1,778 research outputs found
Towards Autopoietic Computing
A key challenge in modern computing is to develop systems that address
complex, dynamic problems in a scalable and efficient way, because the
increasing complexity of software makes designing and maintaining efficient and
flexible systems increasingly difficult. Biological systems are thought to
possess robust, scalable processing paradigms that can automatically manage
complex, dynamic problem spaces, possessing several properties that may be
useful in computer systems. The biological properties of self-organisation,
self-replication, self-management, and scalability are addressed in an
interesting way by autopoiesis, a descriptive theory of the cell founded on the
concept of a system's circular organisation to define its boundary with its
environment. In this paper, therefore, we review the main concepts of
autopoiesis and then discuss how they could be related to fundamental concepts
and theories of computation. The paper is conceptual in nature and the emphasis
is on the review of other people's work in this area as part of a longer-term
strategy to develop a formal theory of autopoietic computing.Comment: 10 Pages, 3 figure
Chemical communication between synthetic and natural cells: a possible experimental design
The bottom-up construction of synthetic cells is one of the most intriguing
and interesting research arenas in synthetic biology. Synthetic cells are built
by encapsulating biomolecules inside lipid vesicles (liposomes), allowing the
synthesis of one or more functional proteins. Thanks to the in situ synthesized
proteins, synthetic cells become able to perform several biomolecular
functions, which can be exploited for a large variety of applications. This
paves the way to several advanced uses of synthetic cells in basic science and
biotechnology, thanks to their versatility, modularity, biocompatibility, and
programmability. In the previous WIVACE (2012) we presented the
state-of-the-art of semi-synthetic minimal cell (SSMC) technology and
introduced, for the first time, the idea of chemical communication between
synthetic cells and natural cells. The development of a proper synthetic
communication protocol should be seen as a tool for the nascent field of
bio/chemical-based Information and Communication Technologies (bio-chem-ICTs)
and ultimately aimed at building soft-wet-micro-robots. In this contribution
(WIVACE, 2013) we present a blueprint for realizing this project, and show some
preliminary experimental results. We firstly discuss how our research goal
(based on the natural capabilities of biological systems to manipulate chemical
signals) finds a proper place in the current scientific and technological
contexts. Then, we shortly comment on the experimental approaches from the
viewpoints of (i) synthetic cell construction, and (ii) bioengineering of
microorganisms, providing up-to-date results from our laboratory. Finally, we
shortly discuss how autopoiesis can be used as a theoretical framework for
defining synthetic minimal life, minimal cognition, and as bridge between
synthetic biology and artificial intelligence.Comment: In Proceedings Wivace 2013, arXiv:1309.712
EMERGING THE EMERGENCE SOCIOLOGY: The Philosophical Framework of Agent-Based Social Studies
The structuration theory originally provided by Anthony Giddens and the advance improvement of the theory has been trying to solve the dilemma came up in the epistemological aspects of the social sciences and humanity. Social scientists apparently have to choose whether they are too sociological or too psychological. Nonetheless, in the works of the classical sociologist, Emile Durkheim, this thing has been stated long time ago. The usage of some models to construct the bottom-up theories has followed the vast of computational technology. This model is well known as the agent based modeling. This paper is giving a philosophical perspective of the agent-based social sciences, as the sociology to cope the emergent factors coming up in the sociological analysis. The framework is made by using the artificial neural network model to show how the emergent phenomena came from the complex system. Understanding the society has self-organizing (autopoietic) properties, the Kohonenâs self-organizing map is used in the paper. By the simulation examples, it can be seen obviously that the emergent phenomena in social system are seen by the sociologist apart from the qualitative framework on the atomistic sociology. In the end of the paper, it is clear that the emergence sociology is needed for sharpening the sociological analysis in the emergence sociology
Enaction-Based Artificial Intelligence: Toward Coevolution with Humans in the Loop
This article deals with the links between the enaction paradigm and
artificial intelligence. Enaction is considered a metaphor for artificial
intelligence, as a number of the notions which it deals with are deemed
incompatible with the phenomenal field of the virtual. After explaining this
stance, we shall review previous works regarding this issue in terms of
artifical life and robotics. We shall focus on the lack of recognition of
co-evolution at the heart of these approaches. We propose to explicitly
integrate the evolution of the environment into our approach in order to refine
the ontogenesis of the artificial system, and to compare it with the enaction
paradigm. The growing complexity of the ontogenetic mechanisms to be activated
can therefore be compensated by an interactive guidance system emanating from
the environment. This proposition does not however resolve that of the
relevance of the meaning created by the machine (sense-making). Such
reflections lead us to integrate human interaction into this environment in
order to construct relevant meaning in terms of participative artificial
intelligence. This raises a number of questions with regards to setting up an
enactive interaction. The article concludes by exploring a number of issues,
thereby enabling us to associate current approaches with the principles of
morphogenesis, guidance, the phenomenology of interactions and the use of
minimal enactive interfaces in setting up experiments which will deal with the
problem of artificial intelligence in a variety of enaction-based ways
The communication of meaning in social systems
The sociological domain is different from the psychological one insofar as
meaning can be communicated at the supra-individual level (Schutz, 1932;
Luhmann, 1984). The computation of anticipatory systems enables us to
distinguish between these domains in terms of weakly and strongly anticipatory
systems with a structural coupling between them (Maturana, 1978). Anticipatory
systems have been defined as systems which entertain models of themselves
(Rosen, 1985). The model provides meaning to the modeled system from the
perspective of hindsight, that is, by advancing along the time axis towards
possible future states. Strongly anticipatory systems construct their own
future states (Dubois, 1998a and b). The dynamics of weak and strong
anticipations can be simulated as incursion and hyper-incursion, respectively.
