Making Sense in Participation: An Enactive Approach to Social Cognition

Most research on social understanding, in such diverse fields as developmental psychology, neuroscience, philosophy of mind, cognitive science, anthropology, linguistics and robotics, seems to have fallen into one of two categories: the one in which the interaction process (in its social and cultural aspects) is central, and the one in which individual capacities are at the focus. Even dialogue analysis and cognitive science, which intersect between the above disciplines, have most often focused on only one of these two angles: on the interaction or on the individual respectively. We argue that these two lines of approach to the question above need to be brought into correspondence with each other. We criticise existing approaches to social cognition on the basis that interactionist approaches tend to see social processes as having too much of a life of their own, while individualism sees social encounters as problems to be solved by a cogniser. A fruitful approach to the complexities of social cognition will, however, need to explore the relation between individual actions and social processes and bring them together in an integrated framework. We suggest that a story that succeeds in taking both the interaction process and the individuals involved seriously and in making progress on understanding their relationship, can be delivered by extending the enactive approach to cognition in general to the realm of social cognition. More specifically, we extend the enactive notion of sense-making into the social domain. Our argument runs like this. Enactivists characterise cognition as sense-making (Varela 1991; Thompson 2004; Di Paolo 2005), which is the active engagement with a world by a cogniser who imbues his environment with meaning and value because of this active engagement with it. Sense-making is an embodied and embedded activity, and if this is true, then movements are its tools and expressions. It is well-established that individuals can coordinate their movements intra-individually (Thelen 1981; Kelso and Clark 1982; Turvey 1990), and that such coordination is a non-mysterious and ubiquitous phenomenon in nature (Strogatz and Stewart 1993; Clayton, Sager and Will 2004). It has also been found that coordination can happen inter-individually. People can coordinate, for instance, their heartbeats (Neugebauer and Aldridge 1998) and their movements and utterances (see Kendon 1990, among others) in social settings. Interindividual coordination, moreover, seems to be a phenomenon that can be hard to avoid (Kelso 1995). Until now, no principled account of this coordination in social interaction has been put forward. We introduce a set of concepts that serves to unpack the workings of coordination in social interactions and get a better grip on it. We describe how the proposed notions can guide and inform interdisciplinary empirical research. This groundwork in the understanding of how interactors coordinate underlies our proposal regarding social understanding. We argue that, if movements are the tools and expressions of sense-making activities, and movements can be coordinated inter-individually, sense-making activities can also be coordinated. We call such coordination of sense-making participatory sense-making. Participatory sense-making is the active engagement of social agents in making and transforming meaning together (De Jaegher 2006). This approach combines the individual and interactional aspects of social understanding in that the interaction process plays a fundamental and indispensable role in the meanings generated and transformed by individuals in interaction. The individual and interactional levels emerge as having complex synchronic and diachronic relationships: social processes and individual actions in the same timescale become mutually constraining, and a developmental history of interactions changes us as individuals and makes us more prone to certain expectations and interactions

Integrating behavior and autopoiesis: An exploration in computational chemo-ethology

It has been argued that the difference between an autonomous entity and an agent is in the ability of the latter to perform behaviors supplemental to processes of self-maintenance (autopoiesis). Theories have been proposed concerning how such behaviors might relate to autopoiesis, but so far, computational models of autopoiesis have paid little attention to these relations. In this article we present a new model designed to explore the relationship between mechanisms of autopoiesis and behavior. We report on three clarifications of the theory provided by the model: (a) mechanisms of behavior can be related to mechanisms of autopoiesis while remaining operationally distinct, (b) the organization of an operationally closed system can change over time while remaining operationally closed, and (c) behavior modulation based upon autopoietic efficacy has limitations that can be avoided through the use of a partially decoupled behavioral system. Finally, we discuss questions that have surfaced during examination of the model

The tango of a load balancing biped

One of the most popular approaches to developing bipedal walking machines has been to record the human gait and use it as a template for a walking algorithm. In this paper we demonstrate a different approach based on passive dynamics, neural networks, and genetic algorithms. A bipedal machine is evolved in simulation that when pushed walks either forward or backwards just enough to release the pressure placed on it. Just as a tango dancer uses a dance frame to control the movements of their follower, external forces are a subtle way to control the machines speed. When the machine is subjected to noise in its body¿s size, weight, or actuators as well as external forces it demonstrates the ability to dynamically adapt its gait through feedback loops between its actuators and sensors

The horizons of evolutionary robotics

Evolutionary robotics (ER) aims to apply evolutionary computation techniques to the design of both real and simulated autonomous robots. The Horizons of Evolutionary Robotics offers an authoritative overview of this rapidly developing field, presenting state-of-the-art research by leading scholars. The result is a lively, expansive survey that will be of interest to computer scientists, robotics engineers, neuroscientists, and philosophers. The contributors discuss incorporating principles from neuroscience into ER; dynamical analysis of evolved agents; constructing appropriate evolutionary pathways; spatial cognition; the coevolution of robot brains and bodies; group behavior; the evolution of communication; translating evolved behavior into design principles; the development of an evolutionary robotics–based methodology for shedding light on neural processes; an incremental approach to complex tasks; and the notion of “mindless intelligence"—complex processes from immune systems to social networks—as a way forward for artificial intelligence