Chromosomal organization and evolutionary conservation of the human chromosome 19q linkage group containing three DNA repair genes

A series of human-rodent somatic cell hybrids were investigated by Southern blot analysis for the presence or absence of twenty-six molecular markers and three isozyme loci from human chromosome 19. Based on the co-retention of these markers in the various independent hybrid clones containing portions of human chromosome 19 and on pulsed field mapping, chromosome 19 is divided into twenty ordered regions. The most likely marker order for the chromosome is: (LDLR, C3)-(cen-MANNB)-D19S7-PEPD-D19S9-GPI-TGF$ \beta$-(CYP2A, NCA, CGM2, BCKAD)-PSG1a-(D19S8, XRCC1)-(D19S19, ATP1A3)-(D19S37, APOC2)-CKMM-ERCC2-ERCC1-(D19S62, D19S51)-D19S6-D19S50-D19S22-(CGB, FTL)-qter.^ The region of 19q between the proximal marker D19S7 and the distal gene coding for the beta subunit of chorionic gonadotropin (CGB) is about 37 Mb in size and covers about 37 cM genetic distance. The ration of genetic to physical distance on 19q is therefore very close to the genomic average OF 1 cM/Mb. Estimates of physical distances for intervals between chromosome 19 markers were calculated using a mapping function which estimates distances based on the number of breaks in hybrid clone panels. The consensus genetic distances between individual markers (established at HBM10) were compared to these estimates of physical distances. The close agreement between the two estimates suggested that spontaneously broken hybrids are as appropriate for this type of study as radiation hybrids.^ All three DNA repair genes located on chromosome 19 were found to have homologues on Chinese hamster chromosome 9, which is hemizygous in CHO cells, providing an explanation for the apparent ease with which mutations at these loci were identified in CHO cells. Homologues of CKMM and TGF$\beta$ (from human chromosome 19q) and a mini-satellite DNA specific to the distal region of human chromosome 19q were also mapped to Chinese hamster 9. Markers from 19p did not map to this hamster chromosome. Thus the q-arm of chromosome 19, at least between the genes PEPD and ERCC1, appears to be a linkage group which is conserved intact between humans and Chinese hamsters. ^

A hybrid method for large-scale short-term scheduling of make-and-pack production processes

Due to the ongoing trend towards increased product variety, fast-moving consumer goods such as food and beverages, pharmaceuticals, and chemicals are typically manufactured through so-called make-and-pack processes. These processes consist of a make stage, a pack stage, and intermediate storage facilities that decouple these two stages. In operations scheduling, complex technological constraints must be considered, e.g., non-identical parallel processing units, sequence-dependent changeovers, batch splitting, no-wait restrictions, material transfer times, minimum storage times, and finite storage capacity. The short-term scheduling problem is to compute a production schedule such that a given demand for products is fulfilled, all technological constraints are met, and the production makespan is minimised. A production schedule typically comprises 500–1500 operations. Due to the problem size and complexity of the technological constraints, the performance of known mixed-integer linear programming (MILP) formulations and heuristic approaches is often insufficient. We present a hybrid method consisting of three phases. First, the set of operations is divided into several subsets. Second, these subsets are iteratively scheduled using a generic and flexible MILP formulation. Third, a novel critical path-based improvement procedure is applied to the resulting schedule. We develop several strategies for the integration of the MILP model into this heuristic framework. Using these strategies, high-quality feasible solutions to large-scale instances can be obtained within reasonable CPU times using standard optimisation software. We have applied the proposed hybrid method to a set of industrial problem instances and found that the method outperforms state-of-the-art methods.

