Adaptive user modelling in intelligent telephone and email assistants

With the burgeoning complexity and capabilities of modern information appliances and services, user modelling is becoming an increasingly important research area. Simple user profiles already personalise many software products and consumer goods such as digital TV recorders and mobile phones. A user model should be easy to initialise, and it must adapt in the light of interaction with the user. In many cases, a large amount of training data is needed to generate a user model, and adaptation is equivalent to retraining the system. This paper briefly outlines the user modelling problem and work done at BTexact on an intelligent personal assistant (IPA) which incorporates a user profile. We go on to describe FILUM, a more flexible method of user modelling, and show its application to the telephone assistant and email assistant components of the IPA, with tests to illustrate its usefulness.     

An evolutionary tuned driving system for virtual car racing games: The AUTOPIA driver

This work presents a driving system designed for virtual racing situations. It is based on a complete modular architecture capable of automatically driving a car along a track with or without opponents. The architecture is composed of intuitive modules, with each one being responsible for a basic aspect of car driving. Moreover, this modularity of the architecture will allow us to replace or add modules in the future as a way to enhance particular features of particular situations. In the present work, some of the modules are implemented by means of hand‐designed driving heuristics, whereas modules responsible for adapting the speed and direction of the vehicle to the track's shape, both critical aspects of driving a vehicle, are optimized by means of a genetic algorithm that evaluates the performance of the controller in four different tracks to obtain the best controller in a large number of situations; the algorithm also penalizes controllers that go out of the track, lose control, or get damaged. The evaluation of the performance is done in two ways. First, in runs with and without adversaries over several tracks. And second, the architecture was submitted as a participant to the 2010 Simulated Car Racing Competition, which in end won laurels. © 2012 Wiley Periodicals, Inc.     

Are you a human or a humanoid: Predictive user modelling through behavioural analysis of online gameplay data

Intelligent agents are widely used in robotics, gaming and simulation. A key issue is modelling human behaviours so that intelligent agents can use a human’s behavioural model to imitate them and predict their next moves. In this article, we use Internet-based multiplayer online gaming (MOG) as a case study to present our approach to predictive user modelling through behavioural analysis of online gameplay data. As latency is an inherited bottleneck of the Internet and is likely to remain so into a foreseeable future, a lot of efforts have been made to address the resulting issues. Most of the existing latency handling techniques are based on the assumption that latency is within an acceptable threshold so that they can alleviate or even completely hide its negative impact on players’ quality of experience (QoE) that directly determines consumers’ satisfaction of the provided MOG services. While this assumption is mostly valid, it is worth noting that a player’s Internet connection latency always fluctuates (known as jitter), possibly to the extent of exceeding a MOG’s designated threshold in which case none of the techniques can handle properly but disconnecting the player from the gameplay session. Forcing a player to quit prematurely simply due to a spike of unusual high latency has a significant negative impact both on the gameplay’s fairness and on the player’s QoE. To improve customer satisfaction of a MOG service, we propose a more tolerant approach by temporarily substituting a player with a humanoid bot in the event of latency hikes so that the player always remains in the gameplay session. The challenge in this approach is to create a personalised humanoid bot that can imitate the playing pattern of the individual human player being substituted. Our solution is to first extract key variables that have impact on the human player’s decision-makings through behavioural analysis of the player’s historical gameplay data, then model the relationships among these variables, and finally creates the player’s humanoid bot with the model. In this paper, we use a multiplayer online pong game as a case study to explain behavioural variables, modelling techniques, processes, outcomes, and performance studies.     

