This article presents the design and analysis of a polysensory listening experience of different languages. Combining sensory design, phenomenology and language education, this research draws on the enaction paradigm. The objective of the authors is twofold: to understand the nature and structures of transmodal perception of unknown languages and to prepare a novel educational approach to sensory awareness to foreign languages. The article will explain the origin of the project as well as its theoretical framework and the foundations that dictated the aesthetic and didactic choices for the video used as a primer within the experiment. Finally, the authors share findings that suggest that inhabitual ways of listening to familiar and unfamiliar languages result in emotional filters as well as cognitive and attentional oscillations.

The present paper wants to show the extent to which prosody, or best, prosodies, as Firth (1948) put it, contribute in their own and specific ways to enaction, at various levels of operational closure. On the one hand prosodies (stress, accent, melody) are linked to speech and exchange in a non-escapable fashion, as opposed to gesture for example. Hearing speech implies hearing syllables, tones, intensity variations; it does not imply seeing face or gesture (though one may object the language-dependency of prosody – gesture pairings). Simon & Auchlin (2004) described the independent timings of parameters, such as pitch range, height and intensity, speech rate: the first two or three syllables of speech alone inform on speaker sex, age, mood, investment in speech, importance of speech for her, or intentionality; the meaning of the whole utterance is obtained much later, thus the first flow somehow frames the second which, in turn, may allow blending with previously accessed information. In that way, linguistic meaning incorporates prosodic manifestations. On the other hand, one of the most basic prosodic dimensions, namely speech rate (articulation rate + pauses) is properly speaking a shared dimension between speaker and hearer: no one can hear slowly, or more rapidly than the speaker speaks. Speech rate is properly un-escapable, or necessarily shared dimension in dialogue. Indeed, interpreting is constantly anticipating – but anticipations timing still depends upon speech rate. Note that speech rate is also un-escapable for the observer, provided (s) he enacts the discourse, turning herself into a participant in the piece of interaction (s) he wants to describe (Auchlin, 1999). Sharing the temporal grid, i. e. entering it, is essential to such now. Indeed, interactionists’ work (P. Auer, E. Couper-Kuhlen, F. Müller; M. Selting; J. Local, i. a.) precisely describe verbal interactions’’ ballet temporality. Yet, their descriptive claim, which constrains empirical work, deliberately rejects any kind of theoretical conclusion or generalization; and their need to '‘objectively’’ describe speech events firmly contradicts what is mandatory for the enactive approach, namely the epistemological experientialist turn, first posited by Lakoff & Johnson (1980). The present paper examines a couple of emblematic cases of prosodic enacting meaning experience that should contribute to grounding the concept, both on its epistemological and its empirical sides.

Francisco Varela’s neurophenomenological research program is still ahead of us. It therefore needs some further philosophical reflections in order to become fully understood, and to avoid mixing it up with other views. Neurophenomenology shares so many features with the mind-brain identity theory that it has sometimes been mistaken for it, and that it also shares some of its explanatory virtues. But it also parts company with the identity theory on a crucial point, so that it is immune of several defects of the latter conception. The major difference is that it deflects theoretical issues onto a methodological plane; it does not state a mind-brain identity, but rather tries to institute a close relationship between the two corresponding methods of investigation. Besides, some sentences of Varela were strongly suggestive of idealism. But once again, this is wrong. Varela does not hold the ontological primacy of lived experience. He only advocates the importance for science of taking into account in its practice all the aspects of experience, be they subjective or objective. A final parallel with evolutionary biology and quantum physics shows that neurophenomenology has reached a high level of epistemological universality.

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.

Although cognitive science has recently asked how human sociality is constituted, there is no clear and consistent account of the emergence of human style social agency. Previously, we have critiqued views based on '‘participatory sensemaking’’ by arguing that agency requires a distinctive kind of phenomenology that enables a diachronic social experience. In advancing the positive argument, we link developmental psychology to phenomenological insights by focusing on childcaregiver dynamics around the middle of the second year. Having developed very basic social skills, an infant comes to feel normative perturbances impinging on her in a way that leads to new modes of action. Accordingly, we trace agency and linguistic competencies to how these kinds of coordination intermesh. Nascent capabilities for predicating draw on the child’s history of coping with norms and rules that are imposed by caretakers. Developmental events thus transform the child’s experience and drive the emergence of social agency. Once the child has successfully dealt with the environment’s normative perturbations she is able to develop the skills of a fullyfledged human social agent.

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.

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.

In this issue, the authors present how robotics can not only be inspired by biology but also constitute a proxy to better understand it. Here we emphasize the need to keep a clear the distinction between natural organisms and artificial machines and to ethically consider the impact of robotics and artificial intelligence on human society.