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.
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.
What deliverables did Stafford Beer envision when he developed his “science of effective organisation”? This paper answers this question as: the organisations that use the distinctions of Beer’s viable system model. Such organisations are part of daily life, but develop to become knowledge by continuously striving to identify experiences that falsify their existence. They will be irreducible in the sense that any acceptable model of the organisation will be the organisation itself. The notion of knowledge involved is made explicit in the paper as a tribute to Stafford Beer’s pioneering work. It allowed Stafford Beer to introduce and develop insights that began to be developed by others only much later.
How is the field of systems science different from other scientific fields, and how can we distinguish the various traditions within systems science? We propose that there is a set of underlying assumptions which are generally shared within systems science but are less common in other scientific fields. Furthermore, the various traditions within systems science have adopted different combinations of these assumptions. We examine six traditions within systems science – cybernetics, operations research, general systems theory, system dynamics, total quality management, and organizational learning. We then consider eight underlying assumptions – observation, causality, reflexivity, self-organization, determinism, environment, relationships, and holism. We then assess where each tradition stands with respect to each of the underlying
For half a century, the widespread occurrence of threshold in the nervous system, and the importance of threshold in the details of neuronic activity, have been well known. There is less known, however, about how threshold would show in the large – in the behavior of the organism as a whole. Two studies (Beurle, 1956; Farley and Clark, 1961) have been made of the behavior of waves of activity traveling through a nerve net. Both studies have shown that such a net would have difficulty in maintaining a steady activity, for the wave of activity tends either to die out completely or to increase to saturation. Far from being tractable and steady, from the standpoint of biological usefulness such a network displays an essential instability. Not only does it tend rapidly to the extremes of inactivity or activity, but, once there, it can be moved away from the extreme only with difficulty. This finding deserves emphasis because it is quite contrary to the plausible idea that threshold stabilizes a network. It also suggests that the actual brain must incorporate some mechanism that actively opposes the instability. The studies cited are complex and do not allow the instability and the threshold to be related directly and simply. Here, we shall show that an extremely general and simple rr.odel still allows the relation to be displayed clearly. It also allows us to see more readily what is essential.
I’d like, in this column, to celebrate Charles Francois” astonishing “International Encyclopaedia of Systems and Cybernetics.” This mammoth undertaking is the outcome of an act of the greatest generosity towards our field and community. I believe, therefore, that it is an essentially cybernetic act: because, for me, cybernetics can only exist where generosity is the presumed mode of behavior. Cybernetics requires generosity: it requires generosity from us in our behavior, and, if we wish to benefit from having it, cybernetics also requires that we behave generously to get that benefit.
Von Bertalanffy stated that, at a certain threshold of complexity – namely when numerous forces are simultaneously interacting – systems” dynamics belong to a class other than causal mechanism, whether linear or circular. My objective here is to develop Von Bertalanffy’s point and to sort out a class of systems, the multilevel web, in which various forces or subsystems interact simultaneously within and across levels. Webs thus exhibit dynamical evolution through the cooperation and co-evolution of processes. I focus on two instances of multilevel web – the human mind, and small groups of people and show that cognitive webs demonstrate creative self-organization, as well as plural self-reference and free-will. I argue that, in multilevel webs, the variety and the complexity of forces interacting simultaneously instantiate inter-influences between connected elements/processes, so complex that they render causality irrelevant as a formalism. Webs’ inter-influences are fundamentally non deterministic, and they reach beyond causal mechanisms. However, simpler mechanisms such as linear cause-effects and circular causality may exist as component processes, enmeshed in the ensemble of interactions of the more complex system. In the first and second sections I present cognitive and social webs and sort out their properties.