Advanced overtaking behaviors for blocking opponents in racing games using a fuzzy architecture

In car racing, blocking refers to maneuvers that can prevent, disturb or completely block an overtaking action by an incoming car. In this paper, we present an advanced overtaking behavior that is able to deal with opponents implementing blocking strategies of various difficulty level. The behavior we developed has been integrated in an existing fuzzy-based architecture for driving simulated cars and tested using The Open Car Racing Simulator (TORCS). We compared a driver implementing our overtaking strategy against four of the bots available in the TORCS distribution and Simplix, a state-of-the-art driver which won several competitions. The comparison was carried out against opponents implementing three blocking strategies of increasing difficulty and two different scenarios: (i) a basic scenario with one opponent on a straight stretch to overtake as quickly as possible; (ii) an advanced scenario involving a race on a non-trivial track against several opponents. The results from the basic scenario show that our strategy can always overtake the opponent car; in particular, our strategy is slightly more risky than the other ones and may result in a little damage, however, all the other controllers show a more careful and safe policy that often prevents them to complete an overtaking maneuver. When racing against several opponents on complex tracks, our strategy results in the best trade-off between the time spent being blocked by an opponent ahead and the number of overtaking maneuvers completed.     

A demonstration of pharmacokinetics and physiological modelling using a microcomputer for data capture and analysis

We describe a simple and inexpensive demonstration of mass transport and exchange using dye clearance from a hydrodynamic model. A microcomputer was used for data acquisition and storage, non-linear least squares curve fitting, compartmental analysis and parameter estimation. The system is useful for demonstrating the indicator-dilution technique for fluid volume measurement and compartmental analysis in pharmacokinetics.     

FSAE赛车车架的强度和刚度分析

为保证吉林大学SAE方程式(Formula SAE,FSAE)赛车能够安全参赛,介绍其车架设计方案,利用MSC Patran建立车架的有限元模型,得出该车架在多种工况下的强度值以及扭转和弯曲刚度值;将分析所得数据与已知数据进行对比,证明该方案满足设计要求,为FSAE赛车的安全参赛提供理论保证.     

Effective affective user interface design in games

It is proposed that games, which are designed to generate positive affect, are most successful when they facilitate flow (Csikszentmihalyi 1992). Flow is a state of concentration, deep enjoyment, and total absorption in an activity. The study of games, and a resulting understanding of flow in games can inform the design of non-leisure software for positive affect. The paper considers the ways in which computer games contravene Nielsen's guidelines for heuristic evaluation (Nielsen and Molich 1990) and how these contraventions impact on flow. The paper also explores the implications for research that stem from the differences between games played on a personal computer and games played on a dedicated console. This research takes important initial steps towards defining how flow in computer games can inform affective design.     

Effective affective user interface design in games

It is proposed that games, which are designed to generate positive affect, are most successful when they facilitate flow (Csikszentmihalyi 1992). Flow is a state of concentration, deep enjoyment, and total absorption in an activity. The study of games, and a resulting understanding of flow in games can inform the design of non-leisure software for positive affect. The paper considers the ways in which computer games contravene Nielsen's guidelines for heuristic evaluation (Nielsen and Molich 1990) and how these contraventions impact on flow. The paper also explores the implications for research that stem from the differences between games played on a personal computer and games played on a dedicated console. This research takes important initial steps towards defining how flow in computer games can inform affective design.     

Adaptation and user expertise modelling in AthosMail

This article describes the User Model component of AthosMail, a speech-based interactive e-mail application developed in the context of the EU project DUMAS. The focus is on the system’s adaptive capabilities and user expertise modelling, exemplified through the User Model parameters dealing with initiative and explicitness of the system responses. The purpose of the conducted research was to investigate how the users could interact with a system in a more natural way, and the two aspects that mainly influence the system’s interaction capabilities, and thus the naturalness of the dialogue as a whole, are considered to be the dialogue control and the amount of information provided to the user. The User Model produces recommendations of the system’s appropriate reaction depending on the user’s observed competence level, monitored and computed on the basis of the user’s interaction with the system. The article also discusses methods for the evaluation of adaptive user models and presents results from the AthosMail evaluation.The research was done while the author was affiliated with the University of Art and Design Helsinki as the scientific coordinator of the DUMAS project.     

Semantic data modelling and visualisation using Noetica

Noetica is a tool for structuring knowledge about concepts and the relationships between them. It differs from typical information systems in that the knowledge it represents is abstract, highly connected, and includes meta-knowledge (knowledge about knowledge). Noetica represents knowledge using a strongly typed graph data model. By providing a rich type system it is possible to represent conceptual information using formalised structures. A class hierarchy provides a basic classification for all objects. This allows for a consistency of representation that is not often found in “free” semantic networks, and gives the ability to easily extend a knowledge model while retaining its semantics.

