Understanding analogical reasoning : viewpoints from psychology and related disciplines

Analogy and metaphor have a long history of study in linguistics, education, philosophy and psychology. Consensus over what analogy is or how analogy functions in language and thought, however, has been elusive. This paper, the first in a two part series, examines these various research traditions, attempting to bring out major lines of agreement over the role of analogy in individual human experience. As well as being a general literature review which may be helpful for newcomers to the study of analogy, this paper attempts to extract from these literatures existing theories, models and concepts which may be interesting or useful for computational studies of analogical reasoning

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

The 'what' and 'how' of learning in design, invited paper

Previous experiences hold a wealth of knowledge which we often take for granted and use unknowingly through our every day working lives. In design, those experiences can play a crucial role in the success or failure of a design project, having a great deal of influence on the quality, cost and development time of a product. But how can we empower computer based design systems to acquire this knowledge? How would we use such systems to support design? This paper outlines some of the work which has been carried out in applying and developing Machine Learning techniques to support the design activity; particularly in utilising previous designs and learning the design process

Toward an expert project management system

The purpose of the research effort is to prescribe a generic reusable shell that any project office can install and customize for the purposes of advising, guiding, and supporting project managers in that office. The prescribed shell is intended to provide both: a component that generates prescriptive guidance for project planning and monitoring activities, and an analogy (intuition) component that generates descriptive insights of previous experience of successful project managers. The latter component is especially significant in that it has the potential to: retrieve insights, not just data, and provide a vehicle for expert PMs to easily transcribe their current experiences in the course of each new project managed

The SEC-system : reuse support for scheduling system development

Recently, in a joint cooperation of Stichting VNA, SAL Apotheken, the Faculty of Management and Organization, and the University Centre for Pharmacy, University of Groningen in the Netherlands, a Ph.D-study started regarding Apot(he)ek, Organization and Management (APOM). The APOM-project deals with the structuring and steering of pharmacy organization. The manageability of the internal pharmacy organization, and the manageability of the direct environment of pharmacy organization is the subject matter. The theoretical background of the APOM-project is described. A literature study was made to find mixes of objectives. Three mixes of objectives in pharmacy organization are postulated; the product mix, the process mix, and the customer mix. The typology will be used as a basic starting point for the empirical study in the next phase of the APOM-project.

Reasoning by analogy in the generation of domain acceptable ontology refinements

Refinements generated for a knowledge base often involve the learning of new knowledge to be added to or replace existing parts of a knowledge base. However, the justifiability of the refinement in the context of the domain (domain acceptability) is often overlooked. The work reported in this paper describes an approach to the generation of domain acceptable refinements for incomplete and incorrect ontology individuals through reasoning by analogy using existing domain knowledge. To illustrate this approach, individuals for refinement are identified during the application of a knowledge-based system, EIRA; when EIRA fails in its task, areas of its domain ontology are identified as requiring refinement. Refinements are subsequently generated by identifying and reasoning with similar individuals from the domain ontology. To evaluate this approach EIRA has been applied to the Intensive Care Unit (ICU) domain. An evaluation (by a domain expert) of the refinements generated by EIRA has indicated that this approach successfully produces domain acceptable refinements

An autonomous satellite architecture integrating deliberative reasoning and behavioural intelligence

This paper describes a method for the design of autonomous spacecraft, based upon behavioral approaches to intelligent robotics. First, a number of previous spacecraft automation projects are reviewed. A methodology for the design of autonomous spacecraft is then presented, drawing upon both the European Space Agency technological center (ESTEC) automation and robotics methodology and the subsumption architecture for autonomous robots. A layered competency model for autonomous orbital spacecraft is proposed. A simple example of low level competencies and their interaction is presented in order to illustrate the methodology. Finally, the general principles adopted for the control hardware design of the AUSTRALIS-1 spacecraft are described. This system will provide an orbital experimental platform for spacecraft autonomy studies, supporting the exploration of different logical control models, different computational metaphors within the behavioral control framework, and different mappings from the logical control model to its physical implementation

Learning strategies in interpreting text: From comprehension to illustration

Learning strategies can be described as behaviours and thoughts a learner engages in during learning that are aimed at gaining knowledge. Learners are, to use Mayer’s (1996) constructivist definition, ‘sense makers’. We can therefore position this to mean that, if learners are sense makers, then learning strategies are essentially cognitive processes used when learners are striving to make sense out of newly presented material. This paper intends to demonstrate that such thoughts and behaviours can be made explicit and that students can co-ordinate the basic cognitive processes of selecting, organising and integrating. I will discuss two learning strategies which were developed during three cycles of an action research enquiry with a group of illustration students. While each cycle had its own particular structure and aims, the main task, that of illustrating a passage of expository text into an illustration was a constant factor. The first learning strategy involved assisting students develop ‘macropropositions’—personal understandings of the gist or essence of a text (Louwerse and Graesser, 2006; Armbruster, Anderson and Ostertag, 1987; Van Dijk & Kintsch, 1983). The second learning strategy used a form of induction categorised as analogical reasoning (Holyoak, 2005; Sloman and Lagnado, 2005). Both strategies were combined to illustrate the expository text extract. The data suggests that design students benefit from a structured approach to learning, where thinking processes and approaches can be identified and accessible for other learning situations. The research methodology is based on semi-structured interviews, questionnaires, developmental design (including student notes) and final design output. All student names used are pseudonyms. The text extract from ‘Through the Magic Door’ an essay Sir Arthur Conan Doyle, (1907) has been included as it provides context to analysis outcomes, student comments and design outputs. Keywords: Action Research; Illustration; Macrostructures; Analogical Reasoning; Learning Strategies</p

DecMS : an approach to providing decision support within NEC delivery

Decision-making across the military capability lifecycle phases can vary considerably in terms of the types of decisions made and the manner in which they are made. Although decision-making has received considerable attention within the research community, much work has concentrated on providing decision support for particular styles of decision-making. However, within capability delivery there is a need to develop approaches that can both map styles of decision-making to particular decision problems, and provide decision support at an executable level of detail. This paper presents the Decision Management and Support (DecMS) approach to providing decision support during capability delivery. The approach is based upon refining a fundamental model of decision-making to an executable level of detail. Refinement is controlled using analogical reasoning to ensure that the model is refined in accordance with the needs of the decision problem at hand. Future work will involve testing the effectiveness of the approach