Generating Systems from Multiple Levels of Abstraction

2007 ◽  
pp. 127-141 ◽  
Author(s):  
Martin Girschick ◽  
Thomas Kühne ◽  
Felix Klar
Keyword(s):  
Levels Of Abstraction ◽  
Multiple Levels

Learning at Multiple Levels of Abstraction: The Case of Verb Argument Constructions

2007 ◽  
Author(s):  
Amy Perfors ◽  
Charles Kemp ◽  
Elizabeth Wonnacott ◽  
Joshua B. Tenenbaum
Keyword(s):  
Levels Of Abstraction ◽  
Multiple Levels

scholarly journals A Model for Analysing the Collective Dynamic Behaviour and Characterising the Exploitation of Population-Based Algorithms

2014 ◽  
Vol 22 (1) ◽  
pp. 159-188 ◽  
Author(s):  
Mikdam Turkey ◽  
Riccardo Poli
Keyword(s):  
Population Dynamics ◽  
Dynamic Behaviour ◽  
Fitness Landscape ◽  
Population Based ◽  
Levels Of Abstraction ◽  
Collective Dynamic ◽  
Model Studies ◽  
Proposed Model ◽  
Wide Range ◽  
Multiple Levels

Several previous studies have focused on modelling and analysing the collective dynamic behaviour of population-based algorithms. However, an empirical approach for identifying and characterising such a behaviour is surprisingly lacking. In this paper, we present a new model to capture this collective behaviour, and to extract and quantify features associated with it. The proposed model studies the topological distribution of an algorithm's activity from both a genotypic and a phenotypic perspective, and represents population dynamics using multiple levels of abstraction. The model can have different instantiations. Here it has been implemented using a modified version of self-organising maps. These are used to represent and track the population motion in the fitness landscape as the algorithm operates on solving a problem. Based on this model, we developed a set of features that characterise the population's collective dynamic behaviour. By analysing them and revealing their dependency on fitness distributions, we were then able to define an indicator of the exploitation behaviour of an algorithm. This is an entropy-based measure that assesses the dependency on fitness distributions of different features of population dynamics. To test the proposed measures, evolutionary algorithms with different crossover operators, selection pressure levels and population handling techniques have been examined, which lead populations to exhibit a wide range of exploitation-exploration behaviours.

Analogical recognition of shape and structure in design drawings

2008 ◽  
Vol 22 (2) ◽  
pp. 117-128 ◽  
Author(s):  
Patrick W. Yaner ◽  
Ashok K. Goel
Keyword(s):  
Structural Model ◽  
Line Drawing ◽  
Source Model ◽  
Two Dimensional ◽  
Structural Components ◽  
Levels Of Abstraction ◽  
Shape Representations ◽  
Source Case ◽  
Multiple Levels

AbstractWe describe a method for constructing a structural model of an unlabeled target two-dimensional line drawing by analogy to a known source model of a drawing with similar structure. The source case is represented as a schema that contains its line drawing and its structural model represented at multiple levels of abstraction: the lines and intersections in the drawing, the shapes, the structural components, and connections of the device are depicted in the drawing. Given a target drawing and a relevant source case, our method of compositional analogy first constructs a representation of the lines and the intersections in the target drawing, then uses the mappings at the level of line intersections to transfer the shape representations from the source case to the target; next, it uses the mappings at the level of shapes to transfer the full structural model of the depicted system from the source to the target.

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