Structure and dynamics of hybrid zones at different stages of speciation in the common vole (Microtus arvalis)

The genetic structure and dynamics of hybrid zones provide crucial information for understanding the processes and mechanisms of evolutionary divergence and speciation. In general, higher levels of evolutionary divergence between taxa are more likely to be associated with reproductive isolation and may result in suppressed or strongly restricted hybridization. In this study, we examined two secondary contact zones between three deep evolutionary lineages in the common vole (Microtus arvalis). Differences in divergence times between the lineages can shed light on different stages of reproductive isolation and thus provide information on the ongoing speciation process in M. arvalis. We examined more than 800 individuals for mitochondrial (mtDNA), Y-chromosome and autosomal markers and used assignment and cline analysis methods to characterize the extent and direction of gene flow in the contact zones. Introgression of both autosomal and mtDNA markers in a relatively broad area of admixture indicates selectively neutral hybridization between the least-divergent lineages (Central and Eastern) without evidence for partial reproductive isolation. In contrast, a very narrow area of hybridization, shifts in marker clines and the quasi-absence of Y-chromosome introgression support a moving hybrid zone and unidirectional selection against male hybrids between the lineages with older divergence (Central and Western). Data from a replicate transect further support non-neutral processes in this hybrid zone and also suggest a role for landscape history in the movement and shaping of geneflow profiles.

An evolutionary algorithm for the surface structure problem

Many macroscopic properties: hardness, corrosion, catalytic activity, etc. are directly related to the surface structure, that is, to the position and chemical identity of the outermost atoms of the material. Current experimental techniques for its determination produce a “signature” from which the structure must be inferred by solving an inverse problem: a solution is proposed, its corresponding signature computed and then compared to the experiment. This is a challenging optimization problem where the search space and the number of local minima grows exponentially with the number of atoms, hence its solution cannot be achieved for arbitrarily large structures. Nowadays, it is solved by using a mixture of human knowledge and local search techniques: an expert proposes a solution that is refined using a local minimizer. If the outcome does not fit the experiment, a new solution must be proposed again. Solving a small surface can take from days to weeks of this trial and error method. Here we describe our ongoing work in its solution. We use an hybrid algorithm that mixes evolutionary techniques with trusted region methods and reuses knowledge gained during the execution to avoid repeated search of structures. Its parallelization produces good results even when not requiring the gathering of the full population, hence it can be used in loosely coupled environments such as grids. With this algorithm, the solution of test cases that previously took weeks of expert time can be automatically solved in a day or two of uniprocessor time.

Evaluation and implementation of a hybrid cross-platform application combining mobile web-technologies and native device functions

