stiffness and loss factor were employed to evaluate the second natural frequency of the test rig. The results are in good agreement with the experimentally measured natural frequencies.

Experience with Rule Induction & k-Nearest Neighbour Methods for Interface Agents that Learn

Peer reviewed

Ghost Machine: a Sound Performance

Ghost Machine is an encounter between a person and a machine in a suburban shed. The machine reveals the story of a man haunted by an image that seems to shift and change as it sits on the wall of his study. In an attempt to locate the origins of the image he builds a viewing machine to finally confront it. Ghost Machine is based on The Mezzotint (1904) by M.R James, retold as a suburban ghost story. It was part of SENSE at Mayfest in Bristol between 24th - 26th May 2013.

Interface de app para dispositivos móveis de universidade virtual, caso da UAb

O avanço das tecnologias de informação continua a mudar os paradigmas de ensino e aprendizagem. Os meios disponíveis são cada vez mais diversificados e, com a necessidade de procurar novos estudantes e diversificar o público-alvo, as instituições de ensino superior estão a repensar os seus modelos de negócio e estratégias pedagógicas. A proliferação de dispositivos móveis catalisa uma aposta crescente no ensino a distância (EaD) no sentido de proporcionar aprendizagens em mobilidade (m-learning). No entanto, as soluções existentes para m-learning são ainda pouco adaptadas às recentes metodologias de EaD, na maioria das vezes funcionando como extensão de um ambiente virtual de aprendizagem ou com muito foco nos conteúdos. Sendo a Universidade Aberta (UAb) a única instituição de ensino superior público em Portugal de ensino a distância, com um modelo pedagógico próprio, constitui um natural caso de aplicação de tecnologia móvel em novos contextos de aprendizagem, importando por isso estudar e desenhar os mecanismos de interação mais adequados com professores e estudantes em mobilidade. Adotou-se neste trabalho a metodologia Design Science Research, tendo sido identificadas as características e comportamentos de potenciais utilizadores, e definidas as funcionalidades que devem ser disponibilizadas na primeira versão de uma aplicação para dispositivos móveis (app) no contexto do ensino a distância. É proposto o design da interface dessa app, usando o modelo da UAb como caso de aplicação, e disponibilizada uma lista de orientações para o desenvolvimento do protótipo funcional. Da investigação realizada, concluiu-se que a interface proposta constitui um modelo válido para o desenho de uma app para aprendizagens em mobilidade, no regime de ensino de uma universidade virtual. A partir deste modelo, as instituições de ensino superior podem desenvolver apps adaptando-se ao avanço das Tecnologias de Informação e Comunicação e ficarem alinhadas com as necessidades dos seus alunos e docentes, particularmente se dispuserem de oferta formativa a distância.

Real time cyber attack analysis on Hadoop ecosystem using machine learning algorithms

Big Data technologies are exciting cutting-edge technologies that generate, collect, store and analyse tremendous amount of data. Like any other IT revolution, Big Data technologies also have big challenges that are obstructing it to be adopted by wider community or perhaps impeding to extract value from Big Data with pace and accuracy it is promising. In this paper we first offer an alternative view of «Big Data Cloud» with the main aim to make this complex technology easy to understand for new researchers and identify gaps efficiently. In our lab experiment, we have successfully implemented cyber-attacks on Apache Hadoop's management interface «Ambari». On our thought about «attackers only need one way in», we have attacked the Apache Hadoop's management interface, successfully turned down all communication between Ambari and Hadoop's ecosystem and collected performance data from Ambari Virtual Machine (VM) and Big Data Cloud hypervisor. We have also detected these cyber-attacks with 94.0187% accurateness using modern machine learning algorithms. From the existing researchs, no one has ever attempted similar experimentation in detection of cyber-attacks on Hadoop using performance data.

Predicting the concentration of residual methanol in industrial formalin using machine learning

In this thesis, a machine learning approach was used to develop a predictive model for residual methanol concentration in industrial formalin produced at the Akzo Nobel factory in Kristinehamn, Sweden. The MATLABTM computational environment supplemented with the Statistics and Machine LearningTM toolbox from the MathWorks were used to test various machine learning algorithms on the formalin production data from Akzo Nobel. As a result, the Gaussian Process Regression algorithm was found to provide the best results and was used to create the predictive model. The model was compiled to a stand-alone application with a graphical user interface using the MATLAB CompilerTM.