Beyond Gazing, Pointing, and Reaching: A Survey of Developmental Robotics

Developmental robotics is an emerging field located at the intersection of developmental psychology and robotics, that has lately attracted quite some attention. This paper gives a survey of a variety of research projects dealing with or inspired by developmental issues, and outlines possible future directions

Adaptivity through alternate freeing and freezing of degrees of freedom

Starting with fewer degrees of freedom has been shown to enable a more efficient exploration of the sensorimotor space. While not necessarily leading to optimal task performance, it results in a smaller number of directions of stability, which guide the coordination of additional degrees of freedom. The developmental release of additional degrees of freedom is then expected to allow for optimal task performance and more tolerance and adaptation to environmental interaction. In this paper, we test this assumption with a small-sized humanoid robot that learns to swing under environmental perturbations. Our experiments show that a progressive release of degrees of freedom alone is not sufficient to cope with environmental perturbations. Instead, alternate freezing and freeing of the degrees of freedom is required. Such finding is consistent with observations made during transitional periods in acquisition of skills in infants

Simulating development in a real robot: on the concurrent increase of sensory, motor, and neural complexity

We present a quantitative investigation on the effects of a discrete developmental progression on the acquisition of a foveation behavior by a robotic hand-arm-eyes system. Development is simulated by (a) increasing the resolution of visual and tactile systems, (b) freezing and freeing mechanical degrees of freedom, and (c) adding neuronal units to the neural control architecture. Our experimental results show that a system starting with a low-resolution sensory system, a low precision motor system, and a low complexity neural structure, learns faster that a system which is more complex at the beginning

Adaptivity through Physical Immaturity

Given a neural control structure, what would be the impact of body growth on control performance? This question, which addresses the issue of the interaction between innate structure, ongoing developing structure and experience, is very relevant to the field of epigenetic robotics. Much of the early social interaction is done as the body develops and the interplay cannot be ignored. We hypothesize that starting with fewer degrees of freedom enables a more efficient exploration of the sensorimotor space, that results in multiple directions of stability. While not necessarily corresponding to optimal task performance, they will guide the coordination of additional degrees of freedom. These additional degrees of freedom then allow for optimal task performance as well as for more tolerance and adaptation to environmental interaction. We propose a simple case-study to validate our hypothesis and describe experiments with a small humanoid robot

Representation recovers information

Early agreement within cognitive science on the topic of representation has now given way to a combination of positions. Some question the significance of representation in cognition. Others continue to argue in favor, but the case has not been demonstrated in any formal way. The present paper sets out a framework in which the value of representation-use can be mathematically measured, albeit in a broadly sensory context rather than a specifically cognitive one. Key to the approach is the use of Bayesian networks for modeling the distal dimension of sensory processes. More relevant to cognitive science is the theoretical result obtained, which is that a certain type of representational architecture is *necessary* for achievement of sensory efficiency. While exhibiting few of the characteristics of traditional, symbolic encoding, this architecture corresponds quite closely to the forms of embedded representation now being explored in some embedded/embodied approaches. It becomes meaningful to view that type of representation-use as a form of information recovery. A formal basis then exists for viewing representation not so much as the substrate of reasoning and thought, but rather as a general medium for efficient, interpretive processing

The use of information theory in evolutionary biology

Information is a key concept in evolutionary biology. Information is stored in biological organism's genomes, and used to generate the organism as well as to maintain and control it. Information is also "that which evolves". When a population adapts to a local environment, information about this environment is fixed in a representative genome. However, when an environment changes, information can be lost. At the same time, information is processed by animal brains to survive in complex environments, and the capacity for information processing also evolves. Here I review applications of information theory to the evolution of proteins as well as to the evolution of information processing in simulated agents that adapt to perform a complex task.Comment: 25 pages, 7 figures. To appear in "The Year in Evolutionary Biology", of the Annals of the NY Academy of Science

