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Towards a metabolic robot controller
... Additionally, they emphasized the importance of boundaries as defense mechanisms of autocatalytic sets located inside cells. (Ziegler et al., 1998) proposed a metabolic robot controller based on different chemicals reacting and forming autocatalytic cycles. ...
... First of all, the demand for spontaneous, independent of external signals activity is frequently neglected. For example, simulations of metabolism in unicellular organisms were used to design artificial agents capable of avoiding obstacles (Ojala, 1998) and seeking for light (Ziegler, Dittrich, & Banzhaf, 1998). However, an external sensory input is needed to maintain activity of these agents. ...
Various organisms share certain basic rules for a searching behavior. We hypothesize that these rules may emerge from basic properties of nonlinear systems as a whole, rather then being evolved from a scratch gradually. In order to support this hypothesis, we have developed a virtual agent that consists of three simple nonlinear oscillators. These oscillators are driven by an internal noise, which results in phase transitions in their activity. External stimuli modify the activity via sensors and food consumption. The interaction among the activity of oscillators and external influences give rise to an emergence of searching rules that are similar to those shared by various organisms, thus favoring this hypothesis. The hypothesis can be verified further by investigating various types of nonlinear systems in different environments.
... First of all, the demand for spontaneous, independent of an external signals activity is frequently neglected. For example, simulations of metabolism in unicellular organisms were used to design artificial agents capable of avoiding obstacles (Ojala, 1998) and seeking for light (Ziegler, Dittrich, and Banzhaf, 1998). However, an external sensory input is needed to maintain an activity of these agents. ...
Various organisms share in common certain basic rules for a searching behavior. We hypothesize that these rules may emerge from basic properties of non-linear systems as a whole, rather then being evolved from a scratch gradually. In order to support this hypothesis, we have developed a virtual agent that consists of three simple central pattern generators (CPG). These CPGs are driven by an internal noise, which results in phase transitions in their activity. External stimuli modify the activity via sensors and food consumption. The interaction among the activity of CPGs and external influences give rise to an emergence of searching rules that are similar to those shared by various organisms, thus favoring the above hypothesis. The hypothesis could be verified further by investigating various types of non- linear systems in different environments. Also, such an investigation may answer the question: how simple could be an underlying dynamic system to ensure viability of an agent in a given environment? To what extent adaptive abilities of living being are constrained and steered by dynamic laws of non-linear systems?
... On the other hand, researchers link theory with practical applications by taking advantage of the similarity between ACs and other complex dynamic systems (e.g. [2,7,8,15,20]). A natural definition for many tasks is in terms of elementary interactions to be performed frequently. But what " language " should be used to encode a given task? ...
Using the framework of artificial chemistries (ACs) an automated theorem prover (ATP) is constructed. Though it is an application
of its own, in the context of ACs automated theorem proving can serve a second purpose. In this paper, we present a resolution-based
AC named RESAC. Once converted to the first-order predicate calculus a problem straightly fits to this non-deterministic AC model. The calculus
therefore provides a general and intuitive language for ”programming” RESAC. The fixed implicit interaction scheme and predefined structure of the objects is advantageous and helps to predict the system’s
dynamics. Furthermore, the versatility of the methodology is demonstrated by implementing the Adleman problem. An analysis
of the dynamic behavior is performed delivering insight into the synthesis of non-deterministic emerging processes. This analysis
include a discussion of some general AC parameters.
... A likely early application niche for the principles outlined in the previous section is the area of autonomous micro robotic devices. With the quest for robots at a scale of a cubic millimetre and below molecular controllers become increasingly attractive [23, 24] , and initial steps towards implementation are under- way [25]. Coherent perception-action under real-time constraints with severely limited computational resources does not allow for the inefficiency of a virtual machine that abstracts physics away. ...
