A review on integration of artificial intelligence into water quality modelling

2005-2006 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

The effect of multiple knowledge sources on learning and teaching

Current paradigms for machine-based learning and teaching tend to perform their task in isolation from a rich context of existing knowledge. In contrast, the research project presented here takes the view that bringing multiple sources of knowledge to bear is of central importance to learning in complex domains. As a consequence teaching must both take advantage of and beware of interactions between new and existing knowledge. The central process which connects learning to its context is reasoning by analogy, a primary concern of this research. In teaching, the connection is provided by the explicit use of a learning model to reason about the choice of teaching actions. In this learning paradigm, new concepts are incrementally refined and integrated into a body of expertise, rather than being evaluated against a static notion of correctness. The domain chosen for this experimentation is that of learning to solve "algebra story problems." A model of acquiring problem solving skills in this domain is described, including: representational structures for background knowledge, a problem solving architecture, learning mechanisms, and the role of analogies in applying existing problem solving abilities to novel problems. Examples of learning are given for representative instances of algebra story problems. After relating our views to the psychological literature, we outline the design of a teaching system. Finally, we insist on the interdependence of learning and teaching and on the synergistic effects of conducting both research efforts in parallel

A review on the integration of artificial intelligence into coastal modeling

Author name used in this publication: Kwokwing Chau2005-2006 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

Modelling student errors in physics problem-solving

The motivation for this work has been the development of knowledge about the behaviour of human problem-solvers that would enable an intelligent machine tutor to be designed. In the domain of Newtonian Mechanics, this breaks down into two necessary sub-tasks; how do people decide what equation to generate; and what do they produce when they do try to generate an equation? Although these are psychologically separate questions, an automatic tutor for the domain would need to make use of both kinds of knowledge. Therefore, strategies for controlling search in physics problem-solving are investigated, and a computational model of erroneous solutions is described. Experimental data is used to evaluate the model. Errors in the domain are classified, and the behaviour of problem-solvers predicted under certain circumstances. Prediction of Novice errors is a crucial ability for an intelligent tutorial system, and the error analysis implemented in the NEWT program is the main contribution of this thesis. The investigation has two principal aims: (1) To develop a model that allows a student's future behaviour to be predicted from an analysis of his past actions. It is argued that this is a necessary prerequisite for the construction of an intelligent tutorial system. (2) To identify the psychological mechanisms used by problem-solvers working in the domain. The thesis attempts to achieve these aims in two main ways: (1) A computer program called NEWT has been constructed, which solves problems of Newtonian Mechanics correctly, or in one of a number of erroneous ways. This allows human errors to be matched, classified, and in some cases predicted. (2) An analysis of published data leads to the formulation of a control strategy termed "planstacking". This is compared to alternative control strategies, and shown to explain existing data more adequately. The program is evaluated both as a psychological theory, and as a proposed student model for use in a computer-based tutorial system. The NEWT program was developed from the MECHO program written by Bundy, Byrd, Luger, Mellish and Palmer (1979), at the Department of Artificial Intelligence, Edinburgh University. This program was adapted to produce erroneous problem solutions by the inclusion of procedures to implement malrules observed in the domain

identifying archaeological knowledge using multi dimensional scaling and multiple constraint satisfaction

In this thesis, I look at the current state of research in two fields: the cognitive psychology of learning and expertise & the development of Intelligent Tutoring Systems, especially their methods of modelling the users knowledge state. Within these areas I proceed to examine the way that these theories have overlapped in the past and consider their recent divergence, suggesting that this parting of the ways is premature. I then consider other relevent research so as to suggest a hypothesis where a symbolic connectionist approach to the modelling of knowledge states could be a solution to previous difficulties in the field of Intelligent Tutoring. This hypothesis is then used to construct a method for its examination and also a computer program to analyse the collected data. I then undertake experimental work to validate my hypothesis, and compare my results and methods with a pre-established technique for interpreting the data, that of multi-dimensional scaling. Finally the method now shown to be feasible is discussed to indicate the its success and highlight its shortcomings. Further suggestions are also made as to further research avenues

