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Force-Based Evolutionary Computation Approach for Automatic Skeletal Motion Learning in Human Animation

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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 "landscape", 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 "blueprint" design techniques in developing organic structures. Using a "recipe" to 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 "Mutator" 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 concept to Negroponte's "Architecture Machine" which he proposed would be computer system so personalised so as to be almost unusable by other people. The Universal State Space Modeller The Universal State Space Modeller is the basis of Frazer's current work. It is a system which can be used to model any structure, hence the universal claim in it's title. The datastructure underlying the modeller is a state space of scaleless logical points, called motes. Motes are arranged in a close-packing sphere arrangement, which makes each one equidistant from it's twelve neighbours. Any point can be broken down into a self-similar tetrahedral structure of logical points. Giving the state space a fractal nature which allows modelling at many different levels at once. Each mote can be thought of as analogous to a cell in a biological organism. Every mote carries a copy of the architectural genetic code in the same way that each cell within a organism carries a copy of it's DNA. The genetic code of a mote is stored as a sequence of binary "morons" which are grouped together into spatial configurations which are interpreted as the state of the mote. The developmental process begins with a seed. The seed develops through cellular duplication according to the rules of the genetic code. In the beginning the seed develops mainly in response to the internal genetic code, but as the development progresses the environment plays a greater role. Cells communicate by passing messages to their immediate twelve neighbours. However, it can send messages directed at remote cells, without knowledge of it's spatial relationship. During the development cells take on specialised functions, including environmental sensors or producers of raw materials. The resulting system is process driven, without presupposing the existence of a construction set to use. The datastructure can be interpreted in many ways to derive various phenotypes. The resulting structure is a by-product of the cellular activity during development and in response to the environment. As such the resulting structures have much in common with living organisms which are also the emergent result or by-product of local cellular activity. Primordial Architectural Soups To conclude, Frazer presents some of the most recent work done, evolving fundamental structures using limited raw materials, an initial seed and massive feedback. Frazer proposes to go further and do away with the need for initial seed and start with a primordial soup of basic architectural concepts. The research is attempting to evolve the starting conditions and evolutionary processes without any preconditions. Is there enough time to evolve a complex system from the basic building blocks which Frazer proposes? The computational complexity of the task being embarked upon is not discussed. There is an implicit assumption that the "superb tactics" of natural selection are enough to cut through the complexity of the task. However, Kauffman has shown how self-organisation plays a major role in the early development of replicating systems which we may call alive. Natural selection requires a solid basis upon which it can act. Is the primordial soup which Frazer proposes of the correct constitution to support self-organisation? Kauffman suggests that one of the most important attributes of a primordial soup to be capable of self-organisation is the need for a complex network of catalysts and the controlling mechanisms to stop the reactions from going supracritical. Can such a network be provided of primitive architectural concepts? What does it mean to have a catalyst in this domain? Conclusion Frazer shows some interesting work both in the areas of evolutionary design and self-organising systems. It is obvious from his work that he sympathizes with the opinions put forward by Kauffman that the order found in living organisms comes from both external evolutionary pressure and internal self-organisation. His final remarks underly this by paraphrasing the words of Kauffman, that life is always to found on the edge of chaos. By the "edge of chaos" Kauffman is referring to the area within the ordered regime of a system close to the "phase transition" to chaotic behaviour. Unfortunately, Frazer does not demonstrate that the systems he has presented have the necessary qualities to derive useful order at the edge of chaos. He does not demonstrate, as Kauffman does repeatedly, that there exists a "phase transition" between ordered and chaotic regimes of his systems. He also does not make any studies of the relationship of useful forms generated by his work to phase transition regions of his systems should they exist. If we are to find an organic architecture, in more than name alone, it is surely to reside close to the phase transition of the construction system of which is it built. Only there, if we are to believe Kauffman, are we to find useful order together with environmentally sensitive and thermodynamically open systems which can approach the utility of living organisms.
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The article describes a system for real-time interpolated animation that addresses some of these problems. Through creating parameterized motions-which the authors call verbs parameterized by adverbs-a single authored verb produces a continuous range of subtle variations of a given motion at real-time rates. As a result, simulated figures alter their actions based on their momentary mood or in response to changes in their goals or environmental stimuli. For example, they demonstrate a walk verb that can show emotions such as happiness and sadness, and demonstrate subtle variations due to walking up or down hill while turning to the left and right. They also describe verb graphs, which act as the glue to assemble verbs and their adverbs into a runtime data structure. Verb graphs provide the means for seamless transition from verb to verb for the simulated figures within an interactive runtime system. Finally they briefly discuss the discrete event simulator that handles the runtime main loop
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