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The link between robotic systems and living systems is increasingly considered to be important. However finding out more precisely which properties these two kinds of system must share is a difficult question to answer. It is suggested that behavioral plasticity constitutes a crucial property that robots must share with living beings. A classification is then proposed for the different aspects of plasticity that contribute to global behavioral plasticity in robotic and living systems. These are mainly divided into four dimensions and three orders. Finally some consequences of this classification are mentioned regarding the future of biologically-inspired robotics and the role of evolutionary AI.

Neuroscience is deeply influenced by computationalism, namely, the thesis that the brain is an information processing machine or computer. In this paper it is shown that a significant portion of this influence is due to the epistemological principle of Verum Factum which states that true understanding of a phenomenon is not possible unless one knows how to make the phenomenon. Important differences between biological nervous systems and computers are listed with the consequence that brains cannot be built the same way computers are. If computationalism cannot provide recipes for building brains, it fails to meet the Verum Factum principle, thus weakening significantly its influence.

A recent debate concerning the representational content of DNA in developmental processes has opposed “dynamicists” and “computationalists.” I review the arguments in favor of a representational interpretation of the role of genes, and show that they are inconclusive. There is a very restricted sense in which genes can be said to represent something, and stronger claims about DNA being a program for the construction of an organism are overstatements. I also show that arbitrariness, taken by representationalists to be a central criterion for identifying representational vehicles, is neither a sufficient nor a necessary condition to qualify as a representation. Finally, I propose a relatively new way to define what programs are, which implies that genetic regulatory networks shouldn’t be thought of as being programs. As a consequence, insofar as cognition and development share similar mechanisms, any computational account of cognition should be significantly weakened.

It is widely believed that neural elements interact by communicating messages. Neurons, or groups of neurons, are supposed to send packages of data with informational content to other neurons or to the body. Thus, behavior is traditionally taken to consist in the execution of commands or instructions sent by the nervous system. As a consequence, neural elements and their organization are conceived as literally embodying and transmitting representations that other elements must in some way read and conform to. In opposition to this conception, growing approaches such as enactivism and ecological psychology hold that neurons are not in the business of representing. However, by insisting that neural causation is not of a representational kind, these anti-representationalist approaches seem to be left with only one rather implausible alternative, viz. that behavior is the result of nothing but basic physical causation such as push-pull forces. In this paper it is argued that a third form of causation—termed “modulation”—exists and is at work in the coordination of animal behavior. Modulation is the quasi-direct guidance of dynamical systems through specific yet emerging trajectories. By setting the constraints that coordinate the free interaction of multi-element systems, modulation influences without forcing nor representing goal states. The basic properties of modulatory causation are analyzed and shown to be present in some fundamental aspects of neural and bodily interaction.

Luciano Floridi reinterprets and re-ontologizes our world
informationally. That part of his theory may (or may
not) work, but what matters for this paper’s topic is that
when it comes to defining what the value of Being is, his
informational-ontological interpretation is based on order,
organization, and structure. Therefore, there is a common
ground between his interpretation and the way modern
thermodynamics formalizes the concept of order. Floridi
proposes to think of Good as qualitative order and Evil as
its absence, or entropy. However, the kind of entities that are
of importance to us for our judgments and interventions as
agents are ordered and thus valuable because they exist far
from equilibrium. In this paper I shall attempt to establish
that far-from-equilibrium systems attain ever increasing
degrees of order at the cost of faster entropy production. Yet,
inversely, by promoting an increase in entropy production,
more complex and ordered forms emerge on Earth. Entropy
production and order are thus complementary; they imply
each other reciprocally. By promoting Evil in Floridi’s sense,
Good happens lawfully because order is nature’s favorite
way of producing entropy. In short, moving against entropy
only creates more entropy

Answers to the question of perceptual presence are usually
either representational or dispositional. According to the former, we
feel internal representations of features unavailable to the senses
while the latter holds that the feeling is but a disposition to certain
behavioural reactions to those features. The sensorimotor theory of
perception tries to avoid both positions by positing a form of knowledge
of sensorimotor patterns that is not behavioural yet operates as
an implicit skill. It is argued that this position has not been supported
well enough and that, as it stands, it is too close to representationalism.
The example of predictive processing as a theory that claims to
implement perceptual presence as explicit counterfactual representations
is advanced, then criticized. As an alternative, an account based
on coordinative structures is proposed where perceptual presence is
due to the feeling of constraints upon the structures underlying
sensorimotor interactions. This account thus favours a dispositional
interpretation.