Este Proyecto de Fin de Carrera presenta un prototipo de aplicación móvil híbrida multi-plataforma para Android y iOS. Las aplicaciones móviles híbridas son una combinación de aplicaciones web móviles y aplicaciones móviles nativas. Se desarrollan parcialmente con tecnologías web y pueden acceder a la capa nativa y sensores del teléfono. Para el usuario se presentan como aplicaciones nativas, ya que se pueden descargar de las tiendas de aplicaciones y son instaladas en el dispositivo. El prototipo consiste en la migración del módulo de noticias financieras de las aplicaciones actuales para móviles de una compañía bancaria reimplementándolo como aplicación híbrida utilizando uno de los entornos de desarrollo disponibles en el mercado para este propósito. El desarrollo de aplicaciones híbridas puede ahorrar tiempo y dinero cuando se pretende alcanzar más de una plataforma móvil. El objetivo es la evaluación de las ventajas e inconvenientes que ofrece el desarrollo de aplicaciones híbridas en términos de reducción de costes, tiempo de desarrollo y resultado final de la aplicación. El proyecto consta de varias fases. Durante la primera fase se realiza un estudio sobre las aplicaciones híbridas que podemos encontrar hoy en día en el mercado utilizando los ejemplos de linkedIn, Facebook y Financial times. Se hace hincapié en las tecnologías utilizadas, uso de la red móvil y problemas encontrados. Posteriormente se realiza una comparación de distintos entornos de desarrollo multi-plataforma para aplicaciones híbridas en términos de la estrategia utilizada, plataformas soportadas, lenguajes de programación, acceso a capacidades nativas de los dispositivos y licencias de uso. Esta primera fase da como resultado la elección del entorno de desarrollo más adecuado a las exigencias del proyecto, que es PhoneGap, y continua con un análisis más detallado de dicho entorno en cuanto a su arquitectura, características y componentes. La siguiente fase comienza con un estudio de las aplicaciones actuales de la compañía para extraer el código fuente necesario y adaptarlo a la arquitectura que tendrá la aplicación. Para la realización del prototipo se hace uso de la característica que ofrece PhoneGap para acceder a la capa nativa del dispositivo, esto es, el uso de plugins. Se diseña y desarrolla un plugin que permite acceder a la capa nativa para cada plataforma. Una vez desarrollado el prototipo para la plataforma Android, se migra y adapta para la plataforma iOS. Por último se hace una evaluación de los prototipos en cuanto a su facilidad y tiempo de desarrollo, rendimiento, funcionalidad y apariencia de la interfaz de usuario. ABSTRACT. This bachelor's thesis presents a prototype of a hybrid cross-platform mobile application for Android and iOS. Hybrid mobile applications are a combination of mobile web and mobile native applications. They are built partially with web technologies and they can also access native features and sensors of the device. For a user, they look like native applications as they are downloaded from the application stores and installed on the device. This prototype consists of the migration of the financial news module of current mobile applications from a financial bank reimplementing them as a hybrid application using one of the frameworks available in the market for that purpose. Development of applications on a hybrid way can help reducing costs and effort when targeting more than one platform. The target of the project is the evaluation of the advantages and disadvantages that hybrid development can offer in terms of reducing costs and efforts and the final result of the application. The project starts with an analysis of successfully released hybrid applications using the examples of linkedIn, Facebook and Financial Times, emphasizing the different used technologies, the transmitted network data and the encountered problems during the development. This analysis is followed by a comparison of most popular hybrid crossplatform development frameworks in terms of the different approaches, supported platforms, programming languages, access to native features and license. This first stage has the outcome of finding the development framework that best fits to the requirements of the project, that is PhoneGap, and continues with a deeper analysis of its architecture, features and components. Next stage analyzes current company's applications to extract the needed source code and adapt it to the architecture of the prototype. For the realization of the application, the feature that PhoneGap offers to access the native layer of the device is used. This feature is called plugin. A custom plugin is designed and developed to access the native layer of each targeted platform. Once the prototype is finished for Android, it is migrated and adapted to the iOS platform. As a final conclusion the prototypes are evaluated in terms of ease and time of development, performance, functionality and look and feel.

Towards the automatic generation of card games through Grammar-Guided Genetic Programming

We demonstrate generating complete and playable card games using evolutionary algorithms. Card games are represented in a previously devised card game description language, a context-free grammar. The syntax of this language allows us to use grammar-guided genetic programming. Candidate card games are evaluated through a cascading evaluation function, a multi-step process where games with undesired properties are progressively weeded out. Three representa- tive examples of generated games are analysed. We observed that these games are reasonably balanced and have skill ele- ments, they are not yet entertaining for human players. The particular shortcomings of the examples are discussed in re- gard to the generative process to be able to generate quality games

