37746133
The Transfer of Text-Editing Skill
Abstract Computer-naive subjects were taught to use either one or two line editors and then a screen editor. Positive transfer was observed both between the line editors and from the line editors to the screen editor. Transfer expressed itself in terms of reductions in total time, keystrokes, residual errors, and seconds per keystroke. A simple two-component model of transfer is proposed that allows for the differential practice of general and specific components when learning a skill.
12617679
Human Symbol Manipulation Within an Integrated Cognitive Architecture
This article describes the Adaptive Control of Thought-Rational (ACT-R) cognitive architecture (Anderson et al., 2004; Anderson & Lebiere, 1998) and its detailed application to the learning of algebraic symbol manipulation. The theory is applied to modeling the data from a study by Qin, Anderson, Silk, Stenger, & Carter (2004) in which children learn to solve linear equations and perfect their skills over a 6-day period. Functional MRI data show that: (a) a motor region tracks the output of equation solutions, (b) a prefrontal region tracks the retrieval of declarative information, (c) a parietal region tracks the transformation of mental representations of the equation, (d) an anterior cingulate region tracks the setting of goal information to control the information flow, and (e) a caudate region tracks the firing of productions in the ACT-R model. The article concludes with an architectural comparison of the competence children display in this task and the competence that monkeys have shown in tasks that require manipulations of sequences of elements.
195901903
Integrating analogical mapping and general problem solving: the path-mapping theory
This article describes the path-mapping theory of how humans integrate analogical mapping and general problem solving. The theory posits that humans represent analogs with declarative roles, map analogs by lower-level retrieval of analogous role paths, and coordinate mappings with higher-level organizational knowledge. Implemented in the ACT-R cognitive architecture, the path-mapping theory enables models of analogical mapping behavior to incorporate and interface with other problem-solving knowledge. Path-mapping models thus can include task-specific skills such as encoding analogs or generating responses, and can make behavioral predictions at the level of real-world metrics such as latency or correctness. We show that the path-mapping theory can successfully account for the major phenomena addressed by previous theories of analogy. We also describe a path-mapping model that can account for subjects' incremental eye-movement and typing behavior in a story-mapping task. We discuss extensions and implications of this work to other areas of analogy and problem-solving research.
29133778
Toward a real-time model-based training system
This article describes the development of a real-time model-based training system that provides adaptive ''over-the-shoulder'' (OTS) instructions to trainees as they learn to perform an Anti-Air Warfare Coordinator (AAWC) task. The long-term goal is to develop a system that will provide real-time instructional materials based on learners' actions, so that eventually the initial set of instructions on a task can be strengthened, complemented, or overridden at different stages of training. The training system is based on the ACT-R architecture, which serves as the theoretical background for the cognitive model that monitors the learning process of the trainee. An experiment was designed to study the impact of OTS instructions on learning. Results showed that while OTS instructions facilitated short-term learning, (a) they took time away from the processing of current information, (b) their effects tended to decay rapidly in initial stages of training, and (c) their effects on training diminished when the OTS instructions were proceduralized in later stages of training. A cognitive model that learned from both the upfront and OTS instructions was created and provided good fits to the learning and performance data collected from human participants. Our results suggest that to fully capture the symbiotic performance between humans and intelligent training systems, it is important to closely monitor the learning process of the trainee so that instructional interventions can be delivered effectively at different stages of training. We proposed that such a flexible system can be developed based on an adaptive cognitive model that provides real-time predictions on learning and performance.
17702751
The Geometry Tutor
The tutor for doing proofs in high school geometry consists of a cot of ideal and buggy rules (IRR), a tutor, and an interface. The IBR is responsible for ehiuertly computing matcher, to all the correct and incorrect rules The interface is responsible for interacting with the student and graphically representing the proof. The tutor is responsible for directing the IBR and interface to achieve a current tutorial strategy. The strategy wo employ involves tracing the student's behavior in terms of what rules in the IBR it instantiates, correcting the student when behavior deviates below a minimum threshold, and helping the student over hurdles. While incomplete, current evidence indicates the geometry tutor is guite effective. 
 
The Advanced Computer Tutoring Project has been working on the development of intelligent computerhased tutors for mathematics and science subjects in the range of senior high-school to junior college. This paper describes the general framework that we have developed and its instantiation in the case of a tutor tor generating proofs in geometry. First, we will describe the general philosophy of out tutoring efforts. Second, we will describe the basic structure of the geometry tutor that we have built. Third, we will describe the ongoing efforts to evaluate the tutor.
1998598
Dynamic Student Modelling in an Intelligent Tutor for LISP Programming
We describe an intelligent tutor for LISP programming. This tutor achieves a set of pedagogical objectives derived from Anderson's (1983) learning theory provide instruction in the context of problem-solving, have the student generate as much of each solution as possible, provide immediate feedback on errors, and represent the goal structure of the problem-solving. The tutorial interface facilitates communication and prevents distracting low-level errors Field tests of the tutor in college classes demonstrate that it is more effective than conventional classroom instruction.
