On the Causal Structure of the Sensorimotor Loop

Abstract

In recent years, the application of information theory to the field of embodied intelligence has turned out to be extremely fruitful. Here, several measures of information flow through the sensorimotor loop of an agent are of particular interest. There are mainly two ways to apply information theory to the sensorimotor setting.First, information-theoretic measures can be used within various analysis methods. Sensorimotor interactions of an embodied agent lead to the emergence of redundancy and structure of the agent's intrinsic processes. Understanding the generation of structure in the sensorimotor process and its exploitation is important within the field of embodied intelligence (Pfeifer and Bongard 2006). The quantification and analysis of information flows through an agent's sensorimotor loop from the perspective of an external observer, that is from the perspective of a scientist, proves to be effective in this regard Sporns 2005, 2006). Here, transfer entropy (Schreiber 2000) has been used in order to quantify the flows of information between various processes of the sensorimotor loop, such as the sensor process on the actuator process. Furthermore, excess entropy, also known as predictive information (Bialek et al. 2001), has been used to analyse the interplay between information-theoretic measures and behavioral patterns of embodied agents .Second, information-theoretic measures can be used as objective functions for self-organized learning. This is based on the hypothesis that learning in natural intelligent systems is partly governed by an information-theoretic optimisation principle. Corresponding studies aim at the implementation of related principles, so-called

Geometric Design Principles for Brains of Embodied Agents

“…In order to approach a general theory of embodied agents, I have introduced a formal model of the sensorimotor loop, which specifies its intrinsic and extrinsic mechanisms, building on previous work [7,13]. The extrinsic mechanisms represent the embodiment constraints of the system which can be utilised by appropriate adjustment of the intrinsic mechanisms in order to express useful behaviours.…”

“…In this article, I want to formally address the tight connection between the control architecture and the embodiment of an agent in terms of geometry, in particular information geometry [1,3]. In order to do so, I apply a theory of the sensorimotor loop in terms of a causal model, as developed in [7,13,16], and propose an approach for designing controller architectures that utilise the sensorimotor constraints. My aim is not to provide the most general results, but to exemplify the strength of the theory by integrating initial results from an existing body of work [2,4,8,12,[14][15][16]25], and discussing them, for the first time, from a unifying perspective.…”

Analysis of Soft Robotics Based on the Concept of Category of Mobility

“…R a decreased faster with TARGET A than B. Although the initial value of R a was the same for A and B, they had different spatial frequencies, as shown in equation (14). To examine the underlying behavior, Figure 4(g) shows the number of particles transferred between the regions.…”

“…This is in contrast to hard robots, where a vast and deep theoretical foundation is provided, ranging from conventional and modern control theories [11] to architectural insights such as subsumption architecture [12]. Regarding the theory for soft robots, Pfeifer et al presented an architectural analysis of the controller, mechanical system, sensory system, and task environment [3]; Brown et al performed an ad hoc but detailed dynamical system modeling of grippers [5]; Hauser et al examined the morphological computation of compliant bodies [13]; and Ay et al performed information theoretic analysis of sensorimotor loop by utilizing transfer entropy to examine the causal structures therein [14]. All of these early theoretical studies shed light on the unique aspects and properties of soft robotics.…”

Evaluating Morphological Computation in Muscle and DC-Motor Driven Models of Hopping Movements

“…For simplicity, we only discuss the sensorimotor loop for reactive systems in this work (for a detailed discussion, please see Ay and Zahedi (2014)). This is plausible, because behaviors which exploit the embodiment (e.g., walking, swimming, flying) are typically reactive.…”