Co-simulation Methodologies for Hybrid and Electric Vehicle Dynamics

In recent decades, full electric and hybrid electric vehicles have emerged as an alternative to conventional cars due to a range of factors, including environmental and economic aspects. These vehicles are the result of considerable efforts to seek ways of reducing the use of fossil fuel for vehicle propulsion. Sophisticated technologies such as hybrid and electric powertrains require careful study and optimization. Mathematical models play a key role at this point. Currently, many advanced mathematical analysis tools, as well as computer applications have been built for vehicle simulation purposes. Given the great interest of hybrid and electric powertrains, along with the increasing importance of reliable computer-based models, the author decided to integrate both aspects in the research purpose of this work. Furthermore, this is one of the first final degree projects held at the ETSII (Higher Technical School of Industrial Engineers) that covers the study of hybrid and electric propulsion systems. The present project is based on MBS3D 2.0, a specialized software for the dynamic simulation of multibody systems developed at the UPM Institute of Automobile Research (INSIA). Automobiles are a clear example of complex multibody systems, which are present in nearly every field of engineering. The work presented here benefits from the availability of MBS3D software. This program has proven to be a very efficient tool, with a highly developed underlying mathematical formulation. On this basis, the focus of this project is the extension of MBS3D features in order to be able to perform dynamic simulations of hybrid and electric vehicle models. This requires the joint simulation of the mechanical model of the vehicle, together with the model of the hybrid or electric powertrain. These sub-models belong to completely different physical domains. In fact the powertrain consists of energy storage systems, electrical machines and power electronics, connected to purely mechanical components (wheels, suspension, transmission, clutch…). The challenge today is to create a global vehicle model that is valid for computer simulation. Therefore, the main goal of this project is to apply co-simulation methodologies to a comprehensive model of an electric vehicle, where sub-models from different areas of engineering are coupled. The created electric vehicle (EV) model consists of a separately excited DC electric motor, a Li-ion battery pack, a DC/DC chopper converter and a multibody vehicle model. Co-simulation techniques allow car designers to simulate complex vehicle architectures and behaviors, which are usually difficult to implement in a real environment due to safety and/or economic reasons. In addition, multi-domain computational models help to detect the effects of different driving patterns and parameters and improve the models in a fast and effective way. Automotive designers can greatly benefit from a multidisciplinary approach of new hybrid and electric vehicles. In this case, the global electric vehicle model includes an electrical subsystem and a mechanical subsystem. The electrical subsystem consists of three basic components: electric motor, battery pack and power converter. A modular representation is used for building the dynamic model of the vehicle drivetrain. This means that every component of the drivetrain (submodule) is modeled separately and has its own general dynamic model, with clearly defined inputs and outputs. Then, all the particular submodules are assembled according to the drivetrain configuration and, in this way, the power flow across the components is completely determined. Dynamic models of electrical components are often based on equivalent circuits, where Kirchhoff’s voltage and current laws are applied to draw the algebraic and differential equations. Here, Randles circuit is used for dynamic modeling of the battery and the electric motor is modeled through the analysis of the equivalent circuit of a separately excited DC motor, where the power converter is included. The mechanical subsystem is defined by MBS3D equations. These equations consider the position, velocity and acceleration of all the bodies comprising the vehicle multibody system. MBS3D 2.0 is entirely written in MATLAB and the structure of the program has been thoroughly studied and understood by the author. MBS3D software is adapted according to the requirements of the applied co-simulation method. Some of the core functions are modified, such as integrator and graphics, and several auxiliary functions are added in order to compute the mathematical model of the electrical components. By coupling and co-simulating both subsystems, it is possible to evaluate the dynamic interaction among all the components of the drivetrain. ‘Tight-coupling’ method is used to cosimulate the sub-models. This approach integrates all subsystems simultaneously and the results of the integration are exchanged by function-call. This means that the integration is done jointly for the mechanical and the electrical subsystem, under a single integrator and then, the speed of integration is determined by the slower subsystem. Simulations are then used to show the performance of the developed EV model. However, this project focuses more on the validation of the computational and mathematical tool for electric and hybrid vehicle simulation. For