An Object-Oriented Programming Environment for Parallel Genetic Algorithms

This thesis investigates an object-oriented programming environment for building parallel applications based on genetic algorithms (GAs). It describes the design of the Genetic Algorithms Manipulation Environment (GAME), which focuses on three major software development requirements: flexibility, expandability and portability. Flexibility is provided by GAME through a set of libraries containing pre-defined and parameterised components such as genetic operators and algorithms. Expandability is offered by GAME'S object-oriented design. It allows applications, algorithms and genetic operators to be easily modified and adapted to satisfy diverse problem's requirements. Lastly, portability is achieved through the use of the standard C++ language, and by isolating machine and operating system dependencies into low-level modules, which are hidden from the application developer by GAME'S application programming interfaces. The development of GAME is central to the Programming Environment for Applications of PArallel GENetic Algorithms project (PAPAGENA). This is the principal European Community (ESPRIT III) funded parallel genetic algorithms project. It has two main goals: to provide a general-purpose tool kit, supporting the development and analysis of large-scale parallel genetic algorithms (PGAs) applications, and to demonstrate the potential of applying evolutionary computing in diverse problem domains. The research reported in this thesis is divided in two parts: i) the analysis of GA models and the study of existing GA programming environments from an application developer perspective; ii) the description of a general-purpose programming environment designed to help with the development of GA and PGA-based computer programs. The studies carried out in the first part provide the necessary understanding of GAs' structure and operation to outline the requirements for the development of complex computer programs. The second part presents GAME as the result of combining development requirements, relevant features of existing environments and innovative ideas, into a powerful programming environment. The system is described in terms of its abstract data structures and sub-systems that allow the representation of problems independently of any particular GA model. GAME's programming model is also presented as general-purpose object-oriented framework for programming coarse-grained parallel applications. GAME has a modular architecture comprising five modules: the Virtual Machine, the Parallel Execution Module, the Genetic Libraries, the Monitoring Control Module, and the Graphic User Interface. GAME's genetic-oriented abstract data structures, and the Virtual Machine, isolates genetic operators and algorithms from low-level operations such as memory management, exception handling, etc. The Parallel Execution Module supports GAME's object- oriented parallel programming model. It defines an application programming interface and a runtime library that allow the same parallel application, created within the environment, to run on different hardware and operating system platforms. The Genetic Libraries outline a hierarchy of components implemented as parameterised versions of standard and custom genetic operators, algorithms and applications. The Monitoring Control Module supports dynamic control and monitoring of simulations, whereas the Graphic User Interface defines a basic framework and graphic 'widgets' for displaying and entering data. This thesis describes the design philosophy and rationale behind these modules, covering in more detail the Virtual Machine, the Parallel Execution Module and the Genetic Libraries. The assessment discusses the system's ability to satisfy the main requirements of GA and PGA software development, as well as the features that distinguish GAME from other programming environments

Integration of Abductive and Deductive Inference Diagnosis Model and Its Application in Intelligent Tutoring System

This dissertation presents a diagnosis model, Integration of Abductive and Deductive Inference diagnosis model (IADI), in the light of the cognitive processes of human diagnosticians. In contrast with other diagnosis models, that are based on enumerating, tracking and classifying approaches, the IADI diagnosis model relies on different inferences to solve the diagnosis problems. Studies on a human diagnosticians\u27 process show that a diagnosis process actually is a hypothesizing process followed by a verification process. The IADI diagnosis model integrates abduction and deduction to simulate these processes. The abductive inference captures the plausible features of this hypothesizing process while the deductive inference presents the nature of the verification process. The IADI diagnosis model combines the two inference mechanisms with a structure analysis to form the three steps of diagnosis, mistake detection by structure analysis, misconception hypothesizing by abductive inference, and misconception verification by deductive inference. An intelligent tutoring system, Recursive Programming Tutor (RPT), has been designed and developed to teach students the basic concepts of recursive programming. The RPT prototype illustrates the basic features of the IADI diagnosis approach, and also shows a hypertext-based tutoring environment and the tutoring strategies, such as concentrating diagnosis on the key steps of problem solving, organizing explanations by design plans and incorporating the process of tutoring into diagnosis

Form Follows Feeling – The Acquisition of Design Expertise and the Function of Aesthesis in the Design Process

