arXiv subjects

Jeff Jones

Publications and source records attributed to Jeff Jones.

At least 19 recordsLinked to original sources

arXiv2019

The US Program in Ground-Based Gravitational Wave Science: Contribution from the LIGO Laboratory

Recent gravitational-wave observations from the LIGO and Virgo observatories have brought a sense of great excitement to scientists and citizens the world over. Since September 2015,10 binary black hole coalescences and one binary neutron star coalescence have been observed. They have provided remarkable, revolutionary insight into the "gravitational Universe" and have greatly extended the field of multi-messenger astronomy. At present, Advanced LIGO can see binary black hole coalescences out to redshift 0.6 and binary neutron star coalescences to redshift 0.05. This probes only a very small fraction of the volume of the observable Universe. However, current technologies can be extended to construct "$3^\mathrm{rd}$ Generation" (3G) gravitational-wave observatories that would extend our reach to the very edge of the observable Universe. The event rates over such a large volume would be in the hundreds of thousands per year (i.e.tens per hour). Such 3G detectors would have a 10-fold improvement in strain sensitivity over the current generation of instruments, yielding signal-to-noise ratios of 1000 for events like those already seen. Several concepts are being studied for which engineering studies and reliable cost estimates will be developed in the next 5 years.

astro-ph.IM↗

arXiv2016

Embodied Approximation of the Density Classification Problem via Morphological Adaptation

The Majority (or Density Classification) Problem in Cellular Automata (CA) aims to converge a string of cells to a final homogeneous state which reflects the majority of states present in the initial configuration. The problem is challenging in CA as individual cells only possess information about their own and local neighbour states. The problem is an exercise in the propagation and processing of information within a distributed computational medium. We explore whether the Majority Problem can be approximated in a similarly simple distributed computing substrate - a multi-agent model of slime mould. An initial pattern of discrete voting choices is represented by spatial arrangement of the agent population, temporarily held in-place by an attractant stimulus. When this stimulus is removed the model adapts its shape and size, moving to form a minimal distance connecting line. The final position of this line is shown, in simple examples, to successfully represent the majority vote decision, and also accurately reflects the size of the majority. We note properties, limitations and potential improvements to the approach before returning full-circle by re-encoding this morphological adaptation approach in a simple (and more space efficient) 1D CA model.

cs.ET↗

arXiv2015

Exploiting Environmental Computation in a Multi-Agent Model of Slime Mould

Very simple organisms, such as the single-celled amoeboid slime mould Physarum polycephalum possess no neural tissue yet, despite this, are known to exhibit complex biological and computational behaviour. Given such limited resources, can environmental stimuli play a role in generating the complexity of slime mould behaviour? We use a multi-agent collective model of slime mould to explore a two-way mechanism where the collective behaviour is influenced by simulated chemical concentration gradient fields and, in turn, this behaviour alters the spatial pattern of the concentration gradients. This simple mechanism yields complex behaviour amid the dynamically changing gradient profiles and suggests how the apparently intelligent response of the slime mould could possibly be due to outsourcing of computation to the environment.

cs.ET↗

arXiv2015

Automated Guidance of Collective Movement in a Multi-Agent Model of Physarum polycephalum

Collective movement occurs in living systems where the simple movements of individual members of a pop- ulation are combined to generate movement of the collective as a whole, displaying complex dynamics which cannot be found in the component parts themselves. The plasmodium stage of slime mould Physarum polycephalum displays complex amoeboid movement during its foraging and hazard avoidance and its movement can be influenced by the spatial placement of attractant and repellent stimuli. Slime mould is attractive to robotics due to its simple component parts and the distributed nature of its control and locomotion mechanisms. We investigate methods of automated guidance of a multi-agent swarm collective along a pre-defined path to a goal location. We demonstrate a closed-loop feedback mechanism using attractant and repellent stimuli. We find that guidance by repellent stimuli (a light illumination mask) provides faster and more accurate guidance than attractant sources, which exhibit overshooting phenomena at path turns. The method allows traversal of convoluted arenas with challenging obstacles and provides an insight into how unconven- tional computing substrates may be hybridised with classical computing methods to take advantage of the benefits of both approaches.

