Computational Matter: Evolving Computational Functions in Nanoscale Materials

Broersma, Hajo; Miller, Julian F.; Nichele, Stefano

doi:10.1007/978-3-319-33921-4_16

Cited by 15 publications

(20 citation statements)

References 69 publications

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“…But to be able to do this, first of all there is a need for a translation or mapping between the physical domain and the computer domain, and vice versa, as indicated in Figure 6 that was taken from [5].…”

Section: Back To the General Methodsmentioning

confidence: 99%

“…To illustrate the steps in the GA, here are the ingredients of a generic GA in pseudocode, as adapted from [5].…”

Section: Back To the General Methodsmentioning

confidence: 99%

“…More details can be found in [5] and the papers that are listed there. But we start with some additional remarks about the motivation behind the suggested approach of EIM, and by presenting more details on the use of evolutionary algorithms, with a specific example that was used to evolve a nanoparticle substrate.…”

Section: Nascence In a Nutshellmentioning

confidence: 99%

“…In the NP-network example we have just given, the stimuli signals were static voltages and time-dependent voltages and currents, but the type of signals could be different, depending on the type of material and its characteristic [5] behaviour under influence of external stimuli. The signals are either input signals, output signals or configuration signals.…”

Section: Back To the General Methodsmentioning

confidence: 99%

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Evolution in Nanomaterio: The NASCENCE Project

Broersma

2017

Inspired by Nature

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This chapter describes some of the work that was carried out by members of the NASCENCE project, an FP7 project sponsored by the European Community. Apart from some historical notes and background material, the chapter explains how nanoscale material systems have been configured to perform computational tasks by finding appropriate configuration signals using artificial evolution. Most of this exposition is centred around the work that has been carried out at the MESA+ Institute for Nanotechnology at the University of Twente using disordered networks of nanoparticles. The interested reader will also find many pointers to references that contain more details on work that has been carried out by other members of the NASCENCE consortium on composite materials based on single-walled carbon nanotubes.

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Section: Back To the General Methodsmentioning

confidence: 99%

“…To illustrate the steps in the GA, here are the ingredients of a generic GA in pseudocode, as adapted from [5].…”

Section: Back To the General Methodsmentioning

confidence: 99%

Section: Nascence In a Nutshellmentioning

confidence: 99%

Section: Back To the General Methodsmentioning

confidence: 99%

See 2 more Smart Citations

Evolution in Nanomaterio: The NASCENCE Project

Broersma

2017

Inspired by Nature

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“…Interestingly, up to now there are very few practical implementation of reservoir computers in hardware. Up to date pioneering efforts exploit photonic systems [32,70,69], complex amorphous materials [21,22,72,17,15], etc. In here we suggest yet another computing substrate: the building and its components; walls, blocks or other pre-fabricated construction components, and ultimately the material it is made of.…”

Section: Computing Concretementioning

confidence: 99%

On Buildings that Compute. A Proposal

Adamatzky

Szaciłowski

Przyczyna

et al. 2019

From Astrophysics to Unconventional Computation

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We present ideas aimed at bringing revolutionary changes on architectures and buildings of tomorrow by radically advancing the technology for the building material concrete and hence building components. We propose that by using nanotechnology we could embed computation and sensing directly into the material used for construction. Intelligent concrete blocks and panels advanced with stimuli-responsive smart paints are the core of the proposed architecture. In particular, the photo-responsive paint would sense the buildings internal and external environment while the nano-materialconcrete composite material would be capable of sensing the building environment and implement massive-parallel information processing resulting in distributed decision making. A calibration of the proposed materials with in-materio suitable computational methods and corresponding building in-formation modelling, computer-aided design and digital manufacturing tools could be achieved via models and prototypes of information processing at nano-level. The emergent technology sees a building as high-level massiveparallel computer -assembled of computing concrete blocks. Based on the generic principles of neuromorphic computation and reservoir computing we envisage a single building or an urban quarter to turn into a large-scale sensing substrate. It could behave as a universal computer, collecting and processing environmental information in situ enabling appropriate data fusion. The broad range of spatio-temporal effects include infrastructural and human mobility, energy, bio-diversity, digital activity, urban management, art and socializing, robustness with regard to damage and noise or real-time monitoring of environmental changes. The proposed intelligent architectures will increase sustainability and viability in digitised urban environments by decreasing information transfer bandwidth by e.g, utilising 5G networks. The emergence of socio-cultural effect will create a cybernetic relationship with our dwellings and cities.

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EvoDynamic: A Framework for the Evolution of Generally Represented Dynamical Systems and Its Application to Criticality

Pontes-Filho

Lind

Yazidi

et al. 2020

Applications of Evolutionary Computation

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Dynamical systems possess a computational capacity that may be exploited in a reservoir computing paradigm. This paper presents a general representation of dynamical systems which is based on matrix multiplication. That is similar to how an artificial neural network (ANN) would be represented in a deep learning library and its computation would be faster because of the optimized matrix operations that such type of libraries have. Initially, we implement the simplest dynamical system, a cellular automaton. The mathematical fundamentals behind an ANN are maintained, but the weights of the connections and the activation function are adjusted to work as an update rule in the context of cellular automata. The advantages of such implementation are its usage on specialized and optimized deep learning libraries, the capabilities to generalize it to other types of networks and the possibility to evolve cellular automata and other dynamical systems in terms of connectivity, update and learning rules. Our implementation of cellular automata constitutes an initial step towards a more general framework for dynamical systems. Our objective is to evolve such systems to optimize their usage in reservoir computing and to model physical computing substrates. Furthermore, we present promising preliminary results toward the evolution of complex behavior and criticality using genetic algorithm in stochastic elementary cellular automata.

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Computational Matter: Evolving Computational Functions in Nanoscale Materials

Cited by 15 publications

References 69 publications

Evolution in Nanomaterio: The NASCENCE Project

Evolution in Nanomaterio: The NASCENCE Project

On Buildings that Compute. A Proposal

EvoDynamic: A Framework for the Evolution of Generally Represented Dynamical Systems and Its Application to Criticality

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