this purpose, a detailed study and comparison of different integrators within the MATLAB environment is done. Consequently, the main efforts are directed towards the implementation of co-simulation techniques in MBS3D software. In this regard, it is not intended to create an extremely precise EV model in terms of real vehicle performance, although an acceptable level of accuracy is achieved. The gap between the EV model and the real system is filled, in a way, by introducing the gas and brake pedals input, which reflects the actual driver behavior. This input is included directly in the differential equations of the model, and determines the amount of current provided to the electric motor. For a separately excited DC motor, the rotor current is proportional to the traction torque delivered to the car wheels. Therefore, as it occurs in the case of real vehicle models, the propulsion torque in the mathematical model is controlled through acceleration and brake pedal commands. The designed transmission system also includes a reduction gear that adapts the torque coming for the motor drive and transfers it. The main contribution of this project is, therefore, the implementation of a new calculation path for the wheel torques, based on performance characteristics and outputs of the electric powertrain model. Originally, the wheel traction and braking torques were input to MBS3D through a vector directly computed by the user in a MATLAB script. Now, they are calculated as a function of the motor current which, in turn, depends on the current provided by the battery pack across the DC/DC chopper converter. The motor and battery currents and voltages are the solutions of the electrical ODE (Ordinary Differential Equation) system coupled to the multibody system. Simultaneously, the outputs of MBS3D model are the position, velocity and acceleration of the vehicle at all times. The motor shaft speed is computed from the output vehicle speed considering the wheel radius, the gear reduction ratio and the transmission efficiency. This motor shaft speed, somehow available from MBS3D model, is then introduced in the differential equations corresponding to the electrical subsystem. In this way, MBS3D and the electrical powertrain model are interconnected and both subsystems exchange values resulting as expected with tight-coupling approach.When programming mathematical models of complex systems, code optimization is a key step in the process. A way to improve the overall performance of the integration, making use of C/C++ as an alternative programming language, is described and implemented. Although this entails a higher computational burden, it leads to important advantages regarding cosimulation speed and stability. In order to do this, it is necessary to integrate MATLAB with another integrated development environment (IDE), where C/C++ code can be generated and executed. In this project, C/C++ files are programmed in Microsoft Visual Studio and the interface between both IDEs is created by building C/C++ MEX file functions. These programs contain functions or subroutines that can be dynamically linked and executed from MATLAB. This process achieves reductions in simulation time up to two orders of magnitude. The tests performed with different integrators, also reveal the stiff character of the differential equations corresponding to the electrical subsystem, and allow the improvement of the cosimulation process. When varying the parameters of the integration and/or the initial conditions of the problem, the solutions of the system of equations show better dynamic response and stability, depending on the integrator used. Several integrators, with variable and non-variable step-size, and for stiff and non-stiff problems are applied to the coupled ODE system. Then, the results are analyzed, compared and discussed. From all the above, the project can be divided into four main parts: 1. Creation of the equation-based electric vehicle model; 2. Programming, simulation and adjustment of the electric vehicle model; 3. Application of co-simulation methodologies to MBS3D and the electric powertrain subsystem; and 4. Code optimization and study of different integrators. Additionally, in order to deeply understand the context of the project, the first chapters include an introduction to basic vehicle dynamics, current classification of hybrid and electric vehicles and an explanation of the involved technologies such as brake energy regeneration, electric and non-electric propulsion systems for EVs and HEVs (hybrid electric vehicles) and their control strategies. Later, the problem of dynamic modeling of hybrid and electric vehicles is discussed. The integrated development environment and the simulation tool are also briefly described. The core chapters include an explanation of the major co-simulation methodologies and how they have been programmed and applied to the electric powertrain model together with the multibody system dynamic model. Finally, the last chapters summarize the main results and conclusions of the project and propose further research topics. In conclusion, co-simulation methodologies are applicable within the integrated development environments MATLAB and Visual Studio, and the simulation tool MBS3D 2.0, where equation-based models of multidisciplinary subsystems, consisting of mechanical and electrical components, are coupled and integrated in a very efficient way.

