Living systems are characterized as self-generating and self-maintaining systems. This type of characterization allows integration of a wide variety of detailed knowledge in biology. The paper clarifies general notions such as processes, systems, and interactions. Basic properties of self-generating systems, i.e. systems which produce their own parts and hence themselves, are discussed and exemplified. This makes possible a clear distinction between living beings and ordinary machines. Stronger conditions are summarized under the concept of self-maintenance as an almost unique character of living systems. Finally, we discuss the far-reaching consequences that the principles of self-generation and self-maintenance have for the organization, structure, function, and evolution of singleand multi-cellular organisms.
This paper has a dual purpose. On the one hand, it suggests ways of making autopoietic theory more precise and more operational for concrete communication analysis. I discuss concepts such as distinction, system, bound- ary, environment, perturbation, and compen- sation. The explication of the concepts is ba- sed on catastrophe theory, and in order to make them operational I emphasise their affinity to traditional semiotics and communi- cation theory. On the other hand I propose changes to the semiotic tradition in order to incorporate insights from autopoietic theory, namely that the human condition is characte- rised by the phenomenon of self-reference and therefore also by the unavoidability of para- doxes. Firstly, this means that truth cannot be a basic semiotic concept; instead the notion of stability is suggested. Secondly, in order to act in a paradoxical context, we need to unfold the paradox in time, which again calls for a dynamic theory of meaning.
Maturana and Varela’s concept of autopoiesis defines the essential organization of living systems and serves as a foundation for their biology of cognition and the enactive approach to cognitive science. As an initial step toward a more formal analysis of autopoiesis, this paper investigates its application to the compact, recurrent spatiotemporal patterns that arise in Conway’s Game of Life cellular automata. In particular, we demonstrate how such entities can be formulated as self-constructing networks of interdependent processes that maintain their own boundaries. We then characterize the specific organizations of several such entities, suggest a way to simplify the descriptions of these organizations, and briefly consider the transformation of such organizations over time. Relevance: The paper presents an analysis of a minimal concrete model of autopoiesis to provide a more rigorous foundation for the concept of autopoiesis and highlight its ambiguities and difficulties.
Autopoietic theory is more than a mere characterization of the living, as it can be applied to a wider class of systems and involves both organizational and epistemological aspects. In this paper we assert the necessity of considering the relation between autopoiesis and emergence, focusing on the crucial importance of the observer’s activity and demonstrating that autopoietic systems can be considered intrinsically emergent processes. From the attempts to conceptualize emergence, especially Rosen’s, autopoiesis stands out for its attention to the unitary character of systems and to emergent levels, both inseparable from the observer’s operations. These aspects are the basis of Varela’s approach to multiple level relationships, considered as descriptive complementarities.
In this article I will outline the basic theoretical assumptions of two examples of the confederative and the integrative views of the living – respectively Ganti’s Chemoton theory and Maturana and Varela’s autopoietic theory – by showing that they are both consistent perspectives, but they differ in the accounts they make of the role of organization in biological systems. In doing so I will also put into evidence how the choice between these two theoretical frameworks is strictly connected to the problem of structure and function in living organisms and entails different strategies of investigation.
An approach which has the purpose to catch what characterizes the specificity of a living system, pointing out what makes it different with respect to physical and artificial systems, needs to find a new point of view – new descriptive modalities. In particular it needs to be able to describe not only the single processes which can be observed in an organism, but what integrates them in a unitary system. In order to do so, it is necessary to consider a higher level of description which takes into consideration the relations between these processes, that is the organization rather than the structure of the system. Once on this level of analysis we can focus on an abstract relational order that does not belong to the individual components and does not show itself as a pattern, but is realized and maintained in the continuous flux of processes of transformation of the constituents. Using Tibor Ganti’s words we call it “Order in the Nothing”. In order to explain this approach we analyse the historical path that generated the distinction between organization and structure and produced its most mature theoretical expression in the autopoietic biology of Humberto Maturana and Francisco Varela. We then briefly analyse Robert Rosen’s (M, R)-Systems, a formal model conceptually built with the aim to catch the organization of living beings, and which can be considered coherent with the autopoietic theory. In conclusion we will propose some remarks on these relational descriptions, pointing out their limits and their possible developments with respect to the structural thermodynamical description.
