Hänsel, Gretel and the slime mould—how an external spatial memory aids navigation in complex environments

Smith-Ferguson, Jules; Reid, Chris; Latty, Tanya; Beekman, Madeleine

doi:10.1088/1361-6463/aa87df

Cited by 14 publications

(11 citation statements)

References 36 publications

(47 reference statements)

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“…When the plasmodium is placed in an environment with distributed nutrients, it develops a network of protoplasmic tubes with length equal to the distance between the sources of food [8]. While foraging and transporting nutrients throughout its protoplasmic body, plasmodium converges to the minimum path in a maze [9,10], calculates planar proximity graphs [11] as well as plane tessellations [12], discloses an early form of memory [13] and performs basic logic operations [8]. The plasmodium can be considered as a general purpose computer because it is capable of simulating the Kolmogorov-Uspensky machine [14,15], while in [16] through laboratory experiments it has demonstrated Boolean logic implementation.…”

Section: Logic Gates Implementation With Physarum Polycephalummentioning

confidence: 99%

Unconventional Bio-Inspired Model for Design of Logic Gates

Floros¹,

Tsakalos²,

Dourvas³

et al. 2020

Preprint

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During the last years, a well studied biological substrate, namely Physarum polycephalum, has been proven efficient on finding appropriate and efficient solutions in hard to solve complex mathematical problems. The plasmodium of P. polycephalum is a single-cell that serves as a prosperous biocomputational example. Consequently, it has been successfully utilized in the past to solve a variety of path problems in graphs and combinatorial problems. In this work, this interesting behaviour is mimicked by a robust unconventional computational model, drawing inspiration from the notion of Cellular and Learning Automata. Namely, we employ principles of Cellular Automata (CAs) enriched with learning capabilities to develop a robust computational model, able of modelling appropriately the aforementioned biological substrate and, thus, capturing its computational capabilities. CAs are very efficient in modelling biological systems and solving scientific problems, owing to their ability of incarnating essential properties of a system where global behaviour arises as an effect of simple components, interacting locally. The resulting computational tool, after combining CAs with learning capabilities, should be appropriate for modelling the behaviour of living organisms. Thus, the inherent abilities and computational characteristics of the proposed bio-inspired model are stressed towards the experimental verification of Physarum's ability to model Logic Gates, while trying to find minimal paths in properly configured mazes with food sources. The presented simulation results for various Logic Gates are found in good agreement, both qualitatively and quantitatively, with the corresponding experimental results, proving the efficacy of this unconventional bio-inspired model and providing useful insights for its enhanced usage in various computing applications.

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Section: Logic Gates Implementation With Physarum Polycephalummentioning

confidence: 99%

Unconventional Bio-Inspired Model for Design of Logic Gates

Floros¹,

Tsakalos²,

Dourvas³

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…Importantly, when Physarum was unable to use its external spatial memory, due to the entire environment being coated in extracellular slime, it was unable to navigate to the goal. Interestingly, the presence of extracellular slime only provides a benefit in environments in which the environment itself also provides information in the form of barriers, such as the Ushaped trap or environments that are similarly bounded (a dead end in a maze set up, for example; Smith-Ferguson, Reid, Latty, & Beekman, 2017). When the complexity of the environment increases, and many more options are available to the organism, the use of an external spatial memory no longer provides a benefit (Smith-Ferguson et al, 2017).…”

Section: Externalised Spatial Memorymentioning

confidence: 99%

Who needs a brain? Slime moulds, behavioural ecology and minimal cognition

Smith-Ferguson

Beekman

2019

Adaptive Behavior

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Although human decision making seems complex, there is evidence that many decisions are grounded in simple heuristics. Such heuristic models of decision making are widespread in nature. To understand how and why different forms of information processing evolve, it is insightful to study the minimal requirements for cognition. Here, we explore the minimally cognitive behaviour of the acellular slime mould, Physarum polycephalum, in order to discuss the ecological pressures that lead to the development of information processing mechanisms. We discuss evidence for memory, basic forms of learning and economically irrational choice in P. polycephalum. We compare P. polycephalum’s behaviour with a number of other non-neuronal organisms in order to question the evolutionary need for complex nervous systems to develop cognitive traits. By highlighting a few examples of common mechanisms, we conclude that all organisms contain the building blocks for more complex information processing. Returning the debate about cognition to the biological basics demystifies some of the confusion around the term ‘cognition’.

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“…In the last decade, there has been an increasing number of studies exploring the ability of Physarum to construct efficient networks (Nakagaki, Yamada & Tóth, ; Tero et al ., ; Reid & Beekman, ), make optimal foraging decisions (Latty & Beekman, , , , b , ; Reid et al ., , ), optimise nutrient intake (Dussutour et al ., ), habituate to unfavourable stimuli (Boisseau, Vogel & Dussutour, ), find its way out of mazes and traps using its external memory system (Reid et al ., ; Smith‐Ferguson et al ., ), and even transfer learned behaviour (Vogel & Dussutour, ). Most, if not all, of these studies relied on iterations of basically the same genetic individual to achieve their sample size.…”

Section: The Concept Of Biological Individualitymentioning

confidence: 99%

Can't see the colony for the bees: behavioural perspectives of biological individuality

Smith-Ferguson

Beekman

2019

Biological Reviews

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The question 'what is an individual' does not often arise in studies within the field of behavioural ecology. Generally behavioural ecologists do not think about what makes an individual because they tend to use intuitive working concepts of individuality. Rarely do they explicitly mention how individuality affects their experimental design and interpretation of results. By contrast, the concept of individuality continues to intrigue philosophers of biology. It is interesting that while philosophers of biology debate definitions of individuality, biologists generally use the concept of individuality every day without much thought. Here we review the philosophical approaches to defining biological individuality, and illustrate how the biological individuality concepts used by biologists are affected by their study question and choice of organism. We clarify the behavioural perspective of biological individuality by introducing the concept of the behavioural individual. The notion of the behavioural individual is particularly interesting when explored in less-conventional study organisms. By including less-conventional organisms, it becomes clear why the concept of biological individuality is usually intuitive in behavioural ecology.

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Hänsel, Gretel and the slime mould—how an external spatial memory aids navigation in complex environments

Abstract: View the article online for updates and enhancements.

Cited by 14 publications

References 36 publications

Unconventional Bio-Inspired Model for Design of Logic Gates

Unconventional Bio-Inspired Model for Design of Logic Gates

Who needs a brain? Slime moulds, behavioural ecology and minimal cognition

Can't see the colony for the bees: behavioural perspectives of biological individuality

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