M. Schroeder and P. Noy. Multi-agent visualization based on multivariate data. In Proceedings of Autonomous Agents2001, Montreal, Canada, 2001. ACM press. Home/Search Document Not in Database Summary Related Articles Check |
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Defining Like-minded Agents with the Aid of Visualization - Noy, Schroeder (2002) Self-citation (Schroeder Noy) (Correct)
....to assist in agent orientated computation. Can this help in the pursuit of the use of visualization techniques for reasoning (diagrammatic reasoning [6] Our earlier work looked at proximity data and multivariate data in the agent domain and indicated possible metric choices for visualization[11,13]. From the agent point of view, the question is how can we apply this and how can we assist in the problem of metric choice for profiling and classification in the agent domain. How can we meaningfully identify like minded agents and then put this to use The agent paradigm is considered by some ....
....where visualization is not necessarily the end product, as well as to present the two specific applications. 2 Defining Profiles In general an agent s profile is considered to be a vector of interests and behaviours (a feature list) or a similarity measure or sets and or combinations of these [11,13]. The purpose of our work in visualization was to find layouts (in 2D or 3D) which would satisfy (usually approximately) these data either by using mathematical transformations (effective reductions via e.g. Principal Component Analysis (PCA) or distance metrics followed by Principal Coordinates ....
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M. Schroeder and P. Noy. Multi-agent visualization based on multivariate data. In Proceedings of Autonomous Agents2001, Montreal, Canada, 2001. ACM press.
Introducing Signature Exploration: a means to aid the.. - Noy, Schroeder (2001) Self-citation (Schroeder Noy) (Correct)
....figure 5) but can sense be made of the resulting patterns Thus we consider the loss of meaning associated with visualization transformations of complex data. The ideas presented here have developed out of initial visualizations of data involving dimension reduction using the tool Space Explorer [13,15,14] and in the context of ongoing work to address the problem of visualizing complex data. Space Explorer is a visualization application for multivariate and proximity data. In an initial investigation it was shown how one data set can be displayed in a number of different ways, producing different ....
....unknown data according to the user s classification. This is considered to be signature exploration by signature modification, although the simplest application would select the algorithm which gave the layout closest to that specified by the user. 3 Algorithm description Space Explorer [13,15,14] implements a number of algorithms for visualizing multivariate and proximity data. Proximity data specifies a distance between entities which may be a direct measurement or derived from the multivariate data. Figure 1 shows some of the ways in which multivariate data can be converted into ....
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Michael Schroeder and Penny Noy. Multi-agent visualization based on multivariate data. In Proceedings of Autonomous Agents
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