cs.ET↗

arXiv2015

Applications of Multi-Agent Slime Mould Computing

The giant single-celled slime mould Physarum polycephalum has inspired rapid develop- ments in unconventional computing substrates since the start of this century. This is primarily due to its simple component parts and the distributed nature of the computation which it approximates during its growth, foraging and adaptation to a changing environment. Slime mould functions as a living embodied computational material which can be influenced (or pro- grammed) by the placement of external stimuli. The goal of exploiting this material behaviour for unconventional computation led to the development of a multi-agent approach to the ap- proximation of slime mould behaviour. The basis of the model is a simple dynamical pattern formation mechanism which exhibits self-organised formation and subsequent adaptation of collective transport networks. The system exhibits emergent properties such as relaxation and minimisation and it can be considered as a virtual computing material, influenced by the external application of spatial concentration gradients. In this paper we give an overview of this multi-agent approach to unconventional computing. We describe its computational mechanisms and different generic application domains, together with concrete example ap- plications of material computation. We examine the potential exploitation of the approach for computational geometry, path planning, combinatorial optimisation, data smoothing and statistical applications.

cs.ET↗

arXiv2015

Towards Lateral Inhibition and Collective Perception in Unorganised Non-Neural Systems

Could simple organisms such as slime mould approximate LI without recourse to neural tissue? We describe a model whereby LI can emerge without explicit inhibitory wiring, using only bulk transport effects. We use a multi-agent model of slime mould to reproduce the char- acteristic edge contrast amplification effects of LI using excitation via attractant based stimuli. We also explore a counterpart behaviour, Lateral Activation (where stimulated regions are inhibited and lateral regions are excited), using simulated exposure to light irradiation. In both cases restoration of baseline activity occurs when the stimuli are removed. In addition to the enhancement of local edge contrast the long-term change in population density distribution corresponds to a collective response to the global brightness of 2D image stimuli, including the scalloped inten- sity profile of the Chevreul staircase and the perceived difference of two identically bright patches in the Simultaneous Brightness Contrast (SBC) effect. This simple modelapproximatesLIcontrastenhancementphenomenaandglobalbrightnessper- ception in collective unorganised systems without fixed neural architectures. This may encourage further research into unorganised analogues of neural processes in simple organisms and suggests novel mechanisms to generate collective perception of contrast and brightness in distributed computing and robotic devices.

cs.ET↗

arXiv2015

Representation of Shape Mediated by Environmental Stimuli in Physarum polycephalum and a Multi-agent Model

The slime mould Physarum polycephalum is known to construct proto- plasmic transport networks which approximate proximity graphs by forag- ing for nutrients during its plasmodial life cycle stage. In these networks, nodes are represented by nutrients and edges are represented by proto- plasmic tubes. These networks have been shown to be efficient in terms of length and resilience of the overall network to random damage. However relatively little research has been performed in the potential for Physarum transport networks to approximate the overall shape of a dataset. In this paper we distinguish between connectivity and shape of a planar point dataset and demonstrate, using scoping experiments with plasmodia of P. polycephalum and a multi-agent model of the organism, how we can gen- erate representations of the external and internal shapes of a set of points. As with proximity graphs formed by P. polycephalum, the behaviour of the plasmodium (real and model) is mediated by environmental stimuli. We further explore potential morphological computation approaches with the multi-agent model, presenting methods which approximate the Convex Hull and the Concave Hull. We demonstrate how a growth parameter in the model can be used to transition between Convex and Concave Hulls. These results suggest novel mechanisms of morphological computation mediated by environmental stimuli.

cs.ET↗

arXiv2015

Quantitative Transformation for Implementation of Adder Circuits in Physical Systems

Computing devices are composed of spatial arrangements of simple funda- mental logic gates. These gates may be combined to form more complex adding circuits and, ultimately, complete computer systems. Implementing classical adding circuits using unconventional, or even living substrates such as slime mould Physarum polycephalum, is made difficult and often impracti- cal by the challenges of branching fan-out of inputs and regions where circuit lines must cross without interference. In this report we explore whether it is possible to avoid spatial propagation, branching and crossing completely in the design of adding circuits. We analyse the input and output patterns of a single-bit full adder circuit. A simple quantitative transformation of the input patterns which considers the total number of bits in the input string allows us to map the respective input combinations to the correct outputs patterns of the full adder circuit, reducing the circuit combinations from a 2:1 mapping to a 1:1 mapping. The mapping of inputs to outputs also shows an incremental linear progression, suggesting its implementation in a range of physical systems. We demonstrate an example implementation, first in simulation, inspired by self-oscillatory dynamics of the acellular slime mould Physarum polycephalum. We then assess the potential implementation using plasmodium of slime mould itself. This simple transformation may enrich the potential for using unconventional computing substrates to implement digital circuits.

cs.ET↗

arXiv2015

Mechanisms Inducing Parallel Computation in a Model of Physarum polycephalum Transport Networks

