Barbara Strug

Distributed Adaptive Design with Hierarchical Autonomous Graph Transformation Systems

In this paper a graph transformation system with the parallel derivation is used to model the process of distribution and adaptation for computer aided design. It is based on earlier research in formal language theory, especially graph grammars, and distributed models. The motivation for the ideas presented here is given and possible ways of application are described. A connection to the multi-agent model is also presented.

Graph Transformations in Evolutionary Design

This paper deals with the problems of hierarchical representation of skeletal structures and their optimization by means of an evolutionary algorithm. We describe the main advantages of using hierarchical graph structures to represent the designed objects as well as specialized genetic operators able to work on these graphs A top-down algorithm allowing for optimization of structures at different levels of hierarchy is also introduced. We illustrate the proposed method with examples of its application to the problem of designing optimal transmission towers.

Reasoning about designs through frequent patterns mining

This paper deals with reasoning about designs based on their internal structures in the form of attributed hypergraphs. A database containing hypergraphs representing solutions of similar design tasks is searched for frequently occurring subgraphs. On the basis of search results the quality of newly created solutions is evaluated. Moreover the syntactic reasoning rules are specified by the designer on the basis of the design knowledge concerning a given task and used to evaluate hypergraphs representing new solutions.

Machine Learning Approach in Mutation Testing

This paper deals with an approach based on the similarity of mutants. This similarity is used to reduce the number of mutants to be executed. In order to calculate such a similarity among mutants their structure is used. Each mutant is converted into a hierarchical graph, which represents the program’s flow, variables and conditions. On the basis of this graph form a special graph kernel is defined to calculate similarity among programs. It is then used to predict whether a given test would detect a mutant or not. The prediction is carried out with the help of a classification algorithm. This approach should help to lower the number of mutants which have to be executed. An experimental validation of this approach is also presented in this paper. An example of a program used in experiments is described and the results obtained, especially classification errors, are presented.

Applying cooperating distributed graph grammars in computer aided design

This paper deals with a graph grammar model of cooperation and distribution for generating designs in computer aided design domain. It is based on earlier research in formal language theory based models for design, especially graph grammars, and also on the developments in the theory of grammar systems. The motivation for the idea presented is given and some possible modes of application are briefly described.

Supporting communication and cooperation in distributed representation for adaptive design

Different types of graphs has been successfully used to represent designs at different stages of the design process. Changes to a model representing a design during the process can be modelled by applying graph transformations. In many real life design tasks the changes/updates can be carried out simultaneously on different parts of the design. Hence a model based on graph transformations is coupled with a multiagent paradigm to enable the parallelisation of these transformations to mimic the real life approach. In this paper a hypergraph representation and transformation model is used as a basis for building a multiagent system supporting distribution and adaptation in computer aided design. This representation can be applicable throughout the lifecycle of the design. It is based on research in formal language theory, like graph grammars, and distributed models including multiagent systems. The motivation for the work presented here is given and possible applications are described. The application of the theoretical results in a graph distribution toolkit proposed as a multiagent framework is also considered. To assure the efficiency of the system it should be implemented as a parallel multiagent system. The hypergraph distribution and partial replication, allowing for its parts to be managed by agents, is also presented. The approach is illustrated by a case study from the domain of building design, where it is used to represent, modify and maintain building information.

Multi-Agent System for Distributed Adaptive Design

This paper deals with the design of a multi-agent system for distributed design. The design processes are often complex and require high computational costs. Yet in many situations many elements of a design process can be computed simultaneously and thus lowering the total time required to finish the design. In this paper an approach based on hypergraph representation and using a formal background of the parallel application of the graph transformation rules is presented (parallel derivation process). The system is illustrated with examples from the floor layout design system.

An Evolutionary Algorithm for Solving the Inverse Problem for Iterated Function Systems for a Two Dimensional Image

This paper presents an approach based on evolutionary computations to the IFS inverse problem. Having a bitmap image we look for a set of functions that can reproduce a good approximation if a given image. A method using variable number of mappings is proposed. A number of different crossover operators is described and tested. Different parameters for fitness functions are also tested. The paper ends with some experimental results showing images we were able to generate with our method

Classifying Mutants with Decomposition Kernel

The paper deals with the problem of reducing the cost of mutation testing using artificial intelligence methods. The presented approach is based on the similarity of mutants. The mutants are coded as control flow diagrams representing the programs structure, variables and conditions. The similarity is then calculated with the use of a new graph kernel and used to predict if a given test case detects a mutant or not. The prediction process is performed by a classification algorithm. Experimental results are also presented in this paper on the basis of two systems.

Heterogeneous graph grammars synchronization in CAD systems supported by hypergraph representations of buildings

The automation of the design process is an important property of computer aided design systems. One of the methods which support it is using graph grammars as a tool for representing the design process. In this paper we consider the coordination of two independent sub-processes: interior and exterior design. The problem of their coordination results from the fact that both actions may interfere. Assuming that sub-processes are modelled by means of two independent graph grammars, our goal is to create a mechanism of their synchronization, which enables preserving an overall consistency of the design. The proposed mechanism is illustrated by the example of the interaction of external and internal design processes performed on the shared environment.