Self-organisation and living systems: Is DNA an ‘artificial intelligence’?

1989 ◽  
Vol 29 (4) ◽  
pp. 223-229 ◽  
Author(s):  
D.H. Adams ◽  
M.R.C. External Scientific Staff
Keyword(s):  
Artificial Intelligence ◽  
Living Systems ◽  
Self Organisation

scholarly journals On Crashing the Barrier of Meaning in Artificial Intelligence

AI Magazine ◽  
2020 ◽  
Vol 41 (2) ◽  
pp. 86-92 ◽  
Author(s):  
Melanie Mitchell
Keyword(s):  
Artificial Intelligence ◽  
Information Theory ◽  
Animal Behavior ◽  
Developmental Psychology ◽  
Living Systems ◽  
Santa Fe ◽  
Dawn Song ◽  
Artificial Intelligence Systems

In 1986, the mathematician and philosopher Gian-Carlo Rota wrote, “I wonder whether or when artificial intelligence will ever crash the barrier of meaning” (Rota 1986). Here, the phrase “barrier of meaning” refers to a belief about humans versus machines: Humans are able to actually understand the situations they encounter, whereas even the most advanced of today’s artificial intelligence systems do not yet have a humanlike understanding of the concepts that we are trying to teach them. This lack of understanding may underlie current limitations on the generality and reliability of modern artificial intelligence systems. In October 2018, the Santa Fe Institute held a three-day workshop, organized by Barbara Grosz, Dawn Song, and myself, called Artificial Intelligence and the Barrier of Meaning. Thirty participants from a diverse set of disciplines — artificial intelligence, robotics, cognitive and developmental psychology, animal behavior, information theory, and philosophy, among others — met to discuss questions related to the notion of understanding in living systems and the prospect for such understanding in machines. In the hope that the results of the workshop will be useful to the broader community, this article summarizes the main themes of discussion and highlights some of the ideas developed at the workshop.

Autonomy and Openness in Human and Machine Systems: Participatory Sense-Making and Artificial Minds

2021 ◽  
pp. 1-21
Author(s):  
Robin L. Zebrowski ◽  
Eli B. McGraw
Keyword(s):  
Artificial Intelligence ◽  
Social Cognition ◽  
Autonomous System ◽  
Living Systems ◽  
Sense Making ◽  
Cognitive Systems ◽  
Social Forms ◽  
Theoretical Approaches ◽  
Machine Systems ◽  
Level Of Analysis

Within artificial intelligence (AI) and machine consciousness research, social cognition as a whole is often ignored. When it is addressed, it is often thought of as one application of more traditional forms of cognition. However, while theoretical approaches to AI have been fairly stagnant in recent years, social cognition research has progressed in productive new ways, specifically through enactive approaches. Using participatory sense-making (PSM) as an approach, we rethink conceptions of autonomy and openness in AI and enactivism, shifting the focus away from living systems to allow incorporation of artificial systems into social forms of sense-making. PSM provides an entire level of analysis through an overlooked autonomous system produced via social interaction that can be both measured and modeled in order to instantiate and examine more robust artificial cognitive systems.

Artificial Intelligence and Automatic Self-Organisation

2016 ◽  
pp. 153-158 ◽  
Author(s):  
Stephan Oelker ◽  
Marco Lewandowski ◽  
Klaus-Dieter Thoben ◽  
Dirk Reinhold ◽  
Ingo Schlalos
Keyword(s):  
Artificial Intelligence ◽  
Self Organisation

scholarly journals Emergence of Organisms

Entropy ◽  
2020 ◽  
Vol 22 (10) ◽  
pp. 1163
Author(s):  
Andrea Roli ◽  
Stuart A. Kauffman
Keyword(s):  
Artificial Intelligence ◽  
Adaptive Behavior ◽  
Artificial Life ◽  
Living Systems ◽  
Self Sufficiency ◽  
Evolution Of Life ◽  
High Level ◽  
Hostile Environments

Since early cybernetics studies by Wiener, Pask, and Ashby, the properties of living systems are subject to deep investigations. The goals of this endeavour are both understanding and building: abstract models and general principles are sought for describing organisms, their dynamics and their ability to produce adaptive behavior. This research has achieved prominent results in fields such as artificial intelligence and artificial life. For example, today we have robots capable of exploring hostile environments with high level of self-sufficiency, planning capabilities and able to learn. Nevertheless, the discrepancy between the emergence and evolution of life and artificial systems is still huge. In this paper, we identify the fundamental elements that characterize the evolution of the biosphere and open-ended evolution, and we illustrate their implications for the evolution of artificial systems. Subsequently, we discuss the most relevant issues and questions that this viewpoint poses both for biological and artificial systems.

scholarly journals Optical nanoscopy

2020 ◽  
Vol 43 (8) ◽  
pp. 385-455
Author(s):  
A. Diaspro ◽  
P. Bianchini
Keyword(s):  
Artificial Intelligence ◽  
Spatial Resolution ◽  
Scanning Probe Microscopy ◽  
Molecular Level ◽  
Super Resolution ◽  
Optical Microscope ◽  
Scanning Probe ◽  
Living Systems ◽  
Starting Point ◽  
Basic Concepts

Abstract This article deals with the developments of optical microscopy towards nanoscopy. Basic concepts of the methods implemented to obtain spatial super-resolution are described, along with concepts related to the study of biological systems at the molecular level. Fluorescence as a mechanism of contrast and spatial resolution will be the starting point to developing a multi-messenger optical microscope tunable down to the nanoscale in living systems. Moreover, the integration of optical nanoscopy with scanning probe microscopy and the charming possibility of using artificial intelligence approaches will be shortly outlined.

