Showing all 4 Tech Reports linked to Trevor Collins

Using genre to support active participation in learning communities

Many communities exist that learn and share information either partly or wholly online. These (wholly or partially) on-line communities share messages, documents, and other artefacts that contain useful community knowledge. Members of the community learn through this sharing process, and the growing archive they create forms a valuable learning resource for existing and new members of the community. Two main kinds of approach exist to support community members in accessing resources. The first...read more

ID: kmi-00-13

Date: 2000

Author(s): Trevor Collins, Paul Mulholland and Stuart Watt

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Understanding Evolutionary Computing: A hands on approach

Evolutionary computing is the study of robust search algorithms based on the principles of evolution. An Evolutionary Algorithm (EA) searches a problem space in order to find possible solutions to a given problem. This paper is intended to highlight the advantages of using software visualization techniques in evolutionary computing: Firstly it describes how a high-dimensional problem space can be represented in two (or more) dimensions, suitable for visualization; secondly it introduces how EA...read more

ID: kmi-97-14

Date: 1997

Author(s): Trevor Collins

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Genotypic-Space Mapping: Population Visualization for Genetic Algorithms

This paper presents one proposed method for representing the population data of Genetic Algorithms (GAs). Typical population data from GAs are large high-dimensional sets of binary, decimal, real or string, state values. This makes their representation by two or three spatial dimensions somewhat difficult. Several attempts at population visualization have been made but have failed to efficiently solve this high dimensional to 2/3 dimensional space mapping problem. The use of the proposed...read more

ID: kmi-96-11

Date: 1996

Author(s): Trevor Collins

Resources:

The Visualization of Genetic Algorithms - Related Work

Genetic Algorithms are robust search algorithms capable of finding multiple solutions to complex problems. In order to ensure that the algorithm is working correctly, it is necessary to examine the steps involved in its execution and the results produced at each stage. It is proposed that Software Visualization may be one technique that could support this task. This review examines a number of Software Visualization systems, discusses the key features that may prove useful for visualizing...read more

ID: kmi-95-12

Date: 1995

Author(s): Trevor Collins

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