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      A Literature Review of Expert Problem Solving using Analogy

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      13th International Conference on Evaluation and Assessment in Software Engineering (EASE) (EASE)

      Evaluation and Assessment in Software Engineering (EASE)

      20 - 21 April 2009

      expert, problem solving, ill-defined, well-defined, analogy, case based reasoning, CBR, personality

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          Abstract

          We consider software project cost estimation from a problem solving perspective. Taking a cognitive psychological approach, we argue that the algorithmic basis for CBR tools is not representative of human problem solving and this mismatch could account for inconsistent results. We describe the fundamentals of problem solving, focusing on experts solving ill-defined problems. This is supplemented by a systematic literature review of empirical studies of expert problem solving of nontrivial problems. We identified twelve studies. These studies suggest that analogical reasoning plays an important role in problem solving, but that CBR tools do not model this in a biologically plausible way. For example, the ability to induce structure and therefore find deeper analogies is widely seen as the hallmark of an expert. However, CBR tools fail to provide support for this type of reasoning for prediction. We conclude this mismatch between experts’ cognitive processes and software tools contributes to the erratic performance of analogy-based prediction.

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          Most cited references 19

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          Categorization and Representation of Physics Problems by Experts and Novices*

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            Perceptual symbol systems.

            Prior to the twentieth century, theories of knowledge were inherently perceptual. Since then, developments in logic, statistics, and programming languages have inspired amodal theories that rest on principles fundamentally different from those underlying perception. In addition, perceptual approaches have become widely viewed as untenable because they are assumed to implement recording systems, not conceptual systems. A perceptual theory of knowledge is developed here in the context of current cognitive science and neuroscience. During perceptual experience, association areas in the brain capture bottom-up patterns of activation in sensory-motor areas. Later, in a top-down manner, association areas partially reactivate sensory-motor areas to implement perceptual symbols. The storage and reactivation of perceptual symbols operates at the level of perceptual components--not at the level of holistic perceptual experiences. Through the use of selective attention, schematic representations of perceptual components are extracted from experience and stored in memory (e.g., individual memories of green, purr, hot). As memories of the same component become organized around a common frame, they implement a simulator that produces limitless simulations of the component (e.g., simulations of purr). Not only do such simulators develop for aspects of sensory experience, they also develop for aspects of proprioception (e.g., lift, run) and introspection (e.g., compare, memory, happy, hungry). Once established, these simulators implement a basic conceptual system that represents types, supports categorization, and produces categorical inferences. These simulators further support productivity, propositions, and abstract concepts, thereby implementing a fully functional conceptual system. Productivity results from integrating simulators combinatorially and recursively to produce complex simulations. Propositions result from binding simulators to perceived individuals to represent type-token relations. Abstract concepts are grounded in complex simulations of combined physical and introspective events. Thus, a perceptual theory of knowledge can implement a fully functional conceptual system while avoiding problems associated with amodal symbol systems. Implications for cognition, neuroscience, evolution, development, and artificial intelligence are explored.
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              The associative basis of the creative process.

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                Author and article information

                Contributors
                Conference
                April 2009
                April 2009
                : 1-10
                Affiliations
                Southampton Solent University
                Brunel University
                Article
                10.14236/ewic/EASE2009.13
                © Carolyn Mair et al. Published by BCS Learning and Development Ltd. 13th International Conference on Evaluation and Assessment in Software Engineering (EASE), Durham University, UK

                This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                13th International Conference on Evaluation and Assessment in Software Engineering (EASE)
                EASE
                13
                Durham University, UK
                20 - 21 April 2009
                Electronic Workshops in Computing (eWiC)
                Evaluation and Assessment in Software Engineering (EASE)
                Product
                Product Information: 1477-9358BCS Learning & Development
                Self URI (journal page): https://ewic.bcs.org/
                Categories
                Electronic Workshops in Computing

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