Learning from experience in the engineering of non-orthogonal architectural surfaces: A computational design system

This research paints a comprehensive picture of the current state of the conception and engineering of non-orthogonal architectural surfaces. The present paradigm in the design and engineering of these elaborate building structures is such that the overall form is decided first and it is then broken down into building components (façade cladding, or structural or shell elements) retrospectively. Subsequently, there is a division between the creation of the design and then the reverse engineering of it. In most of these projects, the discretisation of elaborate architectural surfaces into building components has little to do with how the form has been created, and the logic of the global form and its local subdivision are not of the same order. Experience gained through project work in the sponsoring company Buro Happold has been harnessed to inform the implementation of a design tool prototype. It is an open, extendable system. The development of the tool aims at stepping outside the current paradigm in practice; provides an integrated process of bottom-up generation of form and top-down search and optimisation, using an evolutionary method. The assertion of this thesis is that non-orthogonal design, which mimics a natural form in appearance, can be derived using mechanisms found in nature. These mechanisms, e.g. growth and evolution, can be transferred in such a way that they integrate aspects of the aesthetic, manufacturing, construction or performance. Designs are then created with an inherent logic. Growing form by adding discrete local geometries to produce larger componential surfaces ensures that the local parts and the global geometry are coherent and of the same kind. The aspiration is to make use of computational methods to contribute to the design and buildability of non-orthogonal architectural surfaces, and to further the discussion, development and application of digital design tools in practice

Network intrusion detection using genetic programming.

Masters Degree. University of KwaZulu-Natal, Pietermaritzburg.Network intrusion detection is a real-world problem that involves detecting intrusions on a computer network. Detecting whether a network connection is intrusive or non-intrusive is essentially a binary classification problem. However, the type of intrusive connections can be categorised into a number of network attack classes and the task of associating an intrusion to a particular network type is multiclass classification. A number of artificial intelligence techniques have been used for network intrusion detection including Evolutionary Algorithms. This thesis investigates the application of evolutionary algorithms namely, Genetic Programming (GP), Grammatical Evolution (GE) and Multi-Expression Programming (MEP) in the network intrusion detection domain. Grammatical evolution and multi-expression programming are considered to be variants of GP. In this thesis, a comparison of the effectiveness of classifiers evolved by the three EAs within the network intrusion detection domain is performed. The comparison is performed on the publicly available KDD99 dataset. Furthermore, the effectiveness of a number of fitness functions is evaluated. From the results obtained, standard genetic programming performs better than grammatical evolution and multi-expression programming. The findings indicate that binary classifiers evolved using standard genetic programming outperformed classifiers evolved using grammatical evolution and multi-expression programming. For evolving multiclass classifiers different fitness functions used produced classifiers with different characteristics resulting in some classifiers achieving higher detection rates for specific network intrusion attacks as compared to other intrusion attacks. The findings indicate that classifiers evolved using multi-expression programming and genetic programming achieved high detection rates as compared to classifiers evolved using grammatical evolution

Real life applications of bio-inspired computing models: EAP and NEPs

Tesis doctoral inédita leída en la Universidad Autónoma de Madrid, Escuela Politécnica Superior, Departamento de Ingeniería Informática. Fecha de lectura: 04-07-201

Digital control networks for virtual creatures

Robot control systems evolved with genetic algorithms traditionally take the form of floating-point neural network models. This thesis proposes that digital control systems, such as quantised neural networks and logical networks, may also be used for the task of robot control. The inspiration for this is the observation that the dynamics of discrete networks may contain cyclic attractors which generate rhythmic behaviour, and that rhythmic behaviour underlies the central pattern generators which drive lowlevel motor activity in the biological world. To investigate this a series of experiments were carried out in a simulated physically realistic 3D world. The performance of evolved controllers was evaluated on two well known control tasks—pole balancing, and locomotion of evolved morphologies. The performance of evolved digital controllers was compared to evolved floating-point neural networks. The results show that the digital implementations are competitive with floating-point designs on both of the benchmark problems. In addition, the first reported evolution from scratch of a biped walker is presented, demonstrating that when all parameters are left open to evolutionary optimisation complex behaviour can result from simple components

Extending Grammatical Evolution to Evolve Digital Surfaces with Genr8

we try to find novel approaches to design. Figure 2: A time series capturing 7 growth steps of a HEMLS surface in an environment with five repellors (here drawn as cylinders). The smallest surface is the axiom. The largest surface is the final growth step. Had the repellors been absent, a flat square would have been formed. Figure 3: A HEMLS growth language expressed in Backus Naur Form (BNF). Any derivation of this BNF produces a HEMLS (i.e. a grammar). The terminals are interpreted to form a surface using turtle graphics. Figure 4: A physical model made by Jordi Truco at the Architectural Association in London. The design process started with Genr8 and the evolved digital surface was subsequently exported so that a physical model could be manufactured