Approximation of statistical analysis and estimation by morphological adaptation in a model of slime mould

True slime mould Physarum polycephalum approximates a range of complex computations via growth and adaptation of its protoplasmic transport network, stimulating a large body of recent research into how such a simple organism can perform such complex feats. The properties of networks constructed by slime mould are known to be influenced by the local distribution of stimuli within its environment. But can the morphological adaptation of slime mould yield any information about the global statistical properties of its environment? We explore this possibility using a particle based model of slime mould.We demonstrate how morphological adaptation in blobs of virtual slime mould may be used as a simple computational mechanism that can coarsely approximate statistical analysis, estimation and tracking. Preliminary results include the approximation of the geometric centroid of 2D shapes, approximation of arithmetic mean from spatially represented sorted and unsorted data distributions, and the estimation and dynamical tracking of moving object position in the presence of noise contaminated input stimuli. The results suggest that it is possible to utilise collectives of very simple components with limited individual computational ability (for example swarms of simple robotic devices) to extract statistical features from complex datasets by means of material adaptation and sensorial fusion

On the development of slime mould morphological, intracellular and heterotic computing devices

The use of live biological substrates in the fabrication of unconventional computing (UC) devices is steadily transcending the barriers between science fiction and reality, but efforts in this direction are impeded by ethical considerations, the field’s restrictively broad multidisciplinarity and our incomplete knowledge of fundamental biological processes. As such, very few functional prototypes of biological UC devices have been produced to date. This thesis aims to demonstrate the computational polymorphism and polyfunctionality of a chosen biological substrate — slime mould Physarum polycephalum, an arguably ‘simple’ single-celled organism — and how these properties can be harnessed to create laboratory experimental prototypes of functionally-useful biological UC prototypes. Computing devices utilising live slime mould as their key constituent element can be developed into a) heterotic, or hybrid devices, which are based on electrical recognition of slime mould behaviour via machine-organism interfaces, b) whole-organism-scale morphological processors, whose output is the organism’s morphological adaptation to environmental stimuli (input) and c) intracellular processors wherein data are represented by energetic signalling events mediated by the cytoskeleton, a nano-scale protein network. It is demonstrated that each category of device is capable of implementing logic and furthermore, specific applications for each class may be engineered, such as image processing applications for morphological processors and biosensors in the case of heterotic devices. The results presented are supported by a range of computer modelling experiments using cellular automata and multi-agent modelling. We conclude that P. polycephalum is a polymorphic UC substrate insofar as it can process multimodal sensory input and polyfunctional in its demonstrable ability to undertake a variety of computing problems. Furthermore, our results are highly applicable to the study of other living UC substrates and will inform future work in UC, biosensing, and biomedicine

Opinions and Outlooks on Morphological Computation

Morphological Computation is based on the observation that biological systems seem to carry out relevant computations with their morphology (physical body) in order to successfully interact with their environments. This can be observed in a whole range of systems and at many different scales. It has been studied in animals – e.g., while running, the functionality of coping with impact and slight unevenness in the ground is "delivered" by the shape of the legs and the damped elasticity of the muscle-tendon system – and plants, but it has also been observed at the cellular and even at the molecular level – as seen, for example, in spontaneous self-assembly. The concept of morphological computation has served as an inspirational resource to build bio-inspired robots, design novel approaches for support systems in health care, implement computation with natural systems, but also in art and architecture. As a consequence, the field is highly interdisciplinary, which is also nicely reflected in the wide range of authors that are featured in this e-book. We have contributions from robotics, mechanical engineering, health, architecture, biology, philosophy, and others

Towards physarum engines

The slime mould Physarum polycephalum is a suitable candidate organism for soft-matter robotics because it exhibits controllable transport, movement and guidance behaviour. Physarum may be considered as a smart computing and actuating material since both its motor and control systems are distributed within its undifferentiated tissue and can survive trauma such as excision, fission and fusion of plasmodia. Thus it may be suitable for exploring the generation and distribution of micro-Actuation in individual units or planar arrays. We experimentally show how the plasmodium of Physarum is shaped to execute controllable oscillatory transport behaviour applicable in small hybrid engines. We measure the lifting force of the plasmodium and demonstrate how protoplasmic transport can be influenced by externally applied illumination stimuli. We provide an exemplar vehicle mechanism by coupling the oscillations of the plasmodium to drive the wheels of a Braitenberg vehicle and use light stimuli to effect a steering mechanism. Using a particle model of Physarum we show how emergent travelling wave patterns produced by competing oscillatory domains may be used to to generate spatially represented actuation patterns. We demonstrate different patterns of controllable motion, including linear, reciprocal, rotational and helical, and demonstrate in simulation how dynamic oscillatory patterns may be translated into motive forces for simple transport of substances within a patterned environment. © 2012 - IOS Press and the authors. All rights reserved