Integration of psychological models in the design of artificial creatures

Artificial creatures form an increasingly important component of interactive computer games. Examples of such creatures exist which can interact with each other and the game player and learn from their experiences. However, we argue, the design of the underlying architecture and algorithms has to a large extent overlooked knowledge from psychology and cognitive sciences. We explore the integration of observations from studies of motivational systems and emotional behaviour into the design of artificial creatures. An initial implementation of our ideas using the “sim agent” toolkit illustrates that physiological models can be used as the basis for creatures with animal like behaviour attributes. The current aim of this research is to increase the “realism” of artificial creatures in interactive game-play, but it may have wider implications for the development of AI

Development of a microcomputer based design system for air management of buildings

Expert systems are computer programs that seek to mimic human reasoning. Currently, expert systems are being used for the design of heating, ventilation, and air conditioning (HVAC) systems. The present work involves developing of several smaller expert systems known as knowledge bases, and integrating them in one simple package. The aim of the research is to develop a such computer code for HVAC system designers which will considerably reduce man-hours during the whole design process, improve the productivity, increase the design quality, and give the customers more options to choose the best and optimum design. This thesis describes the development of a computer code, which has the ability to give all the design requirements for HVAC systems. This work which can be considered as a step towards HVAC Expert Systems, which outlines step by step calculation procedure to determine essential elements of heating and cooling loads such as U-value, air infiltration, solar heat gain, heat storage, psychrometric charts and the sunlit area of the exterior surfaces. The code (HVACSYS) consists of a main menu program and several auxiliary programs for gathering data, completing calculations, and printing project reports. The developed code is also connected with the AutoCAD package to give the final design of the HVAC systems. In the AutoCAD package, a special menu for HVAC systems design has been added (HVACCAD). This menu is developed for customizing the AutoCAD package in order to make the code interactive. Finally, a case study has been considered in which solutions were obtained using an existing package and also the developed package. Comparison of the solutions illustrates the usefulness of the new package adequately

Preliminary Design of Tall Buildings

Techniques for preliminary analysis of various tall building systems subjected to lateral loads have been studied herein. Three computer programs written in Matlab® graphical user interface language for use on any personal computer are presented. Two of these programs incorporate interactive graphics. A program called Wall_Frame_2D is introduced for two-dimensional analysis of shear wall-frame interactive structures, using the shear-flexural cantilever analogy. The rigid outrigger approach was utilized to develop a program called Outrigger Program to analyze multi-outrigger braced tall buildings. In addition, a program called Frame Tube was developed which allows analysis of single and quad-bundled framed tube structures. The tube grids are replaced with an equivalent orthotropic plate, and the governing differential equations are solved in closed form. Results for lateral deflections, rotations, and moment, shear, and torque distributions within the various resisting elements are compared against other preliminary and exact matrix analysis methods for several examples. SAP2000 was used to obtain exact results. The approximate analyses are found to give reasonable results and a fairly good indication of the behavior of the actual structure. These programs are proposed for inclusion in a knowledge-based approach to preliminary tall building design. The tall building design process is outlined and criteria are given for the incorporation of these Resource Level Knowledge Modules into an integrated tall building design system

Title IX in the Classroom: Academic Freedom and the Power to Harass

I alla designprocesser måste man ta hänsyn till ett mediums egenskaper. Detta är inget nytt inom design. Ändå förekommer det ofta inom människa --‐ dator interaction (HCI) och interaktiv systemdesign att teknikens egenskaper bara ses över som hastigast. Tekniken är ofta abstraherad, utan att tillräcklig uppmärksamhet ges till hur deras distinkta egenskaper öppnar upp för designmöjligheter. I den här rapporten beskrivs ett tillvägagångssätt som kallas Inspirational Bits för att bli mer bekant med designmaterialet inom HCI, det digitala materialet. Det är också ett sätt för att bli bättre på att förmedla kunskapen till alla gruppmedlemmar i ett interdisciplinärt designteam. Inspirational Bits skapas ”snabbt och smutsigt” men är fullt fungerande system i både hard--‐ och mjukvara, med målet att blotta en eller flera av de dynamiska egenskaperna hos digitala material.In any design process, a medium’s properties need to be considered. This is nothing new in design. Still it is found that in Human--‐Computer Interaction (HCI) and interactive systems design the properties of a technology are often glossed over. That is, technologies are black--‐boxed without much thought given to how their distinctive properties open up design possibilities. This thesis describes an approach using Inspirational Bits to become more familiar with the design material in HCI, the digital material. It is also a way to become better able to share some of this knowledge with all members of an interdisciplinary design team. Inspirational Bits are quick and dirty but fully working systems in both hardware and software with the single aim of exposing one or several of the dynamic properties of some of the digital materials

Facilitating teacher participation in intelligent computer tutor design : tools and design methods.

This work addresses the widening gap between research in intelligent tutoring systems (ITSs) and practical use of this technology by the educational community. In order to ensure that ITSs are effective, teachers must be involved in their design and evaluation. We have followed a user participatory design process to build a set of ITS knowledge acquisition tools that facilitate rapid prototyping and testing of curriculum, and are tailored for usability by teachers. The system (called KAFITS) also serves as a test-bed for experimentation with multiple tutoring strategies. The design includes novel methodologies for tutoring strategy representation (Parameterized Action Networks) and overlay student modeling (a layered student model), and incorporates considerations from instructional design theory. It also allows for considerable student control over the content and style of the information presented. Highly interactive graphics-based tools were built to facilitate design, inspection, and modification of curriculum and tutoring strategies, and to monitor the progress of the tutoring session. Evaluation of the system includes a sixteen-month case study of three educators (one being the domain expert) using the system to build a tutor for statics (forty topics representing about four hours of on-line instruction), testing the tutor on a dozen students, and using test results to iteratively improve the tutor. Detailed throughput analysis indicates that the amount of effort to build the statics tutor was, surprisingly, comparable to similar figures for building (non-intelligent) conventional computer aided instructional systems. Few ITS projects focus on educator participation and this work is the first to empirically study knowledge acquisition for ITSs. Results of the study also include: a recommended design process for building ITSs with educator participation; guidelines for training educators; recommendations for conducting knowledge acquisition sessions; and design tradeoffs for knowledge representation architectures and knowledge acquisition interfaces