P. polycephalum may be considered as a spatially represented parallel unconventional computing substrate, but how can this `computer' be programmed? In this paper we examine and catalogue individual low-level mechanisms which may be used to induce network formation and adaptation in a multi-agent model of P. polycephalum. These mechanisms include those intrinsic to the model (particle sensor angle, rotation angle, and scaling parameters) and those mediated by the environment (stimulus loca- tion, distance, angle, concentration, engulfment and consumption of nutrients, and the presence of simulated light irradiation, repellents and obstacles). The mechanisms in- duce a concurrent integration of chemoattractant and chemorepellent gradients diffusing within the 2D lattice upon which the agent population resides, stimulating growth, move- ment, morphological adaptation and network minimisation. Chemoattractant gradients, and their modulation by the engulfment and consumption of nutrients by the model population, represent an efficient outsourcing of spatial computation. The mechanisms may prove useful in understanding the search strategies and adaptation of distributed organisms within their environment, in understanding the minimal requirements for com- plex adaptive behaviours, and in developing methods of spatially programming parallel unconventional computers and robotic devices.

cs.ET↗

arXiv2015

Slime Mould Inspired Generalised Voronoi Diagrams with Repulsive Fields

The giant single-celled amoeboid organism Physarum polycephalum constructs minimising transport networks but can also approximate the Voronoi diagram using two different mechanisms. In the first method Voronoi bisectors are rep- resented by deformation of a pre-existing plasmodial network by repellent sources acting as generating points. In the second method generating points act as inoculation sites for grow- ing plasmodia and Voronoi bisectors are represented by vacant regions before the plasmodia fuse. To explore the behaviour of minimising networks in the presence of repulsion fields we utilise a computational model of Physarum as a distributed virtual computing material. We characterise the different types of computational behaviours elicited by attraction and repulsion stimuli and demonstrate the approximation Voronoi diagrams using growth towards attractants, avoidance of repellents, and combinations of both. Approximation of Voronoi diagrams for point data sources, complex planar shapes and circle sets is demonstrated. By altering repellent con- centration we found that partition of data sources was maintained but the internal network connectivity was minimised by the contractile force of the transport network. To conclude, we find that the repertoire of unconventional computation methods is enhanced by the addition of stimuli presented by repellent fields, suggesting novel approaches to plane-division, packing, and minimisation problems.

cs.ET↗

arXiv2015

The Emergence and Dynamical Evolution of Complex Transport Networks from Simple Low-Level Behaviours

The true slime mould Physarum polycephalum is a recent well studied example of how complex transport networks emerge from simple auto-catalytic and self- organising local interactions, adapting structure and function against changing environmental conditions and external perturbation. Physarum networks also exhibit computationally desirable measures of transport efficiency in terms of overall path length, minimal connectivity and network resilience. Although significant progress has been made in mathematically modelling the behaviour of Physarum networks (and other biological transport networks) based on observed features in experimental settings, their initial emergence - and in particular their long-term persistence and evolution - is still poorly understood. We present a low-level, bottom-up, approach to the modelling of emergent transport networks. A population of simple particle-like agents coupled with paracrine chemotaxis behaviours in a dissipative environment results in the spontaneous emergence of persistent, complex structures. Second order emergent behaviours, in the form of network surface minimisation, are also observed contributing to the long term evolution and dynamics of the networks. The framework is extended to allow data presentation and the population is used to perform a direct (spatial) approximation of network minimisation problems. Three methods are employed, loosely relating to behaviours of Physarum under different environmental conditions. Finally, the low-level approach is summarised with a view to further research.

cs.ET↗

arXiv2015

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 proto- plasmic 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 in- fluenced 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 approx- imate statistical analysis, estimation and tracking. Preliminary results include the approximation of the geometric centroid of 2D shapes, ap- proximation 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 ex- ample swarms of simple robotic devices) to extract statistical features from complex datasets by means of material adaptation and sensorial fusion.

cs.ET↗

arXiv2015

Material Approximation of Data Smoothing and Spline Curves Inspired by Slime Mould

Using a particle model of Physarum displaying emer- gent morphological adaptation behaviour we demonstrate how a minimal approach to collective material computation may be used to transform and summarise properties of spatially represented datasets. We find that the virtual material relaxes more strongly to high-frequency changes in data which can be used for the smoothing (or filtering) of data by ap- proximating moving average and low-pass filters in 1D datasets. The relaxation and minimisation properties of the model enable the spatial computation of B-spline curves (approximating splines) in 2D datasets. Both clamped and unclamped spline curves, of open and closed shapes, can be represented and the degree of spline curvature corresponds to the relaxation time of the material. The material computation of spline curves also includes novel quasi-mechanical properties including unwind- ing of the shape between control points and a preferential adhesion to longer, straighter paths. Interpolating splines could not directly be ap- proximated due to the formation and evolution of Steiner points at nar- row vertices, but were approximated after rectilinear pre-processing of the source data. This pre-processing was further simplified by transform- ing the original data to contain the material inside the polyline. These exemplar results expand the repertoire of spatially represented uncon- ventional computing devices by demonstrating a simple, collective and distributed approach to data and curve smoothing.