Hyper-incursion generates "horizons of meaning" (Husserl, 1929) among which
choices have to be made by incursive agency
What is Autonomy?
A system is autonomous if it uses its own information to modify itself and its environment to enhance its survival, responding to both environmental and internal stimuli to modify its basic functions to increase its viability. Autonomy is the foundation of functionality, intentionality and meaning. Autonomous systems accommodate the unexpected through self-organizing processes, together with some constraints that maintain autonomy. Early versions of autonomy, such as autopoiesis and closure to efficient cause, made autonomous systems dynamically closed to information. This contrasts with recent work on open systems and information dynamics. On our account, autonomy is a matter of degree depending on the relative organization of the system and system environment interactions. A choice between third person openness and first person closure is not required
Modeling Life as Cognitive Info-Computation
This article presents a naturalist approach to cognition understood as a
network of info-computational, autopoietic processes in living systems. It
provides a conceptual framework for the unified view of cognition as evolved
from the simplest to the most complex organisms, based on new empirical and
theoretical results. It addresses three fundamental questions: what cognition
is, how cognition works and what cognition does at different levels of
complexity of living organisms. By explicating the info-computational character
of cognition, its evolution, agent-dependency and generative mechanisms we can
better understand its life-sustaining and life-propagating role. The
info-computational approach contributes to rethinking cognition as a process of
natural computation in living beings that can be applied for cognitive
computation in artificial systems.Comment: Manuscript submitted to Computability in Europe CiE 201
Technology as an observing system : a 2nd order cybernetics approach
The role of technology in modern society is becoming fundamental to society itself as the boundary between technological utilization and technological interference narrows. Technology penetrates the core of an ever-increasing number of application domains. It exerts considerable influence over institutions, often in subtle ways that cannot be fully understood, and the effects of which, cannot be easily demarcated. Also, the ever-expanding ecosystem of Information and Communication Technologies (ICTs) results in an emergent complexity with unpredictable consequences. Over the past decades this has created a tension that has led to a heated debate concerning the relationship between the technical and the social. Some theorists subsume the technical into the social, others proclaim its domination, others its autonomy, while yet others suggest that it is a derivative of the social. Starting with Luhmannâs remark that technology determines what we observe and what we do not observe, this paper takes the approach that infers there are multiple benefits by looking into how Systems Theory can provide a coherent theoretical platform upon which these interactions can be further explored. It provides a theoretical treatise that examines the conditions through which the systemic nature of technology can be inspected. Also, the paper raises a series of questions that probe the nature of technological interference in other âfunction-systemsâ of society (such as the economy, science, politics, etc). To achieve this goal, a 2nd order cybernetics approach is employed (mostly influenced by the works of Niklas Luhmann), in order to both investigate and delineate the impact of technology as system. Toward that end, a variety of influences of Information Systems (IS) are used as examples, opening the door to a complexity that emerges out of the interaction of technology with its socio-economic and political context. The paper describes technology as an observing system within the context of 2nd order cybernetics, and looks into what could be the different possibilities for a binary code for that system. Finally, the paper presents a framework that synthesizes relevant systems theoretical concepts in the context of the systemic character of technology
Is defining life pointless? Operational definitions at the frontiers of Biology
Despite numerous and increasing attempts to define what life is, there is no consensus on necessary and sufficient conditions for life. Accordingly, some scholars have questioned the value of definitions of life and encouraged scientists and philosophers alike to discard the project. As an alternative to this pessimistic conclusion, we argue that critically rethinking the nature and uses of definitions can provide new insights into the epistemic roles of definitions of life for different research practices. This paper examines the possible contributions of definitions of life in scientific domains where such definitions are used most (e.g., Synthetic Biology, Origins of Life, Alife, and Astrobiology). Rather than as classificatory tools for demarcation of natural kinds, we highlight the pragmatic utility of what we call operational definitions that serve as theoretical and epistemic tools in scientific practice. In particular, we examine contexts where definitions integrate criteria for life into theoretical models that involve or enable observable operations. We show how these definitions of life play important roles in influencing research agendas and evaluating results, and we argue that to discard the project of defining life is neither sufficiently motivated, nor possible without dismissing important theoretical and practical research
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