Environmental niche variation and evolutionary diversification of the Brachypodium distachyon grass complex species in their native circum-Mediterranean range

PREMISE OF THE STUDY: We conducted environmental niche modeling (ENM) of the Brachypodium distachyon s.l. complex, a model group of two diploid annual grasses ( B. distachyon , B. stacei ) and their derived allotetraploid ( B. hybridum) , native to the circum-Mediterranean region. We (1) investigated the ENMs of the three species in their native range based on present and past climate data; (2) identifi ed potential overlapping niches of the diploids and their hybrid across four Quaternary windows; (3) tested whether speciation was associated with niche divergence/conservatism in the complex species; and (4) tested for the potential of the polyploid outperforming the diploids in the native range. M ETHODS: Geo-referenced data, altitude, and 19 climatic variables were used to construct the ENMs. We used paleoclimate niche models to trace the potential existence of ancestral gene fl ow among the hybridizing species of the complex. KEY RESULTS: Brachypodium distachyon grows in higher, cooler, and wetter places, B. stacei in lower, warmer, and drier places, and B. hybridum in places with intermediate climatic features. Brachypodium hybridum had the largest niche overlap with its parent niches, but a similar distribution range and niche breadth. C ONCLUSIONS: Each species had a unique environmental niche though there were multiple niche overlapping areas for the diploids across time, suggesting the potential existence of several hybrid zones during the Pleistocene and the Holocene. No evidence of niche divergence was found, suggesting that species diversifi cation was not driven by ecological speciation but by evolutionary history, though it could be associated to distinct environmental adaptations.

Hybrid simulation-optimization based approach for the optimal design of single-product biotechnological processes

In this work, we present a systematic method for the optimal development of bioprocesses that relies on the combined use of simulation packages and optimization tools. One of the main advantages of our method is that it allows for the simultaneous optimization of all the individual components of a bioprocess, including the main upstream and downstream units. The design task is mathematically formulated as a mixed-integer dynamic optimization (MIDO) problem, which is solved by a decomposition method that iterates between primal and master sub-problems. The primal dynamic optimization problem optimizes the operating conditions, bioreactor kinetics and equipment sizes, whereas the master levels entails the solution of a tailored mixed-integer linear programming (MILP) model that decides on the values of the integer variables (i.e., number of equipments in parallel and topological decisions). The dynamic optimization primal sub-problems are solved via a sequential approach that integrates the process simulator SuperPro Designer® with an external NLP solver implemented in Matlab®. The capabilities of the proposed methodology are illustrated through its application to a typical fermentation process and to the production of the amino acid L-lysine.

Logic hybrid simulation-optimization algorithm for distillation design

In this paper, we propose a novel algorithm for the rigorous design of distillation columns that integrates a process simulator in a generalized disjunctive programming formulation. The optimal distillation column, or column sequence, is obtained by selecting, for each column section, among a set of column sections with different number of theoretical trays. The selection of thermodynamic models, properties estimation etc., are all in the simulation environment. All the numerical issues related to the convergence of distillation columns (or column sections) are also maintained in the simulation environment. The model is formulated as a Generalized Disjunctive Programming (GDP) problem and solved using the logic based outer approximation algorithm without MINLP reformulation. Some examples involving from a single column to thermally coupled sequence or extractive distillation shows the performance of the new algorithm.

Isobutane Alkylation Process Synthesis by means of Hybrid Simulation-Multiobjective Optimization

Multiobjective Generalized Disjunctive Programming (MO-GDP) optimization has been used for the synthesis of an important industrial process, isobutane alkylation. The two objective functions to be simultaneously optimized are the environmental impact, determined by means of LCA (Life Cycle Assessment), and the economic potential of the process. The main reason for including the minimization of the environmental impact in the optimization process is the widespread environmental concern by the general public. For the resolution of the problem we employed a hybrid simulation- optimization methodology, i.e., the superstructure of the process was developed directly in a chemical process simulator connected to a state of the art optimizer. The model was formulated as a GDP and solved using a logic algorithm that avoids the reformulation as MINLP -Mixed Integer Non Linear Programming-. Our research gave us Pareto curves compounded by three different configurations where the LCA has been assessed by two different parameters: global warming potential and ecoindicator-99.