This paper seeks to juxtapose the work of Sir Geoffrey Vickers and Humberto Maturana with a view to thinking more about the theoretical underpinnings of Peter Checkland’s soft systems methodology (SSM) and of soft systems and soft operational research more generally. The paper argues that Maturana’s ‘Theory of the Observer’ can usefully complement Vickers by specifying more precisely the nature of the cognitive structures that underpin people’s descriptions of situations, by clarifying the relationship between cognitive creativity and the historical and relational constraints that bear upon people’s descriptions and explanations, and by providing a more complete description of the dynamics that underpin individual and social learning.
Emergence is the process by which new structures and functions come into being. There are two fundamental, but complementary, conceptions of emergence: combinatoric emergence, wherein novelty arises by new combinations of pre-existing elements, and creative emergence, wherein novelty arises by de novo creation of new kinds of elements. Combinatoric emergence is exemplified by new strings constructed from existing alphabetic letters, whereas creative emergence is exemplified by the addition of new kinds of letters to an alphabet. The two conceptions are complementary, providing two modes for describing and understanding change: as the unfolding consequences of a fixed set of rules or as new processes and interactions that come into play over time. Within an observer-centered, operational framework, the two kinds of emergent novelty can be distinguished by what an external observer must do in order to successfully predict the behavior of an evolving system. Combinatoric and creative emergence can be operationally distinguished by changes in apparent effective dimensionality. Whenever a new independent observable is added to a model, its dimensionality increases by one. A system that only recombines requires no new observables, and does not expand in effective dimension. In contrast, a system that creates new primitives requires new observables for its description, such that its apparent dimensionality increases over time. Dimensional analysis can be applied to signaling systems. Signals have two basic functional properties: signal-type (category, variable, type) and signal-value (state, value, token). These properties can be conveyed by a variety of means: by the signal’s physical channel, by the internal form of the signal (waveform, Fourier spectrum), by its time of arrival, and by its magnitude (average power). Neural coding schemes can similarly be based on which neurons fire, which temporal patterns of spikes are produced, when volleys of spikes arrive, or how many spikes are produced. Traditional connectionist networks are discussed in terms of their assumptions about signal-roles and neural codes. For the most part, connectionist networks are conceptualized in terms of new linkage combinations rather than in terms of new types of signals being created. Neural networks that increase their effective dimensionalities can be envisioned. Some kinds of neural codes, such as temporal pattern and time-of-arrival codes, permit encoding and transmission of multidimensional information by the same elements (multiplexing). We outline how synchronous time-division and asynchronous code-division multiplexing might be realized in neural pulse codes. Multidimensional temporal codes permit different kinds of information to be encoded in different time patterns. Broadcast-based coordination strategies that obviate the need for precise, specified point-to-point connections are then made possible. In such systems new signal types arise from temporal interactions between time-coded signals, without necessarily forming new connections. Pitches of complex tones are given as examples of temporally-coded, emergent Gestalts that can be seen either as the sums of constituent micro-patterns (combinatoric emergence) or as the creation of new ones. Within these temporally-coded systems, interacting sets of neural assemblies might ramify existing, circulating signals to construct new kinds of signal primitives in an apparently open-ended manner.
This chapter outlines a broad theory of sign use in natural and artificial systems that was developed over several decades within the context of theoretical biology, cybernetics, systems theory, biosemiotics, and neuroscience. Different conceptions of semiosis and information in nature are considered. General functional properties of and operations on signs, including measurement, computation, and sign-directed actions are described. A taxonomy of semiotic systems is built up from combinations of these operations. The respective functional organizations and informational capabilities of formal systems and computempiral-predictive scientific models, percept-action systems, purposive goal-seeking systems, and self-constructing systems are discussed. Semiotic relations are considered in terms of Morrisean semiotic triad of syntactics, semantics, and pragmatics. Analysis of statetransition structure is used to demarcate functional boundaries, such as epistemic and control cuts. Capabilities for open-ended behavior, combinatoric and emergent creativity, and umwelt expansion are taken up. Finally, basic problems of neurosemiotics, neural coding, and neurophenomenology are outlined.