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.

This article critiques recent enactivist attempts to bridge an epistemological divide between the individual and the social (i.e. to fill in the posited macro-micro gap) Its central claim is that an inflated view of ‘autonomy’ leads to error. Scrutinising two contributions, we find that methodological solipsism taints Varela’s model: It induces De Jaegher & Di Paolo to ascribe social knowledge to perturbances – contingencies whose logic arises from the closed organization of an individual (De Jaegher & Di Paolo, 2007) and Steiner & Stewart to posit that the pre-dispositions of an organizationally closed world prompt individuals to “receive” shared norms (Steiner & Stewart, 2009) On our deflated view, neither organizational closure nor participatory sense making apply to most human cognition. Rather, we invoke a developmental process based on the recursive self-maintenance that is found in all organism-environment systems (including bacteria) Humans differ in that infants discover ways of making skilled use of phenomenal experience: they learn to predicate something of lived experience. As observers, they connect impersonal resources of culture (artifacts, institutions, languages etc.) with on-going social and environmental activity. This human kind of heteronomy links social processes to agent-environment systems that sustain – and are sustained by – historically positioned modes of life. Far from being organisationally closed, human subjects depend on using sensorimotoric prompts to connect the phenomenal with the impersonal and open up a partly shared, partly lived, reality.

This paper introduces an original model to provide software agents and robots with the capacity of learning by interpreting regularities in their stream of sensorimotor experience rather than by exploiting data that would give them ontological information about a predefined domain. Specifically, this model pulls inspiration from: a) the movement of embodied cognition, b) the philosophy of knowledge, c) constructivist epistemology, and d) the theory of enaction. Respectively to these four influences: a) Our agents discover their environment through their body’s active capacity of experimentation. b) They do not know their environment “as such” but only “as they can experience it.” c) They construct knowledge from regularities of sensorimotor experience. d) They have some level of constitutive autonomy. Technically, this model differs from the traditional perception/cognition/action model in that it rests upon atomic sensorimotor experiences rather than separating percepts from actions. We present algorithms that implement this model, and we describe experiments to validate these algorithms. These experiments show that the agents exhibit a certain form of intelligence through their behaviors, as they construct proto-ontological knowledge of the phenomena that appear to them when they observe persistent possibilities of sensorimotor experiences in time and space. These results promote a theory of artificial intelligence without ontological data about a presupposed reality. An application includes a more robust way of creating robots capable of constructing their own knowledge and goals in the real world, which could be initially unknown to them and un-modeled by their designers.

Key words: artificial intelligence, embodied cognition, constructivist learning, enaction, hierarchical sequence learning, trace-based reasoning, cognitive architecture, self-motivation

This paper introduces an original model to provide software agents and robots with the capacity of learning by interpreting regularities in their stream of sensorimotor experience rather than by exploiting data that would give them ontological information about a predefined domain. Specifically, this model pulls inspiration from: a) the movement of embodied cognition, b) the philosophy of knowledge, c) constructivist epistemology, and d) the theory of enaction. Respectively to these four influences: a) Our agents discover their environment through their body’s active capacity of experimentation. b) They do not know their environment “as such” but only “as they can experience it.” c) They construct knowledge from regularities of sensorimotor experience. d) They have some level of constitutive autonomy. Technically, this model differs from the traditional perception/cognition/action model in that it rests upon atomic sensorimotor experiences rather than separating percepts from actions. We present algorithms that implement this model, and we describe experiments to validate these algorithms. These experiments show that the agents exhibit a certain form of intelligence through their behaviors, as they construct proto-ontological knowledge of the phenomena that appear to them when they observe persistent possibilities of sensorimotor experiences in time and space. These results promote a theory of artificial intelligence without ontological data about a presupposed reality. An application includes a more robust way of creating robots capable of constructing their own knowledge and goals in the real world, which could be initially unknown to them and un-modeled by their designers.

Key words: artificial intelligence, embodied cognition, constructivist learning, enaction, hierarchical sequence learning, trace-based reasoning, cognitive architecture, self-motivation.