Jakob von Uexküll is mostly known for his concept of Umwelt-the meaningful surrounding of animals. von Uexküll insisted vehemently on the fact that Umwelt vindicated Kant's subjectivist epistemology in the biological domain. However, we argue that a crucial yet widely overlooked development in von Uexküll's theory of meaning implies a more radical vision strikingly germane to J. J. Gibson's own direct realist epistemology-ontology and in tension with his own subjectivist concept of Umwelt. Gibson argued that organism and environment are complementary and meaning is not constructed via a subjective act but is directly available in the world as opportunities for action, namely, affordances. We show that von Uexküll's notion of "functional tone" is similar to Gibson's concept of affordance in that it includes action in perception. More important, von Uexküll introduces the musical metaphor of harmony to characterize the relationship between animal and environment. Like Gibson's reciprocity , harmony implies an unmediated isomorphism between the dispositions of the animal and those of the environment that allows for direct perceptual contact with the world and action upon it.

An underlying bias of contemporary cognitive science is that the brain and nervous system are in the business of carrying out computations and building representations. Gibson's ecological approach, in contrast, is decidedly noncomputational and nonrepresentational. How, then, are we to construe the role of brain and nervous system? We consider this question against the backdrop of evidence for rich achievements in perception and action by agents without brains or nervous systems. If fundamental coordination of perception and action does not require a neural substrate, then what value is added in having one? And if the neural substrate is not in the representa-tional-computational business, then what business is it in? We pursue answers grounded in the constraints of macroscopic, multicellular life and thermodynamics. Gibson tends to leave the organism, if not empty, apparently stuffed with foam rubber (Pribram, 1982, p. 370) One dimension of notoriety for Gibson's ecological approach is its lack of enthusiasm for explaining the achievements of perception and action by recourse to neurophysiology. The litany of disparagements that can be quoted from proponents of the ecological approach is unabashed and unambiguous. Much of what has been written takes pains to elucidate why driving an explanation of perception-action from neurophysiology is unsatisfactory. In contrast with the opening lamentation from Pribram, however, a number of those same scholars have also offered suggestions about the style of approach to understanding the role of brain and nervous system that would be more compatible with an ecological approach to perception-action. In this article, we will briefly summarize these historical tacks in order to set the stage for what we see as the requisite framework for understanding what nervous systems are for. At issue is the question: What value do they add? What do they do that has warranted reproduction or, even more fundamentally, warranted their emergence in evolution?

Motor behavior is a phenomenon where the components making up a biological system are organized so as to ensure the coordination of a purposeful movement. According to computational theories, behavior is defined as a motor problem the solution of which can be found by systems divided hierarchically. The components process and communicate information representing the relevant variables of the motor problem (positions, trajectories, velocities, forces, etc.) which are, in turn, assumed to be organized as a hierarchy of increasing abstraction and complexity. The challenge is to tackle the four core problems of behavior: a) The high number of degrees of freedom and their interactions; b) The redundancy of degrees of freedom; c) The anticipation of the effects of movement; d) The uncertainty in information. Classical computational theories advance explanatory schemas made of structured sets of internal models (forward and inverse). More recently, the Bayesian approach advances a more homogeneous hierarchical schema which is supposed to account for uncertainty in information. This research shows that computational theories, including the Bayesian approach, are crippled by an unsolvable dilemma: The first horn is that if the models can scale up while staying computationally tractable, i.e. the computations can be carried out in a reasonable amount of time, then they fail to reproduce the versatility which characterizes the behavior of living beings. The second horn is that if the models aspire to reproduce biological versatility, then they are intractable.

Tensegrity systems have been proposed as both the medium of haptic perception and the functional architecture of motor coordination in animals. However, a full working model integrating those two aspects with some form of neural implementation is still lacking. A basic two-dimensional cross-tensegrity plant is designed and its mechanics simulated. The plant is coupled to a Recurrent Neural Network (RNN). The model's task is to maintain postural balance against gravity despite the intrinsically unstable configuration of the plant. The RNN takes only proprioceptive input about the springs' lengths and rate of length change and outputs minimum lengths for each spring which modulates their interaction with the plant's inertial kinetics. Four artificial agents are evolved to coordinate the patterns of spring contractions in order to maintain dynamic equilibrium. A first study assesses quiet standing performance and reveals coordinative patterns between the tensegrity rods akin to humans' strategy of anti-phase hip-ankle relative phase. The agents show a mixture of periodic and aperiodic trajectories of their Center of Mass. Moreover, the agents seem to tune to the anticipatory "time-to-balance" quantity in order to maintain their movements within a region of reversibility. A second study perturbs the systems with mechanical platform shifts and sensorimotor degradation. The agents' response to the mechanical perturbation is robust. Dimensionality analysis of the RNNs' unit activations reveals a pattern of degree of freedom recruitment after perturbation. In the degradation sub-study, different levels of noise are added to the RNN inputs and different levels of weakening gain are applied to the forces generated by the springs to mimic haptic degradation and muscular weakening in elderly humans. As expected, the systems perform less well, falling earlier than without the insults. However, the same systems re-evolved again under the degraded conditions see significant functional recovery. Overall, the dissertation supports the plausibility of RNN cum tensegrity models of haptics-guided postural coordination in humans.