32806401
Use of multiple difference-of-Gaussian filters to verify geometric models
Abstract Experiments are reported with a program which recognizes London buses in busy street scenes. The program uses a 3D model of a bus. together with knowledge of camera and scene parameters, to compute the visual appearance of possible target events. In earlier work this took the form of 2D templates, which identify locations within the image where abrupt discontinuities of grey-value are expected. Each template corresponds to an hypothesis which is verified by measuring the agreement between the predicted features and the response of a Sobel filter to the image data. This paper reports an extension to the program which offers improved selectivity, and a more general-purpose method of linking predicted features to detected imageattributes. Multiple difference-of-Gaussian filters perform an initial object-independent analysis of the image to provide an intermediate domain in which object-dependent features, predicted by hypothesized instances of the model, are tested.
22373766
Explorations of an incremental, Bayesian algorithm for categorization
An incremental categorization algorithm is described which, at each step, assigns the next instance to the most probable category. Probabilities are estimated by a Bayesian inference scheme which assumes that instances are partitioned into categories and that within categories features are displayed independently and probabilistically. This algorithm can be shown to be an optimization of an ideal Bayesian algorithm in which predictive accuracy is traded for computational efficiency. The algorithm can deliver predictions about any dimension of a category and does not treat specially the prediction of category labels. The algorithm has successfully modeled much of the empirical literature on human categorization. This paper describes its application to a number of data sets from the machine learning literature. The algorithm performs reasonably well, having its only serious difficulty because the assumption of independent features is not always satisfied. Bayesian extensions to deal with nonindependent features are described and evaluated.
17909219
Robot Free Will
We introduce the perspex machine which unifies projective geometry and Turing computation and results in a supra-Turing machine. We show two ways in which the perspex machine unifies symbolic and non-symbolic AI. Firstly, we describe concrete geometrical models that map perspexes onto neural networks, some of which perform only symbolic operations. Secondly, we describe an abstract continuum of perspex logics that includes both symbolic logics and a new class of continuous logics. We argue that an axiom in symbolic logic can be the conclusion of a perspex theorem. That is, the atoms of symbolic logic can be the conclusions of sub-atomic theorems. We argue that perspex space can be mapped onto the spacetime of the universe we inhabit. This allows us to discuss how a robot might be conscious, feel, and have free will in a deterministic, or semi-deterministic, universe. We ground the reality of our universe in existence. On a theistic point, we argue that preordination and free will are compatible. On a theological point, we argue that it is not heretical for us to give robots free will. Finally, we give a pragmatic warning as to the double-edged risks of creating robots that do, or alternatively do not, have free will.
19285984
Surface Based Hypothesis Verification in Intensity Images Using Geometric and Appearance Data
In this paper we discuss current work concerning Appearance-based and CAD-based vision; two opposing vision strategies. CAD-based vision is geometry based, reliant on having complete object centred models. Appearance-based vision builds view dependent models from training images. Existing CAD-based vision systems that work with intensity images have all used one and zero dimensional features, for example lines, arcs, points and corners. We describe a system we have developed for combining these two strategies. Geometric models are extracted from a commercial CAD library of industry standard parts. Surface appearance characteristics are then learnt automatically by observing actual object instances. This information is combined with geometric information and is used in hypothesis evaluation. This augmented description improves the systems robustness to texture, specularities and other artifacts which are hard to model with geometry alone, whilst maintaining the advantages of a geometric description.
6600453
The nature of indexing: how humans and machines analyze messages and texts for retrieval - Part I: Research, and the nature of human indexing
Abstract Does human intellectual indexing have a continuing role to play in the face of increasingly sophisticated automatic indexing techniques? In this two-part essay, a computer scientist and long-time TREC participant (Perez-Carballo) and a practitioner and teacher of human cataloging and indexing (Anderson) pursue this question by reviewing the opinions and research of leading experts on both sides of this divide. We conclude that human analysis should be used on a much more selective basis, and we offer suggestions on how these two types of indexing might be allocated to best advantage. Part one of the essay critiques the comparative research, then explores the nature of human analysis of messages or texts and efforts to formulate rules to make human practice more rigorous and predictable. We find that research comparing human vs automatic approaches has done little to change strongly held beliefs, in large part because many associated variables have not been isolated or controlled. Part II focuses on current methods in automatic indexing, its gradual adoption by major indexing and abstracting services, and ways for allocating human and machine approaches. Overall, we conclude that both approaches to indexing have been found to be effective by researchers and searchers, each with particular advantages and disadvantages. However automatic indexing has the over-arching advantage of decreasing cost, as human indexing becomes ever more expensive.