Dynamical properties and path dependence in a gene-network model of cell differentiation

Braccini, Michele; Roli, Andrea; Villani, Marco; Serra, Roberto

doi:10.1007/s00500-020-05354-0

Cited by 6 publications

(7 citation statements)

References 48 publications

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“…Finally, in light of the great complexities posed by the path-dependent nature of the online adaptation process [ 20 , 48 , 49 ], we conclude that a mechanism such as the one we have introduced might be an effective tool for tuning artificial systems to the specific environment in which they have to operate. As a futuristic application, we imagine the construction of miniaturized robots that can accomplish missions precluded to humans, such as recovering polluted environments.…”

Section: Discussionmentioning

confidence: 99%

“…Since their inception as an abstract model of gene regulatory networks [ 14 ], Boolean networks (BNs) have been the subject of a wealth of works investigating their computational and dynamical properties. Notably, BNs have demonstrated their ability to effectively capture significant biological phenomena, such as cell differentiation [ 15 , 16 , 17 , 18 , 19 , 20 , 21 ]. Evidence of an edge provided by critical Boolean networks has been demonstrated in classification, filtering and control tasks, just to mention some examples.…”

Section: Introductionmentioning

confidence: 99%

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On the Criticality of Adaptive Boolean Network Robots

Braccini

Roli

Barbieri

et al. 2022

Entropy

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Systems poised at a dynamical critical regime, between order and disorder, have been shown capable of exhibiting complex dynamics that balance robustness to external perturbations and rich repertoires of responses to inputs. This property has been exploited in artificial network classifiers, and preliminary results have also been attained in the context of robots controlled by Boolean networks. In this work, we investigate the role of dynamical criticality in robots undergoing online adaptation, i.e., robots that adapt some of their internal parameters to improve a performance metric over time during their activity. We study the behavior of robots controlled by random Boolean networks, which are either adapted in their coupling with robot sensors and actuators or in their structure or both. We observe that robots controlled by critical random Boolean networks have higher average and maximum performance than that of robots controlled by ordered and disordered nets. Notably, in general, adaptation by change of couplings produces robots with slightly higher performance than those adapted by changing their structure. Moreover, we observe that when adapted in their structure, ordered networks tend to move to the critical dynamical regime. These results provide further support to the conjecture that critical regimes favor adaptation and indicate the advantage of calibrating robot control systems at dynamical critical states.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

On the Criticality of Adaptive Boolean Network Robots

Braccini

Roli

Barbieri

et al. 2022

Entropy

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“…The basic steps defining adaptation strategy 1 and 3 are actually the same as those used in the online adaptation mechanism proposed in [34]. See Figure 3.…”

Section: Adaptive Mechanismsmentioning

confidence: 99%

Sensory–Motor Loop Adaptation in Boolean Network Robots

Braccini,

Gardinazzi,

Roli

et al. 2024

Sensors

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Recent technological advances have made it possible to produce tiny robots equipped with simple sensors and effectors. Micro-robots are particularly suitable for scenarios such as exploration of hostile environments, and emergency intervention, e.g., in areas subject to earthquakes or fires. A crucial desirable feature of such a robot is the capability of adapting to the specific environment in which it has to operate. Given the limited computational capabilities of a micro-robot, this property cannot be achieved by complicated software but it rather should come from the flexibility of simple control mechanisms, such as the sensory–motor loop. In this work, we explore the possibility of equipping simple robots controlled by Boolean networks with the capability of modulating their sensory–motor loop such that their behavior adapts to the incumbent environmental conditions. This study builds upon the cybernetic concept of homeostasis, which is the property of maintaining essential parameters inside vital ranges, and analyzes the performance of adaptive mechanisms intervening in the sensory–motor loop. In particular, we focus on the possibility of maneuvering the robot’s effectors such that both their connections to network nodes and environmental features can be adapted. As the actions the robot takes have a feedback effect to its sensors mediated by the environment, this mechanism makes it possible to tune the sensory–motor loop, which, in turn, determines the robot’s behavior. We study this general setting in simulation and assess to what extent this mechanism can sustain the homeostasis of the robot. Our results show that controllers made of random Boolean networks in critical and chaotic regimes can be tuned such that their homeostasis in different environments is kept. This outcome is a step towards the design and deployment of controllers for micro-robots able to adapt to different environments.

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“…This special issue includes seven peer-reviewed articles about synthetic biology, whose aim is to develop formal models for biological-like phenomena, specially in the context of molecular logic (Djordević and Silva 2019;Nemati and Torres 2020;Santiago et al 2020;Braccini et al 2020;Moreira et al 2020;Tavares et al 2021;Veloz and Flores 2021). Molecular logic focuses on understanding logical and operational aspects on molecules and their interactions, providing a fruitful conceptual crossover between chemistry and computation with unsuspected applications.…”

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confidence: 99%

“…The aim of MLSCB18 was harnessing logical and algebraic methods for modeling and verifying systems on the interaction of Nature and Computation, around two main themes, which can also serve to split the list of articles published in this special issue: The development of biological computation models and devices (Djordević and Silva 2019;Braccini et al 2020;Tavares et al 2021;Veloz and Flores 2021), and the application of new computing paradigms to the design of biological systems (Nemati and Torres 2020;Santiago et al 2020;Moreira et al 2020).…”

mentioning

confidence: 99%