Hybrid knowledge representation in a blackboard KBS for liquid retaining structure design

This paper highlights the importance of design expertise, for designing liquid retaining structures, including subjective judgments and professional experience. Design of liquid retaining structures has special features different from the others. Being more vulnerable to corrosion problem, they have stringent requirements against serviceability limit state of crack. It is the premise of the study to transferring expert knowledge in a computerized blackboard system. Hybrid knowledge representation schemes, including production rules, object-oriented programming, and procedural methods, are employed to express engineering heuristics and standard design knowledge during the development of the knowledge-based system (KBS) for design of liquid retaining structures. This approach renders it possible to take advantages of the characteristics of each method. The system can provide the user with advice on preliminary design, loading specification, optimized configuration selection and detailed design analysis of liquid retaining structure. It would be beneficial to the field of retaining structure design by focusing on the acquisition and organization of expert knowledge through the development of recent artificial intelligence technology. (C) 2003 Elsevier Ltd. All rights reserved.

Isolation and characterization of microsatellite loci from mother-of-millions, Bryophyllum delagoense (Crassulaceae), and its hybrid with Bryophyllum daigremontianum, 'Houghton's hybrid'

Nine microsatellite loci were developed, and are transferable, across the Madagascan succulents Bryophyllum daigremontianum, Bryophyllum delagoense (mother-of-millions) and their horticultural hybrid (Houghton's), from enriched libraries of the later two species. For B. delagoense, a tetraploid, three to 13 alleles per locus were found for native Madagascan (H-O = 0.4-1.0), and one to nine in invasive Australian (H-O = 0.0-1.0) samples. In addition for 91 Australian samples, only five multilocus genotypes were found (95% of individuals were of two genotypes), suggesting extensive clonality in its introduced range. These loci will be used to examine genetic diversity, hybrid origin and mating system in natural and introduced populations.

Evolutionary neural networks : models and applications

The scaling problems which afflict attempts to optimise neural networks (NNs) with genetic algorithms (GAs) are disclosed. A novel GA-NN hybrid is introduced, based on the bumptree, a little-used connectionist model. As well as being computationally efficient, the bumptree is shown to be more amenable to genetic coding lthan other NN models. A hierarchical genetic coding scheme is developed for the bumptree and shown to have low redundancy, as well as being complete and closed with respect to the search space. When applied to optimising bumptree architectures for classification problems the GA discovers bumptrees which significantly out-perform those constructed using a standard algorithm. The fields of artificial life, control and robotics are identified as likely application areas for the evolutionary optimisation of NNs. An artificial life case-study is presented and discussed. Experiments are reported which show that the GA-bumptree is able to learn simulated pole balancing and car parking tasks using only limited environmental feedback. A simple modification of the fitness function allows the GA-bumptree to learn mappings which are multi-modal, such as robot arm inverse kinematics. The dynamics of the 'geographic speciation' selection model used by the GA-bumptree are investigated empirically and the convergence profile is introduced as an analytical tool. The relationships between the rate of genetic convergence and the phenomena of speciation, genetic drift and punctuated equilibrium arc discussed. The importance of genetic linkage to GA design is discussed and two new recombination operators arc introduced. The first, linkage mapped crossover (LMX) is shown to be a generalisation of existing crossover operators. LMX provides a new framework for incorporating prior knowledge into GAs.Its adaptive form, ALMX, is shown to be able to infer linkage relationships automatically during genetic search.

Towards identifying salient patterns in genetic programming individuals

This thesis addresses the problem of offline identification of salient patterns in genetic programming individuals. It discusses the main issues related to automatic pattern identification systems, namely that these (a) should help in understanding the final solutions of the evolutionary run, (b) should give insight into the course of evolution and (c) should be helpful in optimizing future runs. Moreover, it proposes an algorithm, Extended Pattern Growing Algorithm ([E]PGA) to extract, filter and sort the identified patterns so that these fulfill as many as possible of the following criteria: (a) they are representative for the evolutionary run and/or search space, (b) they are human-friendly and (c) their numbers are within reasonable limits. The results are demonstrated on six problems from different domains.