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In “An Evolutionary Architecture”, John Frazer presents an overview of his work for the past 30 years. Attempting to develop a theoretical basis for architecture using analogies with nature's processes of evolution and morphogenesis. Frazer's vision of the future of architecture is to construct organic buildings. Thermodynamically open systems which are more environmentally aware and sustainable physically, sociologically and economically. The range of topics which Frazer discusses is a good illustration of the breadth and depth of the evolutionary design problem. Environmental Modelling One of the first topics dealt with is the importance of environmental modelling within the design process. Frazer shows how environmental modelling is often misused or misinterpreted by architects with particular reference to solar modelling. From the discussion given it would seem that simplifications of the environmental models is the prime culprit resulting in misinterpretation and misuse. The simplifications are understandable given the amount of information needed for accurate modelling. By simplifying the model of the environmental conditions the architect is able to make informed judgments within reasonable amounts of time and effort. Unfortunately the simplications result in errors which compound and cause the resulting structures to fall short of their anticipated performance. Frazer obviously believes that the computer can be a great aid in the harnessing of environmental modelling data, providing that the same simplifying assumptions are not made and that better models and interfaces are possible. Physical Modelling Physical modelling has played an important role in Frazer's research. Leading to the construction of several novel machine readable interactive models, ranging from lego-like building blocks to beermat cellular automata and wall partitioning systems. Ultimately this line of research has led to the Universal Constructor and the Universal Interactor. The Universal Constructor The Universal Constructor features on the cover of the book. It consists of a base plug-board, called the “landscapei, on top of which “smart” blocks, or cells, can be stacked vertically. The cells are individually identified and can communicate with neighbours above and below. Cells communicate with users through a bank of LEDs displaying the current state of the cell. The whole structure is machine readable and so can be interpreted by a computer. The computer can interpret the states of the cells as either colour or geometrical transformations allowing a wide range of possible interpretations. The user interacts with the computer display through direct manipulation of the cells. The computer can communicate and even direct the actions of the user through feedback with the cells to display various states. The direct manipulation of the cells encourages experimentation by the user and demonstrates basic concepts of the system. The Universal Interactor The Universal Interactor is a whole series of experimental projects investigating novel input and output devices. All of the devices speak a common binary language and so can communicate through a mediating central hub. The result is that input, from say a body-suit, can be used to drive the out of a sound system or vice versa. The Universal Interactor opens up many possibilities for expression when using a CAD system that may at first seem very strange.However, some of these feedback systems may prove superior in the hands of skilled technicians than more standard devices. Imagine how a musician might be able to devise structures by playing melodies which express the character. Of course the interpretation of input in this form poses a difficult problem which will take a great deal of research to achieve. The Universal Interactor has been used to provide environmental feedback to affect the development of evolving genetic codes. The feedback given by the Universal Interactor has been used to guide selection of individuals from a population. Adaptive Computing Frazer completes his introduction to the range of tools used in his research by giving a brief tour of adaptive computing techniques. Covering topics including cellular automata, genetic algorithms, classifier systems and artificial evolution. Cellular Automata As previously mentioned Frazer has done some work using cellular automata in both physical and simulated environments. Frazer discusses how surprisingly complex behaviour can result from the simple local rules executed by cellular automata. Cellular automata are also capable of computation, in fact able to perform any computation possible by a finite state machine. Note that this does not mean that cellular automata are capable of any general computation as this would require the construction of a Turing machine which is beyond the capabilities of a finite state machine. Genetic Algorithms Genetic algorithms were first presented by Holland and since have become a important tool for many researchers in various areas.Originally developed for problem-solving and optimization problems with clearly stated criteria and goals. Frazer fails to mention one of the most important differences between genetic algorithms and other adaptive problem-solving techniques, ie. neural networks. Genetic algorithms have the advantage that criteria can be clearly stated and controlled within the fitness function. The learning by example which neural networks rely upon does not afford this level of control over what is to be learned. Classifier Systems Holland went on to develop genetic algorithms into classifier systems. Classifier systems are more focussed upon the problem of learning appropriate responses to stimuli, than searching for solutions to problems. Classifier systems receive information from the environment and respond according to rules, or classifiers. Successful classifiers are rewarded, creating a reinforcement learning environment. Obviously, the mapping between classifier systems and the cybernetic view of organisms sensing, processing and responding to environmental stimuli is strong. It would seem that a central process similar to a classifier system would be appropriate at the core of an organic building. Learning appropriate responses to environmental conditions over time. Artificial Evolution Artificial evolution traces it's roots back to the Biomorph program which was described by Dawkins in his book “The Blind Watchmaker”. Essentially, artificial evolution requires that a user supplements the standard fitness function in genetic algorithms to guide evolution. The user may provide selection pressures which are unquantifiable in a stated problem and thus provide a means for dealing ill-defined criteria. Frazer notes that solving problems with ill-defined criteria using artificial evolution seriously limits the scope of problems that can be tackled. The reliance upon user interaction in artificial evolution reduces the practical size of populations and the duration of evolutionary runs. Coding Schemes Frazer goes on to discuss the encoding of architectural designs and their subsequent evolution. Introducing two major systems, the Reptile system and the Universal State Space Modeller. Blueprint vs. Recipe Frazer points out the inadequacies of using standard “blueprinti design techniques in developing organic structures. Using a “recipe” describe the process of constructing a building is presented as an alternative. Recipes for construction are discussed with reference to the analogous process description given by DNA to construct an organism. The Reptile System The Reptile System is an ingenious construction set capable of producing a wide range of structures using just two simple components. Frazer saw the advantages of this system for rule-based and evolutionary systems in the compactness of structure descriptions. Compactness was essential for the early computational work when computer memory and storage space was scarce. However, compact representations such as those described form very rugged fitness landscapes which are not well suited to evolutionary search techniques. Structures are created from an initial “seed” or minimal construction, for example a compact spherical structure. The seed is then manipulated using a series of processes or transformations, for example stretching, shearing or bending. The structure would grow according to the transformations applied to it. Obviously, the transformations could be a predetermined sequence of actions which would always yield the same final structure given the same initial seed. Alternatively, the series of transformations applied could be environmentally sensitive resulting in forms which were also sensitive to their location. The idea of taking a geometrical form as a seed and transforming it using a series of processes to create complex structures is similar in many ways to the early work of Latham creating large morphological charts. Latham went on to develop his ideas into the “Mutatori system which he used to create organic artworks. Generalising the Reptile System Frazer has proposed a generalised version of the Reptile System to tackle more realistic building problems. Generating the seed or minimal configuration from design requirements automatically. From this starting point (or set of starting points) solutions could be evolved using artificial evolution. Quantifiable and specific aspects of the design brief define the formal criteria which are used as a standard fitness function. Non-quantifiable criteria, including aesthetic judgments, are evaluated by the user. The proposed system would be able to learn successful strategies for satisfying both formal and user criteria. In doing so the system would become a personalised tool of the designer. A personal assistant which would be able to anticipate aesthetic judgements and other criteria by employing previously successful strategies. Ultimately, this is a similar