Achieving real-time response to complex, ambiguous, high-bandwidth data is impractical with conventional programming. Only the narrow class of compressible input-output maps can be specified with feasibly sized programs. Present computing concepts enforce formalisms that are arbitrary from the perspective of the physics underlying their implementation. Efficient physical realizations are embarrassed by the need to implement the rigidly specified instructions requisite for programmable systems. The conventional paradigm of erecting strong constraints and potential barriers that narrowly prescribe structure and precisely control system state needs to be complemented with a new approach that relinquishes detailed control and reckons with autonomous building blocks. Brittle prescriptive control will need to be replaced with resilient self-organisation to approach the robustness and efficency afforded by natural systems. Structure-function self-consistency will be key to the spontaneous generation of functional architectures that can harness novel molecular and nano materials in an effective way for increased computational power.
... The second domain is coherent perception-action under real-time constraints in microrobots. Molecular technology may in the future be able to deliver the high integration density and low power consumption that is required to narrow the gap between simple biological organisms and present artificial devices in size, performance, and adaptability [378, 379, 380]. Finally, it is worth pointing out that integrating new devices into existing technology can be expected to be slow. ...
Molecular materials are endowed with unique properties of unrivaled potential for high density integration of computing systems. Present applications of molecules range from organic semiconductor materials for low-cost circuits to genetically modified proteins for commercial imaging equipment. To fully realize the potential of molecules in computation, information processing concepts that relinquish narrow prescriptive control over elementary structures and functions are needed, and self-organizing architectures have to be developed. Investigations into qualitatively new concepts of information processing are underway in the areas of reaction-diffusion computing, self-assembly computing, and conformation-based computing. Molecular computing is best considered not as a competitor for conventional computing, but as an opportunity for new applications. Microrobotics and bioimmersive computing are among the domains likely to benefit from advances in molecular computing. Progress will depend on both novel computing concepts and innovations in materials. This article reviews current directions in the use of bulk and single molecules for information processing.
... Das Bild der Chemie mit ihren vielen zeitgleich stattfindenden Reaktionen dient der ersten Gruppe von Systemen als Metapher für parallele Algorithmen und großen dezentralen Datenstrukturen ( [27,114,120]). ...
Der genetischen Programmierung (GP) liegt zumeist die Annahme zugrunde, dass die Individuen eine evolvierte, wohldefinierte Struktur haben und ihre Ausführung deterministisch erfolgt. Diese Annahme hat ihren Ursprung nicht beim methodischen Vorbild, der natürlichen Evolution, sondern ist ein bewusstes oder unbewusstes Erbe der Umgebung, in der die Evolution nachgebildet wird - der von-Neumann-Architektur.
John von Neumann hat mit der nach ihm benannten von-Neumann-Architektur weit mehr in der Informatik beeinflusst als das Gebiet der Rechnerarchitekturen. Daher ist sein Einfluss auf die Evolution von Algorithmen mittels genetischer Programmierung nicht verwunderlich, auch wenn die von-Neumann-Architektur wenig gemein mit den in der Natur evolvierten Systemen hat. In den letzten Jahren entstanden eine ganze Reihe von Konzepten und theoretischen Modellen, die nur noch wenig Anleihen bei von Neumanns Rechnerarchitektur machen und die in ihren Eigenschaften stärker natürlichen Systemen ähneln. Die Fähigkeit dieser Systeme, Berechnungen durchzuführen, entsteht erst durch die Interaktion ihrer parallel agierenden, nichtdeterministischen und dezentral organisierten Komponenten. Die Fähigkeit emergiert.
Über die Evolution von Algorithmen für solche Systeme jenseits der von-Neumann-Architektur weiß man noch vergleichsweise wenig. Die vorliegende Arbeit nimmt sich dieser Fragestellung an und bedient sich hierbei der algorithmischen Chemie, einer künstlichen Chemie, die bei vereinfachter Betrachtungsweise aus einem veränderten Programmzeigerverhalten in der von-Neumann-Architektur resultiert. Reaktionen, eine Variante einfacher Instruktionen, werden hierbei in zufälliger Reihenfolge gezogen und ausgeführt. Sie interagieren miteinander, indem sie Produkte anderer Reaktionen verwenden und das Ergebnis ihrer Transformation, gespeichert in sogenannten Molekülen, anderen Reaktionen zur Verfügung stellen.