Empowerment for Continuous Agent-Environment Systems

This paper develops generalizations of empowerment to continuous states. Empowerment is a recently introduced information-theoretic quantity motivated by hypotheses about the efficiency of the sensorimotor loop in biological organisms, but also from considerations stemming from curiosity-driven learning. Empowemerment measures, for agent-environment systems with stochastic transitions, how much influence an agent has on its environment, but only that influence that can be sensed by the agent sensors. It is an information-theoretic generalization of joint controllability (influence on environment) and observability (measurement by sensors) of the environment by the agent, both controllability and observability being usually defined in control theory as the dimensionality of the control/observation spaces. Earlier work has shown that empowerment has various interesting and relevant properties, e.g., it allows us to identify salient states using only the dynamics, and it can act as intrinsic reward without requiring an external reward. However, in this previous work empowerment was limited to the case of small-scale and discrete domains and furthermore state transition probabilities were assumed to be known. The goal of this paper is to extend empowerment to the significantly more important and relevant case of continuous vector-valued state spaces and initially unknown state transition probabilities. The continuous state space is addressed by Monte-Carlo approximation; the unknown transitions are addressed by model learning and prediction for which we apply Gaussian processes regression with iterated forecasting. In a number of well-known continuous control tasks we examine the dynamics induced by empowerment and include an application to exploration and online model learning

On directed information theory and Granger causality graphs

Directed information theory deals with communication channels with feedback. When applied to networks, a natural extension based on causal conditioning is needed. We show here that measures built from directed information theory in networks can be used to assess Granger causality graphs of stochastic processes. We show that directed information theory includes measures such as the transfer entropy, and that it is the adequate information theoretic framework needed for neuroscience applications, such as connectivity inference problems.Comment: accepted for publications, Journal of Computational Neuroscienc

A Theory of Cheap Control in Embodied Systems

We present a framework for designing cheap control architectures for embodied agents. Our derivation is guided by the classical problem of universal approximation, whereby we explore the possibility of exploiting the agent's embodiment for a new and more efficient universal approximation of behaviors generated by sensorimotor control. This embodied universal approximation is compared with the classical non-embodied universal approximation. To exemplify our approach, we present a detailed quantitative case study for policy models defined in terms of conditional restricted Boltzmann machines. In contrast to non-embodied universal approximation, which requires an exponential number of parameters, in the embodied setting we are able to generate all possible behaviors with a drastically smaller model, thus obtaining cheap universal approximation. We test and corroborate the theory experimentally with a six-legged walking machine. The experiments show that the sufficient controller complexity predicted by our theory is tight, which means that the theory has direct practical implications. Keywords: cheap design, embodiment, sensorimotor loop, universal approximation, conditional restricted Boltzmann machineComment: 27 pages, 10 figure

Ajulemic acid exerts potent anti-fibrotic effect during the fibrogenic phase of bleomycin lung

Background: Ajulemic acid (AjA) is a synthetic analogue of tetrahydrocannabinol that can prevent and limit progression of skin fibrosis in experimental systemic sclerosis. In this study we investigated whether AjA also prevents and modulates lung fibrosis induced by bleomycin (BLM) when administered in mice during the inflammatory or the fibrogenic phase of the model. Methods: The anti-inflammatory and antifibrotic efficacy of AjA was evaluated in DBA/2 mice treated orally once a day starting either at day 0 (preventive treatment) or at day 8 (therapeutic treatment) after a single intratracheal instillation of BLM. AjA was given at a dose of 1 mg/kg or 5 mg/kg. Mice were sacrificed at day 8, 14 and 21 after BLM and lungs were processed for histology and morphometry, and examined for HO-proline content and for the expression of transforming growth factor beta 1 (TGF-β1), phosphorylated Smad2/3 (pSMAD2/3), connective tissue growth factor (CTGF), alpha-smooth muscle actin (α-SMA) and peroxisome proliferator-activated receptor-gamma (PPAR-γ). Results: In the 1st week after BLM challenge, an acute inflammation characterized by neutrophil and macrophage accumulation was the main change present in lung parenchyma. The "switch" between inflammation and fibrosis occurs between day 8 and 14 after BLM instillation and involves the bronchi and vasculature. In the subsequent week (at day 21 after BLM instillation) bronchiolocentric fibrosis with significant increase of tissue collagen develops. The fibrotic response evaluated by morphometry and quantified as HO-proline in lung tissue at day 21 after BLM treatment was significantly reduced in mice receiving either AjA in the inflammatory or in early fibrogenic phase. AjA induces marked change in the expression pattern of products implicated in fibrogenesis, such as TGF-β1, pSMAD2/3, CTGF and α-SMA. In addition, AjA increases significantly the number of PPAR-γ positive cells and its nuclear localization. Conclusions: AjA treatment, starting either at day 0 or at day 8 after BLM challenge, counteracts the progression of pulmonary fibrosis. The anti-fibrotic effectiveness of AjA is irrespective of timing of compound administration. Further clinical studies are necessary to establish whether AjA may represent a new therapeutic option for treating fibrotic lung diseases