Turing, Searle, and the Wizard of Oz

2010 ◽  
Vol 14 (2) ◽  
pp. 88-102
Author(s):  
S. D. Noam Cook ◽  
Keyword(s):  
Artificial Intelligence ◽  
20Th Century ◽  
Artificial Life ◽  
The Other ◽  
Living Systems ◽  
Wizard Of Oz ◽  
Central Elements ◽  
Future Technologies

Since the middle of the 20th century there has been a significant debate about the attribution of capacities of living systems, particularly humans, to technological artefacts, especially computers—from Turing’s opening gambit, to subsequent considerations of artificial intelligence, to recent claims about artificial life. Some now argue that the capacities of future technologies will ultimately make it impossible to draw any meaningful distinctions between humans and machines. Such issues center on what sense, if any, it makes to claim that gadgets can actually think, feel, act, live, etc. I outline this debate and offer a critique of its persistent polarization. I characterize two of the debate’s major camps (associated roughly with Turing and Searle); argue that the debate’s structure (including key assumptions inherent to each camp) precludes resolution; and, contend that some central clashes within the debate actually stem from an inadequately drawn distinction between claims about the capacities of artifacts and claims about the proper criteria for assessing such attributions. I offer a different perspective in which I: challenge some central elements of the debate that contribute to its perennially irresolvable state; hold that the debate needs to be placed more squarely in sync with how we in fact treat the attribution of such capacities to humans themselves; and, offer (unlike the other two camps) a foothold for making moral assessments of such proposed technologies.

Self-organisation of living systems towards criticality at the edge of chaos

Biosystems ◽  
1994 ◽  
Vol 33 (1) ◽  
pp. 17-24 ◽  
Author(s):  
Keisuke Ito ◽  
Yukio-Pegio Gunji
Keyword(s):  
Living Systems ◽  
Edge Of Chaos ◽  
Self Organisation

scholarly journals Kinematic self-replication in reconfigurable organisms

2021 ◽  
Vol 118 (49) ◽  
pp. e2112672118
Author(s):  
Sam Kriegman ◽  
Douglas Blackiston ◽  
Michael Levin ◽  
Josh Bongard
Keyword(s):  
Artificial Intelligence ◽  
Phenotypic Plasticity ◽  
Genetic Engineering ◽  
Side Effect ◽  
The Body ◽  
Living Systems ◽  
Wild Type ◽  
Artificial Intelligence Methods ◽  
Dissociated Cells ◽  
Self Replication

All living systems perpetuate themselves via growth in or on the body, followed by splitting, budding, or birth. We find that synthetic multicellular assemblies can also replicate kinematically by moving and compressing dissociated cells in their environment into functional self-copies. This form of perpetuation, previously unseen in any organism, arises spontaneously over days rather than evolving over millennia. We also show how artificial intelligence methods can design assemblies that postpone loss of replicative ability and perform useful work as a side effect of replication. This suggests other unique and useful phenotypes can be rapidly reached from wild-type organisms without selection or genetic engineering, thereby broadening our understanding of the conditions under which replication arises, phenotypic plasticity, and how useful replicative machines may be realized.

scholarly journals Cognition, Communication, and Co-operation in Living Systems. Biosemiosis in the Context of Self-organisation

1970 ◽  
Vol 3 (2) ◽  
pp. 75-85
Author(s):  
Wolfgang Hofkirchner ◽  
Günther Ellersdorfer
Keyword(s):  
Living Systems ◽  
Unified Theory ◽  
Evolutionary Systems ◽  
Scientific Disciplines ◽  
Different Types ◽  
Individual Branch ◽  
Common Concept ◽  
Theory Of Information ◽  
Self Organisation ◽  
The Relationship

In the perspective of an as yet-to-be-developed Unified Theory of Information as part of an as yet-to-be-developed theory of evolutionary systems semiosis plausibly coincides with self-organisation. A concept of sign processes that is flexible enough to perform two functions as follows is everything that is required for this framework. It must relate to the most various manifestations of sign processes, thus enabling a variety of scientific disciplines to use a common concept where it seems appropriate; at the same time, it must be precise enough to fit the unique requirements of any individual branch of science dealing with a concrete manifestation. Different types of sign processes have to be related to, if not derived from (albeit in a nonformal way), different types of self-organisation. The paper illustrates how the relationship between the genus proximum of semiosis in self-organising systems and the differentia specifica of semiosis in biota may be approached.

Living architecture: workshop report from the European Conference on Artificial Life, Lyon, France, 4 September 2017

2018 ◽  
Vol 26 (2) ◽  
pp. 85-88 ◽  
Author(s):  
Martin M Hanczyc ◽  
Barbara Imhof ◽  
Andrew Adamatzky
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Built Environment ◽  
Artificial Life ◽  
Feedback Loops ◽  
Living Systems ◽  
Workshop Report ◽  
European Conference ◽  
Open Questions ◽  
The Future

Imagine evolving swarms of robots interacting and by doing so reshaping and cultivating our habitat. This habitat could be here on Earth, on a distant planet or moon, or within a self-contained spacecraft. What would these robots look like and made of what type of material? What kind of information, hardware or software? What are the architectural necessities? There are many open questions when trying to envision the future of architecture; but, in this particular workshop, the goal was not only to imagine the future but also to create it. With this particular goal in mind, the Living Architecture workshop at European Conference on Artificial Life (ECAL) 2017 brought together practitioners from the sciences and architecture to share ideas and technologies to examine possible paths forward. Living Architecture is a specific substantiation of the broader notion of Living Technology where living systems or artificial systems with life-like properties are developed towards technological applications. In Living Architecture, objects designed in the built environment would contain living systems as part of their functionality (such as bioreactors for energy) or artificial distributed systems with feedback loops (such as neural networks or artificial intelligence). In this way, Living Architecture represents a congruence in functionality and form between living systems, technology and architecture.

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