A l“encontre de l“acception classique, qui voit dans la représentation le tenant-lieu d“un référent prédonné, nous proposons une définition de la représentation comme activité de rendre présent. Cette approche, qui s“origine dans le concept phénoménologique d“intentionnalité, ouvre les sciences cognitives à un programme de recherche fondé sur l”énaction et renvoie à une définition de la cognition ancrée dans le vivant. Or des dispositifs de couplage sensori-moteur médiatisent le co-avènement de l“organisme et de son monde propre. Inamovibles chez l“animal, ces dispositifs deviennent amovibles chez l“homme et donnent lieu à des prothèses techniques qui lui permettent une inventivité inédite. Anthropologiquement constitutive, la technique médiatise ainsi la représentation par une mémoire externe inscrite dans des objets matériels. Au plan phénoménologique, elle instaure une genèse technologique de l“intentionnalité qui ébranle le partage traditionnel entre l“empirique et le transcendantal.

Key words: phenomenology, intentionality, representation

The aim of this article is to set up a reciprocal relationship between a scientific study of perception, and phenomenology as a philosophical method. The domain chosen for this exercise is the constitution of spatiality, and in particular spatial depth. After recalling the question of depth as it is presented in The phenomenology of perception by Merleau-Ponty, we present an original experimental study based on a sensory substitution device. This study, which is based on an approach to perception as the extraction of sensory-motor loops, is carried out following two successive points of view: an objective, “third person” perspective, and a “first person” perspective involving a phenomenological analysis of the experience of the subject. The concluding discussion, based on the original phenomenological status of tools, proposes the existence of an “asymmetrical reciprocal envelopment” between that which is constitutive and that which is constituted. This makes it possible to determine the objective “correlates” of the elements of the phenomenological description of the constitution of the experience of depth.

Key words: depth perception, phenomenology, experimental study, third person perspective, first person perspective, tools, constitution.

In the first cybernetics (McCulloch) and the second one (Ashby and von Foerster) as well recursivity was supposed to be a central concepts. But in both theories, the power of recursive functions (to find the code of the program which computes a function that depends on this very same code) as well as the troubles raised by non recursively enumerable functions have been overlooked. A similar position can be found in some theories related to the connectionism of the eighties, that have also been pretended to take place beyond the real power of recursivity.

Key words: recursivity, cybernetics, code, program, connectionism

The purpose of this paper is to describe the neurophenomenologi- cal project on epileptic seizure anticipation, and to sum up the methodological diffi- culties we met. The analysis of neuroelectric signals with new mathematical methods has provided strong evidence that it is possible to detect a pre-seizure state in the neu- ronal dynamics a few minutes before the seizure onset: do these neurodynamical modifications correspond to any modifications in the patients’ subjective experience, and which ones? This paper describes our attempt to correlate these two dimensions of seizure anticipation, the neuroelectric one and the phenomenological one. The em- phasis is put on the phenomenological dimension and the problems related with the description of the patients’ subjective experience. We also describe the different levels of correlation we explored between first person and third person data, stressing the methodological difficulties we met at each level. In conclusion, we evaluate the re- sults of the project and the relevance of the neuro-phenomenological approach on the therapeutic, methodological and epistemic levels…

Key words: Neurophenomenology, phenomenology, subjective experience, epilepsy, epileptogenesis, anticipation of epileptic seizures, cognitive therapy of epilepsy.

Can the “first person” point of view help in an assessment of the relevance of the theory of enaction, theory in which the inside and the outside, the knower and the known, the mind and the world, determine each other? On the basis of an exploration of the dynamic micro-structure of lived experience, we suggest some means of tackling this question.

Key words: Dynamic structure, enaction, explicitation, first person, lived experience, micro-genesis, neuro-phenomenology, transmodality

This article describes a research programme aimed at integrating a disciplined study of lived experience as a part of cognitive science, thanks to new methods which make it possible to obtain a precise and rigorous description of the “first person” experience of the subject. After presenting the procedures involved in these methods, their epistemological foundations, and the process of circulation between analysis in the first person and third person, we explore possible applications of these methods in clinical and therapeutic domains, in the domains of education transfer.