While the consideration of functional and technical criteria, as well as a sense of coherence are basic requirements for solving a design problem; it is the ability to induce an intended quality of aesthetic experience that is the hallmark of design expertise. Expert designers possess a highly developed sense of design, or what in this research is called aesthesis. Reflection on 25 years teaching design in the USA, Hungary, and China led to the observation that most successful design students, more than intellectual ability, drawing, model making or drive, all seemed to possess what may be called an intuitive sense of good design. It is not that they already know how to design, or that they are natural designers, it is that they have a more developed sense aesthesis. This research takes a multi-disciplinary approach to build a theory that describes what is involved in acquiring design expertise,identifies how aesthesis functions in the design process, and determines if what appears to be an intuitive sense of design is just natural talent or an acquired ability.While the consideration of functional and technical criteria, as well as a sense of coherence are basic requirements for solving a design problem; it is the ability to induce an intended quality of aesthetic experience that is the hallmark of design expertise. Expert designers possess a highly developed sense of design, or what in this research is called aesthesis. Reflection on 25 years teaching design in the USA, Hungary, and China led to the observation that most successful design students, more than intellectual ability, drawing, model making or drive, all seemed to possess what may be called an intuitive sense of good design. It is not that they already know how to design, or that they are natural designers, it is that they have a more developed sense aesthesis. This research takes a multi-disciplinary approach to build a theory that describes what is involved in acquiring design expertise,identifies how aesthesis functions in the design process, and determines if what appears to be an intuitive sense of design is just natural talent or an acquired ability.The research started with topics related to design methodology, which led to questions related to cognitive psychology, especially theories of problem-solving. An in-depth review of research in embodied cognition challenged the disembodied concept of the mind and related presuppositions, and reintroduced the body as an essential aspect of human cognition. This lead to related topics including: pre-noetic (pre-verbal) knowledge, the cognitive architecture of the brain, sense mechanisms and perception, limitations and types of memory as well as the processing capacity of the brain, and especially how emotions/feelings function in human cognition, offering insight into how designing functions as a cognitive process. The research provides evidence that more than technical rationality, expert designers rely heavily on a highly developed embodied way of knowing (tacit knowledge) througout the design process that allows them to know more than they can say. Indeed, this is the hallmark of expert performers in many fields. However, this ability is not to be understood as natural talent, but as a result of an intense developmental process that includes years of deliberate practice necessary to restructure the brain and adapt the body in a manner that facilitates exceptional performance. For expert designers it is aesthesis (a kind of body knowledge), functioning as a meta-heuristic, that allows them to solve a complex problem situation in a manner that appears effortless. Aesthesis is an ability that everyone possesses, but that expert designers have highly developed and adapted to allow them to produce buildings and built environments that induce an intended quality of aesthetic experience in the user. It is a cognitive ability that functions to both (re)structure the design problem and evaluate the solution; and allows the designer to inhabit the design world feelingly while seeking aesthetic resonance that anticipates the quality of atmosphere another is likely to experience. This ability is critical to the acquisition of design expertise

Form Follows Feeling – The Acquisition of Design Expertise and the Function of Aesthesis in the Design Process

While the consideration of functional and technical criteria, as well as a sense of coherence, are basic requirements for solving a design problem; it is the ability to induce an intended quality of aesthetic experience that is the hallmark of design expertise. Expert designers possess a highly developed sense of design, or what in this research is called aesthesis. Reflection on 25 years teaching design in the USA, Hungary, and China led to the observation that most successful design students, more than intellectual ability, drawing, model making or drive, all seemed to possess what may be called an intuitive sense of good design. It is not that they already know how to design, or that they are natural designers, it is that they have a more developed sense aesthesis. This research takes a multi-disciplinary approach to build a theory that describes what is involved in acquiring design expertise, identifies how aesthesis functions in the design process and determines if what appears to be an intuitive sense of design is just natural talent or an acquired ability. The research started with topics related to design methodology, which led to questions related to cognitive psychology, especially theories of problem-solving. An in-depth review of research in embodied cognition challenged the disembodied concept of the mind and related presuppositions and reintroduced the body as an essential aspect of human cognition. This lead to related topics including: pre-noetic (pre-verbal) knowledge, the cognitive architecture of the brain, sense mechanisms and perception, limitations and types of memory as well as the processing capacity of the brain, and especially how emotions/feelings function in human cognition, offering insight into how designing functions as a cognitive process.  The research provides evidence that more than technical rationality, expert designers rely heavily on a highly developed embodied way of knowing (tacit knowledge) throughout the design process that allows them to know more than they can say. Indeed, this is the hallmark of expert performers in many fields. However, this ability is not to be understood as natural talent, but as a result of an intense developmental process that includes years of deliberate practice necessary to restructure the brain and adapt the body in a manner that facilitates exceptional performance. For expert designers it is aesthesis (a kind of body knowledge), functioning as a meta-heuristic, that allows them to solve a complex problem situation in a manner that appears effortless. Aesthesis is an ability that everyone possesses that expert designers have highly developed and adapted to allow them to produce buildings and built environments that induce an intended quality of aesthetic experience to the user. It is a cognitive ability that functions to both (re)structure the design problem, evaluates the solution and allows the designer to inhabit the design world feelingly while seeking aesthetic resonance that anticipates the quality of atmosphere another is likely to experience. This ability is critical to the acquisition of design expertise