Social Cognition for Human-Robot Symbiosis—Challenges and Building Blocks

Abstract

The next generation of robot companions or robot working partners will need to satisfy social requirements somehow similar to the famous laws of robotics envisaged by Isaac Asimov time ago (Asimov, 1942). The necessary technology has almost reached the required level, including sensors and actuators, but the cognitive organization is still in its infancy and is only partially supported by the current understanding of brain cognitive processes. The brain of symbiotic robots will certainly not be a “positronic” replica of the human brain: probably, the greatest part of it will be a set of interacting computational processes running in the cloud. In this article, we review the challenges that must be met in the design of a set of interacting computational processes as building blocks of a cognitive architecture that may give symbiotic capabilities to collaborative robots of the next decades: (1) an animated body-schema; (2) an imitation machinery; (3) a motor intentions machinery; (4) a set of physical interaction mechanisms; and (5) a shared memory system for incremental symbiotic development. We would like to stress that our approach is totally un-hierarchical: the five building blocks of the shared cognitive architecture are fully bi-directionally connected. For example, imitation and intentional processes require the “services” of the animated body schema which, on the other hand, can run its simulations if appropriately prompted by imitation and/or intention, with or without physical interaction. Successful experiences can leave a trace in the shared memory system and chunks of memory fragment may compete to participate to novel cooperative actions. And so on and so forth. At the heart of the system is lifelong training and learning but, different from the conventional learning paradigms in neural networks, where learning is somehow passively imposed by an external agent, in symbiotic robots there is an element of free choice of what is worth learning, driven by the interaction between the robot and the human partner. The proposed set of building blocks is certainly a rough approximation of what is needed by symbiotic robots but we believe it is a useful starting point for building a computational framework.

Perspectives and Challenges in Robotic Neurorehabilitation

“…Moreover, new assessment methods that use modelling and only robot sensing capabilities are under development [193]. Regarding the possibility to assess psychological states, there are many studies in the human-robot interaction field [194][195][196]. In particular, the assessment of these states could be crucial to quantitatively monitoring the level of engagement and motivation of the patients.…”

Conceptualization of the Human-Machine Symbiosis – A Literature Review

“…Since then, symbiosis has been adopted by other sciences, such as psychology [28]. Licklider made use of the definition from biology and was the first to extend the term to non-biological artifacts [27,40]. Several authors emphasize that Licklider' made metamorphic use of the term symbiosis, since computers are not living entities [17,18].…”

“…A third main objective of HMS is to create humanlike communication and interaction, which is crucial to enable actors to accept each other as equal partners [39]. Humanlike communication includes both verbal (spoken and written language) and non-verbal communication (gestures, facial expressions, emotions) [40,44]. The machine has to understand the different aspects of human communication and use them in an exchange with the human.…”

“…relation system machine regarded as a partner in an equal position [2,24]. This is reflected in a balance of power: an optimal HMS operates without superior control by either side [40]. This suggests that technology supports humans but should not be seen by people as a mere means to an end.…”

The effect of interpersonal synchrony with a robot on likeability and social motivation

“…While robots are now deployed in various social contexts where they are framed as companions rather than tools (Darling, 2015;Duffy, 2000), roboticists and stakeholders are faced with the seemingly impossible challenge of making robots "truly social" (Duffy, Rooney, Hare, & Donoghue, 1999). Researchers describe this as a grand challenge with a vast problem space (Riek, 2014;Sandini et al, 2018). However, by endowing an artificial agent with socialness, patients as well as healthy individuals might benefit greatly from improved learning, companionship and therapeutic outcomes (Fasola & Matarić, 2012;Feil-Seifer & Matarić, 2011).…”