Various classes of physical devices having adaptive sensors, coordinative parts, and/or effectors are considered with respect to the kinds of informational relations they permit the device to have with its environment. Devices which can evolve their own physical hardware can expand their repertoires of measurements, computations, and controls in a manner analogous to the structural evolution of sensory, coordinative, and effector organs over phylogeny. In particular, those devices which have the capacity to adaptively construct new sensors and effectors gain the ability to modify the relationship between their internal states and the world at large. Such devices in effect adaptively create their own (semantic) categories rather than having them explicitly specified by an external designer. An electrochemical device built in the 1950's which evolved the capacity to sense sound is discussed as a rudimentary exemplar of a class of adaptive, sensor- evolving devices. Such devices could potentially serve as semantically-adaptive front-ends for computationally-adaptive classifiers, by altering the feature primitives (primitive categories) that the classifier operates with. Networks composed of elements capable of evolving new sensors and effectors could evolve new channels for inter-element signalling by creating new effector-sensor combinations between elements. The new channels could be formed orthogonal to pre-existing ones, in effect increasing the dimensionality of the signal space. Such variable-dimension signalling networks might potentially lead to more flexible modes of information processing and storage. Devices having the means to both choose their sensors (primitive perceptual categories) and effectors (primitive action categories) as well as the coordinative mappings between the two sets would acquire a degree of epistemic autonomy not yet found in contemporary devices.

Excerpt: There has been a long-standing debate – from Leibnitz to Lady Lovelace to the present – over whether purely computational devices are capable of fundamentally-creative, truly emergent behavior. This paper will discuss various kinds of devices capable of emergent behaviors and take up the question of whether we can by purely computational means amplify our capacities as observers and actors in the physical world.

In the late 1950's Gordon Pask constructed several electrochemical devices having emergent sensory capabilities. These control systems possessed the ability to adaptively construct their own sensors, thereby choosing the relationship between their internal states and the world at large. Devices were built that evolved de novo sensitivity to sound or magnetic fields. Pask’s devices have far-reaching implications for artificial intelligence, self-constructing devices, theories of observers and epistemically-autonomous agents, theories of functional emergence, machine creativity, and the limits of contemporary machine learning paradigms.

Key words: Epistemology, cybernetics, self-organizing systems, emergence, sensory evolution, machine creativity, evolutionary robotics, artificial intelligence, artificial life, autonomous agents.

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.

Key words: combinatoric and creative emergence, dimensionality, observables, signaling systems, temporal coding, neural assemblies.

The functional organization of the nervous system is discussed from the standpoint of organizational closure and regenerative process in order to draw parallels between life and mind. Living organization entails continual regeneration of material parts and functional relations (self-production). Similarly, dynamic stability of informational states in brains may entail coherent self-regenerating patterns of neural signals. If mind is the functional organization of the nervous system, then mental states can be seen as switchings between alternative sets of stable, self-regenerative neural signal productions. In networks of neurons, signaling resonances can be created through recurrent, reentrant neural circuits that are organized to implement a heterarchy of correlational operations. Neural representations are dynamically built-up through an interplay between externally-impressed, incoming sensory signals and internally-generated circulating signals to form pattern-resonances. Semiotic aspects of resonance states involve semantic sensori-motor linkages to and through the external environment and pragmatic linkages to evaluative mechanisms that implement internal goal states. It is hypothesized that coherent regenerative signaling may be an organizational requirement for a material system to support conscious awareness. In this view general anesthetics and seizures abolish awareness by temporarily disrupting the organizational coherence of regenerative neural signaling.

The work of physicist and theoretical biologist Howard Pattee has focused on the roles that symbols and dynamics play in biological systems. Symbols, as discrete functional switching-states, are seen at the heart of all biological systems in the form of genetic codes, and at the core of all neural systems in the form of informational mechanisms that switch behavior. They also appear in one form or another in all epistemic systems, from informational processes embedded in primitive organisms to individual human beings to public scientific models. Over its course, Pattee’s work has explored (1) the physical basis of informational functions (dynamical vs. rule-based descriptions, switching mechanisms, memory, symbols), (2) the functional organization of the observer (measurement, computation), (3) the means by which information can be embedded in biological organisms for purposes of self-construction and representation (as codes, modeling relations, memory, symbols), and (4) the processes by which new structures and functions can emerge over time. We discuss how these concepts can be applied to a high-level understanding of the brain. Biological organisms constantly reproduce themselves as well as their relations with their environs. The brain similarly can be seen as a self-producing, self-regenerating neural signaling system and as an adaptive informational system that interacts with its surrounds in order to steer behavior.

Key words: Adaptive systems, biological cybernetics, biological semiotics, dynamical systems, emergence, epistemology, evolutionary robotics, genetic code, neural code, neurocomputation, self-organization, symbols.

Temporal codes and neural temporal processing architectures (neural timing nets) that potentially subserve perception of pitch and rhythm are discussed. We address 1) properties of neural interspike interval representations that may underlie basic aspects of musical tonality (e.g., octave similarities), 2) implementation of pattern-similarity comparisons between interval representations using feedforward timing nets, and 3) representation of rhythmic patterns in recurrent timing nets. Computer simulated interval-patterns produced by harmonic complex tones whose fundamentals are related through simple ratios showed higher correlations than for more complex ratios. Similarities between interval-patterns produced by notes and chords resemble similarity-judgements made by human listeners in probe tone studies. Feedforward timing nets extract common temporal patterns from their inputs, so as to extract common pitch irrespective of timbre and vice versa. Recurrent timing nets build up complex temporal expectations over time through repetition, providing a means of representing rhythmic patterns. They constitute alternatives to oscillators and clocks, with which they share many common functional properties.

Open peer commentary on the target article “Arguments Opposing the Radicalism of Radical Constructivism” by Gernot Saalmann. First paragraph: Although supportive of many of the positions taken by constructivists, pragmatists, and instrumentalists against “metaphysical realism,” the author Gernot Saalmann mounts arguments against all epistemological radicalisms, in favor of a critical realism. Ultimately he seeks “development of an antimetaphysical, non-objectivist epistemology” rooted in pragmatism.

W. Ross Ashby was a founder of both cybernetics and general systems theory. His systems theory outlined the operational structure of models and observers, while his cybernetics outlined the functional architecture of adaptive systems. His homeostat demonstrated how an adaptive control system, equipped with a sufficiently complex repertoire of possible alternative structures, could maintain stability in the face of highly varied and challenging environmental perturbations. The device illustrates his ‘law of requisite variety’, i.e. that a controller needs at least as many internal states as those in the system being controlled. The homeostat provided an early example of how an adaptive control system might be ill-defined vis – vis its designer, nevertheless solve complex problems. Ashby ran into insurmountable difficulties when he attempted to scale up the homeostat, and consequently never achieved the general purpose, brainlike devices that he had initially sought. Nonetheless, the homeostat continues to offer useful insights as to how the large analogue, adaptive networks in biological brains might achieve stability.

Upshot: Emergence and Embodiment is a highly worthwhile and well-crafted collection of essays on second-order cybernetics that draws together ideas related to self-organization, autopoiesis, organizational closure, self-reference, and neurophenomenology. Chapters include articles by Heinz von Foerster, Francesco Varela, Niklas Luhmann, George Spencer-Brown, and Evan Thompson and external commentaries on them that analyze the relevance of their ideas in the context of social and cultural theory. Despite some projective distortions to cybernetics that arise from the internal imperatives of culture criticism, the book contains many valuable insights and analyses of core ideas of cybernetics that significantly advance our understanding of them.