206565835
Strategy Choice and Change in Programming
Abstract This research studied looping or iterative choice and change, especially between the "while-do" and "repeat-until" looping constructs in the PASCAL programming language. The empirical results from the first experiment, in which subjects were free to choose between the two looping alternatives, indicated that most PASCAL programmers are quite sensitive to the nature of the problems being solved and adaptable in choosing appropriate looping strategies. Another two experiments were performed in which subjects were either forced or induced to use one of the two looping strategies. These two experiments indicated that subjects are quite tenacious in using the appropriate strategy and their performance deteriorates when they are forced to use a different strategy.
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.
12350992
A Rational Analysis of Categorization
Abstract A rational analysis tries to predict the behavior of a cognitive system from the assumption it is optimized to the environment. An iterative categorization algorithm has been developed which attempts to get optimal Bayesian estimates of the probabilities that objects will display various features. A prior probability is estimated that an object comes from a category and combined with conditional probabilities of displaying features if the object comes from the category. Separate Bayesian treatments are offered for the cases of discrete and continuous dimensions. The resulting algorithm is efficient, works well in the case of large data bases, and replicates the full range of empirical literature in human categorization.
8794180
The generality/specificity of expertise in scientific reasoning
Previous research on scientific reasoning has shown that it involves a diverse set of skills. Yet, little is known about generality or domain specificity of those skills, an important issue in theories of expertise and in attempts to automate scientific reasoning skills. We present a study designed to test what kinds of skills psychologists actually use in designing and interpreting experiments and contrast expertise within a particular research area with general expertise at designing and interpreting experiments. The results suggest that psychologists use many domain-general skills in their experimentation and that bright and motivated Carnegie Mellon undergraduates are missing many of these skills. We believe that these results have important implications for psychological and artificial intelligence models of expertise, as well as educational implications in the domain of science instruction.
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.
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.
5262167
Marching diamonds for unstructured meshes
We present a higher-order approach to the extraction of isosurfaces from unstructured meshes. Existing methods use linear interpolation along each mesh edge to find isosurface intersections. In contrast, our method determines intersections by performing barycentric interpolation over diamonds formed by the tetrahedra incident to each edge. Our method produces smoother, more accurate isosurfaces. Additionally, interpolating over diamonds, rather than linearly interpolating edge endpoints. enables us to identify up to two isosurface intersections per edge. This paper details how our new technique extracts isopoints, and presents a simple connection strategy for forming a triangle mesh isosurface.
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.
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.
13037682
Gigabit routing on a software-exposed tiled-microprocessor
This paper investigates the suitability of emerging tiled-architectures, equipped with low-latency on-chip networks, for high-performance network routing. In this paper, we present the design, implementation and evaluation of a continuum of software-based routers on the MIT RAW microprocessor. The routers presented in this paper explore 1) several design choices for mapping the routing functions to the RAW tiles, 2) the role and behavior of RAW on-chip interconnects for transporting and switching packets, and 3) the placement of packet buffers and their interaction with the RAW on-chip networks. Our experiments evaluate the performance benefit of streaming on-chip networks for transporting packet payloads, effect of buffering on the linecards, and the cost of scal ing our design. Our software-based routers on RAW can achieve a throughput of 15Gb/sec - an order of magnitude improvement over previous software routers on traditional general-purpose architectures and at least four times faster than Intel's XP1200 Network Processor.
46723192
On the role of metaphor and language in design of third party payments in eBanking: Usability and quality
This paper describes results of a usability study of contrasting user-interface designs for Internet Banking (eBanking). Two specific interface metaphors were compared in the first experiment, linear form filling and array editing interaction modes. Terminology in the interaction dialogue was compared in the second experiment, using typical banking language and a generic, plain language interface. This research aimed to perform usability evaluation and comparison of the alternative interface designs to illuminate the development of new eBanking services. This research involved sixty-one participants (Internet users and customers of the involved Bank) exploring the designs in controlled experiments involving hands-on experience. Banks are interested in ensuring their eBanking services are highly customer-centric and that the interface matches customer expectations in order to drive customers towards this lower cost channel. The results of the first experiment (N=32, where N indicates the number of participants in the cohort) concluded that the simple form-filling metaphor, taken from the traditional paper-based procedure, was generally more usable than a Spreadsheet metaphor. In the second experiment (N=29), it was found that although banking terminology was not completely understood across the cohort, the instructional language changes did not impact significantly on usability.