cs.ET↗

arXiv2015

A Morphological Adaptation Approach to Path Planning Inspired by Slime Mould

Using a particle model of slime mould we demonstrate scoping experiments which explore how path planning may be performed by morphological adaptation. We initially demonstrate simple path planning by a shrinking blob of virtual plasmodium between two attractant sources within a polygonal arena. We examine the case where multiple paths are required and the subsequent selection of a single path from multiple options. Collision-free paths are implemented via repulsion from the borders of the arena. Finally, obstacle avoidance is implemented by repulsion from obstacles as they are uncovered by the shrinking blob. These examples show proof-of-concept results of path planning by morphological adaptation which complement existing research on path planning in novel computing substrates.

cs.ET↗

arXiv2015

On the role of the plasmodial cytoskeleton in facilitating intelligent behaviour in slime mould Physarum polycephalum

The plasmodium of slime mould Physarum polycephalum behaves as an amorphous reaction-diffusion computing substrate and is capable of apparently intelligent behaviour. But how does intelligence emerge in an acellular organism? Through a range of laboratory experiments, we visualise the plasmodial cytoskeleton, a ubiquitous cellular protein scaffold whose functions are manifold and essential to life, and discuss its putative role as a network for transducing, transmitting and structuring data streams within the plasmodium. Through a range of computer modelling techniques, we demonstrate how emergent behaviour, and hence computational intelligence, may occur in cytoskeletal communications networks. Specifically, we model the topology of both the actin and tubulin cytoskeletal networks and discuss how computation may occur therein. Furthermore, we present bespoke cellular automata and particle swarm models for the computational process within the cytoskeleton and observe the incidence of emergent patterns in both. Our work grants unique insight into the origins of natural intelligence; the results presented here are therefore readily transferable to the fields of natural computation, cell biology and biomedical science. We conclude by discussing how our results may alter our biological, computational and philosophical understanding of intelligence and consciousness.

cs.ET↗

arXiv2013

On Creativity of Slime Mould

Slime mould Physarum polycephalum is large single cell with intriguingly smart behaviour. The slime mould shows outstanding abilities to adapt its protoplasmic network to varying environmental conditions. The slime mould can solve tasks of computational geometry, image processing, logics and arithmetics when data are represented by configurations of attractants and repellents. We attempt to map behavioural patterns of slime onto the cognitive control versus schizotypy spectrum phase space and thus interpret slime mould's activity in terms of creativity.

cs.ET↗

arXiv2013

Computation of the Travelling Salesman Problem by a Shrinking Blob

The Travelling Salesman Problem (TSP) is a well known and challenging combinatorial optimisation problem. Its computational intractability has attracted a number of heuristic approaches to generate satisfactory, if not optimal, candidate solutions. In this paper we demonstrate a simple unconventional computation method to approximate the Euclidean TSP using a virtual material approach. The morphological adaptation behaviour of the material emerges from the low-level interactions of a population of particles moving within a diffusive lattice. A `blob' of this material is placed over a set of data points projected into the lattice, representing TSP city locations, and the blob is reduced in size over time. As the blob shrinks it morphologically adapts to the configuration of the cities. The shrinkage process automatically stops when the blob no longer completely covers all cities. By manually tracing the perimeter of the blob a path between cities is elicited corresponding to a TSP tour. Over 6 runs on 20 randomly generated datasets of 20 cities this simple and unguided method found tours with a mean best tour length of 1.04, mean average tour length of 1.07 and mean worst tour length of 1.09 when expressed as a fraction of the minimal tour computed by an exact TSP solver. We examine the insertion mechanism by which the blob constructs a tour, note some properties and limitations of its performance, and discuss the relationship between the blob TSP and proximity graphs which group points on the plane. The method is notable for its simplicity and the spatially represented mechanical mode of its operation. We discuss similarities between this method and previously suggested models of human performance on the TSP and suggest possibilities for further improvement.

cs.ET↗

arXiv2012

Sounds Synthesis with Slime Mould of Physarum Polycephalum

Physarum polycephalum is a huge single cell with thousands of nuclei, which behaves like a giant amoeba. During its foraging behaviour this plasmodium produces electrical activity corresponding to different physiological states. We developed a method to render sounds from such electrical activity and thus represent spatio-temporal behaviour of slime mould in a form apprehended by humans. We show to control behaviour of slime mould to shape it towards reproduction of required range of sounds.

nlin.PS↗