On data-driven systems analyzing, supporting and enhancing users’ interaction and experience

[EN]The research areas of Human-Computer Interaction and Software Architectures have been traditionally treated separately, but in the literature, many authors made efforts to merge them to build better software systems. One of the common gaps between software engineering and usability is the lack of strategies to apply usability principles in the initial design of software architectures. Including these principles since the early phases of software design would help to avoid later architectural changes to include user experience requirements. The combination of both fields (software architectures and Human-Computer Interaction) would contribute to building better interactive software that should include the best from both the systems and user-centered designs. In that combination, the software architectures should enclose the fundamental structure and ideas of the system to offer the desired quality based on sound design decisions. Moreover, the information kept within a system is an opportunity to extract knowledge about the system itself, its components, the software included, the users or the interaction occurring inside. The knowledge gained from the information generated in a software environment can be used to improve the system itself, its software, the users’ experience, and the results. So, the combination of the areas of Knowledge Discovery and Human-Computer Interaction offers ideal conditions to address Human-Computer-Interaction-related challenges. The Human-Computer Interaction focuses on human intelligence, the Knowledge Discovery in computational intelligence, and the combination of both can raise the support of human intelligence with machine intelligence to discover new insights in a world crowded of data. This Ph.D. Thesis deals with these kinds of challenges: how approaches like data-driven software architectures (using Knowledge Discovery techniques) can help to improve the users' interaction and experience within an interactive system. Specifically, it deals with how to improve the human-computer interaction processes of different kind of stakeholders to improve different aspects such as the user experience or the easiness to accomplish a specific task. Several research actions and experiments support this investigation. These research actions included performing a systematic literature review and mapping of the literature that was aimed at finding how the software architectures in the literature have been used to support, analyze or enhance the human-computer interaction. Also, the actions included work on four different research scenarios that presented common challenges in the Human- Computer Interaction knowledge area. The case studies that fit into the scenarios selected were chosen based on the Human-Computer Interaction challenges they present, and on the authors’ accessibility to them. The four case studies were: an educational laboratory virtual world, a Massive Open Online Course and the social networks where the students discuss and learn, a system that includes very large web forms, and an environment where programmers develop code in the context of quantum computing. The development of the experiences involved the review of more than 2700 papers (only in the literature review phase), the analysis of the interaction of 6000 users in four different contexts or the analysis of 500,000 quantum computing programs. As outcomes from the experiences, some solutions are presented regarding the minimal software artifacts to include in software architectures, the behavior they should exhibit, the features desired in the extended software architecture, some analytic workflows and approaches to use, or the different kinds of feedback needed to reinforce the users’ interaction and experience. The results achieved led to the conclusion that, despite this is not a standard practice in the literature, the software environments should embrace Knowledge Discovery and datadriven principles to analyze and respond appropriately to the users’ needs and improve or support the interaction. To adopt Knowledge Discovery and data-driven principles, the software environments need to extend their software architectures to cover also the challenges related to Human-Computer Interaction. Finally, to tackle the current challenges related to the users’ interaction and experience and aiming to automate the software response to users’ actions, desires, and behaviors, the interactive systems should also include intelligent behaviors through embracing the Artificial Intelligence procedures and techniques

An experimental methodology for a fuzzy set preference model

A flexible fuzzy set preference model first requires approximate methodologies for implementation. Fuzzy sets must be defined for each individual consumer using computer software, requiring a minimum of time and expertise on the part of the consumer. The amount of information needed in defining sets must also be established. The model itself must adapt fully to the subject's choice of attributes (vague or precise), attribute levels, and importance weights. The resulting individual-level model should be fully adapted to each consumer. The methodologies needed to develop this model will be equally useful in a new generation of intelligent systems which interact with ordinary consumers, controlling electronic devices through fuzzy expert systems or making recommendations based on a variety of inputs. The power of personal computers and their acceptance by consumers has yet to be fully utilized to create interactive knowledge systems that fully adapt their function to the user. Understanding individual consumer preferences is critical to the design of new products and the estimation of demand (market share) for existing products, which in turn is an input to management systems concerned with production and distribution. The question of what to make, for whom to make it and how much to make requires an understanding of the customer's preferences and the trade-offs that exist between alternatives. Conjoint analysis is a widely used methodology which de-composes an overall preference for an object into a combination of preferences for its constituent parts (attributes such as taste and price), which are combined using an appropriate combination function. Preferences are often expressed using linguistic terms which cannot be represented in conjoint models. Current models are also not implemented an individual level, making it difficult to reach meaningful conclusions about the cause of an individual's behavior from an aggregate model. The combination of complex aggregate models and vague linguistic preferences has greatly limited the usefulness and predictive validity of existing preference models. A fuzzy set preference model that uses linguistic variables and a fully interactive implementation should be able to simultaneously address these issues and substantially improve the accuracy of demand estimates. The parallel implementation of crisp and fuzzy conjoint models using identical data not only validates the fuzzy set model but also provides an opportunity to assess the impact of fuzzy set definitions and individual attribute choices implemented in the interactive methodology developed in this research. The generalized experimental tools needed for conjoint models can also be applied to many other types of intelligent systems