Visualisation and query tools are provided for this data model. Visualisation can be used to explore complete sets of link-classes, show paths while navigating through the database, or visualise the results of queries. Noetica supports goal-directed queries (a series of user-supplied goals that the system attempts to satisfy in sequence) and pathfinding queries (where the system finds relationships between objects in the database by following links).     

Nonparametric user activity modelling and prediction

User Modeling and User-Adapted Interaction - Modelling the occupancy of buildings, rooms or the usage of machines has many applications in varying fields, exemplified by the fairly recent emergence...     

Playability: analysing user experience in video games

Currently, few studies focus on analysing the degree of the Player eXperience (PX) in video games. Video games have now become interactive entertainment systems with a high economic impact on society; these are interactive systems characterised by their subjectivity, which differ from other systems in that their main objective is to entertain and amuse the user (player). This work discusses the analysis and evaluation of the User eXperience (UX) in interactive entertainment systems, exploring how usability, given its definition, objectives and the fact it is one of the main dimensions of UX, is not sufficient to characterise the PX, giving rise to a new concept: Playability. In this paper, we present a framework for the analysis and evaluation of the UX in video games. The results show the need and importance of a framework to help us understand and measure the experience that players feel using these types of interactive systems, in order to improve the experience during play time. The proposed framework characterises the experience using attributes to identify and properties to measure UX. It thus provides a multifaceted analysis mechanism to assess the impact of the gaming experience and its relationship with the elements of a video game. We therefore present a system to represent UX based on this framework, with the aim of ensuring and measuring a satisfactory experience of the entertainment system. Finally, we discuss a practical experiment in which an evaluation of the playability of a commercial video game was carried out using the methods proposed in this work.     

Analysing user trust in electronic banking using data mining methods

The potential fraud problems, international economic crisis and the crisis of trust in markets have affected financial institutions, which have tried to maintain customer trust in many different ways. To maintain these levels of trust they have been forced to make significant adjustments to economic structures, in efforts to recoup their investments and maintain the loyalty of their customers. To achieve these objectives, the implementation of electronic banking for customers has been considered a successful strategy. The use of electronic banking in Spain in the last decade has been fostered due to its many advantages, giving rise to real integration of channels in financial institutions. This paper reviews different methods and techniques to determine which variables could be the most important to financial institutions in order to predict the likely levels of trust among electronic banking users including socio-demographic, economic, financial and behavioural strategic variables that entities have in their databases. To do so, the most recent advances in machine learning and soft-computing have been used, including a new selection operator for multiobjective genetic algorithms. The results obtained by the algorithms were validated by an expert committee, ranking the quality of them. The new methodology proposed, obtained the best results in terms of optimisation as well as the highest punctuation given by the experts.     

A fuzzy-rule-based driving architecture for non-player characters in a car racing game

Videogame-based competitions have been the target of considerable interest among researchers over the past few years since they provide an ideal framework in which to apply soft computing techniques. One of the most popular competitions is the Simulated Car Racing Competition which, thanks to the realism implemented by recent car simulators, provides an excellent test bed for the application of autonomous driving techniques. The present work describes the design and implementation of a car controller able to deal with competitive racing situations. The complete driving architecture consists of six simple modules, each one responsible for a basic aspect of car driving. Three modules use simple functions to control gear shifting, steering movements, and pedal positions. A fourth manages speed control by means of a simple fuzzy system. The other two modules are in charge of (i) adapting the driving behaviour to the presence of other cars, and (ii) implementing a basic ‘inter-lap’ learning mechanism in order to remember key track segments and adapt the speed accordingly in future laps. The controller was evaluated in two ways. First, in runs without adversaries over several track designs, our controller allowed some of the longest distances to be covered in a set time in comparison with data from other previous controllers, and second, as a participant in the 2009 Simulated Car Racing Competition which it ended up winning.     

