Chris Scogings

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We discuss algorithms and methods for classifying the clusters of model animals that emerge from simulations of collective behaviour in artificial life models. We show how important statistical properties for understanding scaling and universal growth can be measured from complex and chaotic model systems. We describe animal clustering algorithms and the(More)
There has been some ambiguity about the growth of attractors in Kauffman networks with network size. Some recent work has linked this to the role and growth of circuits or loops of boolean variables. Using numerical methods we have investigated the growth of structural circuits in Kauffman networks and suggest that the exponential growth in the number of(More)
— Computer simulations of complex systems such as physical aggregation processes or swarming and collective behaviour of life-forms, often require order N-squared computational complexity for N microscopic components. This is a significant handicap to simulating systems large enough to compare with real-world experimental data. We discuss space partitioning(More)
Planning and steering numerical experiments that involve many simulations are difficult tasks to automate. We describe how a simulation scheduling tool can help experimenters submit and revoke simulation jobs on the basis of the most up to date partial results and resource estimates. We show how ideas such as pre- and post-conditions; interrupt handling;(More)
Many numerical simulations applications continue to require large computing budgets to allow their use in state-of-the-art parameter regimes. We report on a number of optimisation techniques that are especially applicable to spatial simulations. We employ trade-off techniques based on the use of high-memory and especially 64-bit addressable memory to boost(More)
We observe the spontaneous emergence of spatial tribes in an animat agent model where simple genetic inheritance is supported. Our predator-prey model simulates a flat-world of animat agents which breed, move, eat and predate according to priorities encoded in their genotype. Initialising a random mixture of all possible priority list genotypes, we find not(More)