Zur experimentellen Auswertung dieses nichtdeterministischen Systems wird die sequenzielle Parameteroptimierung um ein Verfahren zur Verteilung eines Experimentbudgets erweitert. Das systematische Design der Experimente und ihre anschließende Analyse ermöglichen es, generalisierte Erkenntnisse über das Systemverhalten jenseits konkreter Parametrisierungen zu gewinnen. Im Fall der genetischen Programmierung einer algorithmischen Chemie führen die gewonnenen Erkenntnisse zu einer Neuentwicklung des Rekombinationsoperators nach dem Vorbild homologer Rekombinationsoperationen und damit zu einer weiteren Verbesserung der Systemperformance.
Es zeigt sich, dass die für ein zielgerichtetes Verhalten einer algorithmischen Chemie notwendigen Reaktionsschemata mittels genetischer Programmierung erlernt werden können. Für gängige Problemstellungen aus dem Bereich der genetischen Programmierung werden Lösungen gefunden, die in ihrer Güte mit denen anderer GP-Varianten und maschineller Lernverfahren vergleichbar sind. Die evolvierten Lösungen fallen dabei deutlich kompakter bezüglich der Datenflusshöhe und der Anzahl benötigter Operationen aus, als in dem zum Vergleich herangezogenen linearen GP-System.
... The hormone system is equivalent to an arti cial chemistry without reactions, so that hormones just carry information and do not process it. Adamatzki et al. [1,2] and we [145] used excitable lattices and simpli ed enzyme-substrate kinetics, respectively, to control real mobile robots. ...
This article reviews the growing body of scientific work in artificial chemistry. First, common motivations and fundamental concepts are introduced. Second, current research activities are discussed along three application dimensions: modeling, information processing, and optimization. Finally, common phenomena among the different systems are summarized. It is argued here that artificial chemistries are "the right stuff" for the study of prebiotic and biochemical evolution, and they provide a productive framework for questions regarding the origin and evolution of organizations in general. Furthermore, artificial chemistries have a broad application range of practical problems, as shown in this review.
... ility to form appropriate sensory, computational, and effector structures in resposne to direct interaction with the environment. Whether it is possible to replicate this plasticity on a virtual level in a formal computational model for execution on digital machine is unclear. Undoubtedly, simulation is a powerful tool for studying design concepts. Ziegler et al. (1998) were among the first to consider the biochemical metaphor for robot control and employed simulation to evolve highly abstracted chemical controllers. More recently Adamatzky et al. (2004) have taken steps towards the realisation of a chemically controlled robot based on reaction diffusion computing with an excitable chemical medium (cf. ...
At present there exists a large gap in size, performance, adaptability and robustness between natural and artificial information processors for performing coherent perception-action tasks under real-time constraints. Even the simplest organisms have an enviable capability of coping with an unknown dynamic environment. Robots, in contrast, are still clumsy if confronted with such complexity. This paper presents a bio-hybrid architecture developed for exploring an alternate approach to the control of autonomous robots. Circuits prepared from amoeboid plasmodia of the slime mold Physarum polycephalum are interfaced with an omnidirectional hexapod robot. Sensory signals from the macro-physical environment of the robot are transduced to cellular scale and processed using the unique micro-physical features of intracellular information processing. Conversely, the response form the cellular computation is amplified to yield a macroscopic output action in the environment mediated through the robot's actuators.
The paper gives probably the first ever systematic discussion on how wave processes in reaction-diffusion and excitable homogeneous
media can be efficiently used to solve a wide range of problems in robot navigation. Three possible applications of chemical
controllers are considered: (i) object following, (ii) optimal path finding, and (iii) universal control. The various implementations
of controllers discussed here include: Belousov-Zhabotinsky chemical processors, families of excitable lattices, and self-localised
excitations. We present some results from a simulation of robot control using excitable lattices, and find the results encouraging
for our planned construction of a chemically controlled robot.
This article demonstrates a new method of programming artificial chemistries. It uses the emerging capabilities of the system's dynamics for information-processing purposes. By evolution of metabolisms that act as control programs for a small robot one achieves the adaptation of the internal metabolic pathways as well as the selection of the most relevant available exteroceptors. The underlying artificial chemistry evolves efficient information-processing pathways with most benefit for the desired task, robot navigation. The results show certain relations to such biological systems as motile bacteria.
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