Adaptive learning and emergent coordination in minority games

This work studies the properties of a coordination game in which agents repeatedly compete to be in the population minority. The game reflects some essential features of those economic situations in which positive rewards are assigned to individuals who behave in opposition to the modal behavior in a population. In this work we model a large group of agents who repeatedly interact in the game and we investigate the extent to which the system medium and long-run efficiency properties depend upon the specification of the agents’ microbehaviors in terms of their degree of rationality, the amount of information they use in making their choices, their learning patterns and the level of heterogeneity in the population. Our results show that, first, the system long-run properties strongly depend on the particular behavioral assumptions adopted, and, second, adding noise at the individual decision level and hence increasing heterogeneity in the population substantially improve aggregate welfare, although at the expense of a longer adjustment phase. In fact, the system achieves in that way a higher level of efficiency compared to that attainable by perfectly rational and completely informed agents.     

Simultaneous scheduling of football games and referees using Turkish league data

Assignment decisions of referees to football (soccer) games are highly debated in sports media. Referee assignments are typically done on a weekly basis as the league progresses. However, this practice ignores important workload constraints on referees. Moreover, referees' skill levels should also be considered in determining their assignments. In this article, we first give a mixed integer linear program formulation for the problem of simultaneously generating a game schedule and assigning main referees to games by incorporating specific rules in the Turkish league. We also approach this problem using a genetic algorithm (GA) because of the computational difficulties in solving the problem. In the GA solution pool, we suggest using templates for referee assignments that follow several referee‐related workload constraints. We explain how these templates can be obtained by solving a mixed integer linear model prior to running the GA. The usage of these templates for referee assignments is conceptually similar to using a basic match schedule for game scheduling such as the one used in the Turkish Football League. We use the Turkish Football League fixtures for 2010–2013 as a case study. Experiments with the GA using real‐world data show a rather modest performance in terms of computation time and objective function value. Our numerical results indicate that the problem is extremely hard to solve.     

Keyword-guided word spotting in historical printed documents using synthetic data and user feedback

In this paper, we propose a novel technique for word spotting in historical printed documents combining synthetic data and user feedback. Our aim is to search for keywords typed by the user in a large collection of digitized printed historical documents. The proposed method consists of the following stages: (1) creation of synthetic image words; (2) word segmentation using dynamic parameters; (3) efficient feature extraction for each word image and (4) a retrieval procedure that is optimized by user feedback. Experimental results prove the efficiency of the proposed approach.     

Solid modelling using a volume encoding data structure

A strong emphasis has lately been put in research to develop methods for Solid Modelling using surface or volume encoding data structures instead of conventional edge-face-vertex or polyhedral representations for 3-D objects.This article describes a Solid Modelling system using a volume encoding data structure called OCTREE which divides a solid into cubes.     

Adaptive image data hiding using transformation and error replacement

Watermarking is popular method for effective copyright protection of digital data. The invisible image watermarking is a type of watermarking which is used to conceal secret information in a cover image. In any watermarking system, there is a trade-off between imperceptibility and payload of the data to be hidden in the cover medium. Therefore, only a limited amount of data can be concealed in the cover image while watermark remain imperceptible. This paper proposes a new method of adaptive blind digital image data hiding in Discrete Cosine Transform (DCT) domain using Minimum Error Lease Significant Bit Replacement (MELSBR) method and Genetic Algorithm (GA). In the proposed method, the secret image is embedded into the DCT transformed cover image. Initially, the host and the secret image both are partitioned into equal sized blocks. Then for each secret image block, host image block is intelligently selected through GA and is embedded using MELSBR method. GA helps in identifying the target cover image blocks such that with the LSB embedding, both visual quality of the cover image and imperceptibility of the secret image remain least affected. In watermark extraction process, the watermarked image is decomposed into equal sized blocks and then using the Jigsaw Puzzle Solver (JPS) the secret image is reconstructed. In spite of doubling the payload of the data to hide, the experimental results have shown better imperceptibility and robustness results of the proposed method as compared to the current approaches in this domain.