Amoeba-Inspired Electronic Solution-Searching System and Its Application to Finding Walking Maneuver of a Multi-legged Robot

Saito, Kenta; Suefuji, Naoki; Kasai, Seiya; Aono, Masashi

doi:10.1109/ismvl.2018.00030

Cited by 9 publications

(15 citation statements)

References 9 publications

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“…A promising candidate of such a computing platform is an analogue electronic circuit. In fact, some authors have explored the use of the amoeba-inspired electronic circuits for tackling the constraint satisfaction problem [33], satisfiability problem [34], analogue-to-digital conversion [35] and finding walking manoeuvre of a multi-legged robot [36]. Such an approach to exploit physical parallelism may develop a novel analogue computing paradigm, providing powerful approximation methods for solving complex optimization problems appearing in a wide spectrum of real-world applications.…”

Section: Discussionmentioning

confidence: 99%

Remarkable problem-solving ability of unicellular amoeboid organism and its mechanism

et al. 2018

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Choosing a better move correctly and quickly is a fundamental skill of living organisms that corresponds to solving a computationally demanding problem. A unicellular plasmodium of Physarum polycephalum searches for a solution to the travelling salesman problem (TSP) by changing its shape to minimize the risk of being exposed to aversive light stimuli. In our previous studies, we reported the results on the eight-city TSP solution. In this study, we show that the time taken by plasmodium to find a reasonably high-quality TSP solution grows linearly as the problem size increases from four to eight. Interestingly, the quality of the solution does not degrade despite the explosive expansion of the search space. Formulating a computational model, we show that the linear-time solution can be achieved if the intrinsic dynamics could allocate intracellular resources to grow the plasmodium terminals with a constant rate, even while responding to the stimuli. These results may lead to the development of novel analogue computers enabling approximate solutions of complex optimization problems in linear time.

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Section: Discussionmentioning

confidence: 99%

Remarkable problem-solving ability of unicellular amoeboid organism and its mechanism

et al. 2018

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“…Recent studies by S. Kasai and M. Aono have proven the utility of a simple, bioinspired computing device in the control of the autonomous robot. 163 This study was inspired by remarkable features of a primitive ameboid organism -slime mould Physarum polycefalum, [164][165] which is a model organism in unconventional computing studies. 166 The Physarum pseudopods are sensitive to light and other stimuli (e.g., food sources of chemical repellants) and change their geometry upon stimulation (Figure 17a).…”

Section: Towards Autonomous Roboticsmentioning

confidence: 99%

“…A basic concept of conversion of ameboid's response to stimulation to system control parameters (a), its implementation in a classical electronic circuit (b), the electrical signal recorded during the search for the solution of a leg movement (c) and an autonomous walking robot with an ameboid-inspired controller onboard (d). Adapted from Ref 163. with permission.…”

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confidence: 99%

Towards synthetic neural networks: can artificial electrochemical neurons be coupled with artificial memristive synapses?

Wlaźlak

Przyczyna

Gutiérrez

et al. 2020

Jpn. J. Appl. Phys.

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The enormous amount of data generated nowadays worldwide is increasingly triggering the search for unconventional and more efficient ways of processing and classifying information, eventually able to transcend the conventional von-Neumann-Turing computational central dogma. It is, therefore, greatly appealing to draw inspiration from less conventional but computationally more powerful systems such as the neural architecture of the human brain.This neuromorphic route has the potential to become one of the most influential and long-lasting paradigms in the field of unconventional computing. The material-based workhorse for current hardware platforms is largely based on standard CMOS technologies, intrinsically following the above mentioned von-Neumann-Turing prescription; we do know, however, that the brain hardware operates in a massively parallel way through a densely interconnected physical network of neurons. This requires challenging the intrinsic definition of the single units and the architecture of computing machines. Memristive and the recently proposed memfractive systems have been shown to display basic features of neural systems such as synaptic-like plasticity and memory features, so that they may offer a diverse playground to implement synaptic connections. Their combination with reservoir computing approaches can further increase their versatility since reservoir networks do not require extra optimization of internal connections. In this review, we address various material-based strategies of implementing unconventional computing hardware: (i) electrochemical oscillators based on liquid metals and (ii) mem-devices exploiting Schottky barrier modulation in polycrystalline and disordered structures made of oxide or perovskite-type semiconductors. Both items (i) and (ii) build the two pillars of neuromimetic computing devices, which we will denote as synthetic neural networks. We complement the more experimental aspects of the review with an overview of few atomistic and phenomenological modelling approaches of memdevices as well as of reservoir computing networks. We expect that the current review will be of great interest for scientists aiming at bridging unconventional computing strategies with specific materials-based platforms.

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“…We focus on a living amoeboid organism that performs trialand-error behaviour to survive efficiently and resiliently in a harsh environment, deforming its gel-like body 30,31 . Here, we demonstrate, as a proof of concept, an analogue electronic computing system called an "electronic amoeba" 32,33 , inspired by the food search and risk avoidance behaviour of a single-celled amoeboid organism, Physarum polycephalum 30,31,[34][35][36][37][38][39] . In the electronic amoeba, an arbitrary TSP instance can be mapped on the resistor network of a crossbar structure shown in Fig.…”

Section: Scientific Reportsmentioning

confidence: 99%

Amoeba-inspired analog electronic computing system integrating resistance crossbar for solving the travelling salesman problem

Saito

Aono²,

Kasai

2020

Sci Rep

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Combinatorial optimization to search for the best solution across a vast number of legal candidates requires the development of a domain-specific computing architecture that can exploit the computational power of physical processes, as conventional general-purpose computers are not powerful enough. Recently, Ising machines that execute quantum annealing or related mechanisms for rapid search have attracted attention. These machines, however, are hard to map application problems into their architecture, and often converge even at an illegal candidate. Here, we demonstrate an analogue electronic computing system for solving the travelling salesman problem, which mimics efficient foraging behaviour of an amoeboid organism by the spontaneous dynamics of an electric current in its core and enables a high problem-mapping flexibility and resilience using a resistance crossbar circuit. The system has high application potential, as it can determine a high-quality legal solution in a time that grows proportionally to the problem size without suffering from the weaknesses of Ising machines.

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Amoeba-Inspired Electronic Solution-Searching System and Its Application to Finding Walking Maneuver of a Multi-legged Robot

Cited by 9 publications

References 9 publications

Remarkable problem-solving ability of unicellular amoeboid organism and its mechanism

Remarkable problem-solving ability of unicellular amoeboid organism and its mechanism

Towards synthetic neural networks: can artificial electrochemical neurons be coupled with artificial memristive synapses?

Amoeba-inspired analog electronic computing system integrating resistance crossbar for solving the travelling salesman problem

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