Context-Independent Task Knowledge for Neurosymbolic Reasoning in Cognitive Robotics

One of the current main goals of artificial intelligence and robotics research is the creation of an artificial assistant which can have flexible, human like behavior, in order to accomplish everyday tasks. A lot of what is context-independent task knowledge to the human is what enables this flexibility at multiple levels of cognition. In this scope the author analyzes how to acquire, represent and disambiguate symbolic knowledge representing context-independent task knowledge, abstracted from multiple instances: this thesis elaborates the incurred problems, implementation constraints, current state-of-the-art practices and ultimately the solutions newly introduced in this scope. The author specifically discusses acquisition of context-independent task knowledge from large amounts of human-written texts and their reusability in the robotics domain; the acquisition of knowledge on human musculoskeletal dependencies constraining motion which allows a better higher level representation of observed trajectories; the means of verbalization of partial contextual and instruction knowledge, increasing interaction possibilities with the human as well as contextual adaptation. All the aforementioned points are supported by evaluation in heterogeneous setups, to bring a view on how to make optimal use of statistical & symbolic applications (i.e. neurosymbolic reasoning) in cognitive robotics. This work has been performed to enable context-adaptable artificial assistants, by bringing together knowledge on what is usually regarded as context-independent task knowledge

Archaic man meets a marvellous automaton: posthumanism, social robots, archetypes

Posthumanism is associated with critical explorations of how new technologies are rewriting our understanding of what it means to be human, and how they might alter human existence itself. Intersections with analytical psychology vary depending on which technologies are held in focus. Social robotics promises to populate everyday settings with entities that have populated the imagination for millennia. A legend of ‘A Marvellous Automaton’ appears as early as 350 B.C. in a book of Taoist teachings, and is joined by ancient and medieval legends of manmade humanoids coming to life, as well as the familiar robots of modern science fiction. However, while the robotics industry seems to be realising an archetypal fantasy, the technology creates new social realities that generate distinctive issues of potential relevance for the theory and practice of analytical psychology

The Irresistible Animacy of Lively Artefacts

This thesis explores the perception of ‘liveliness’, or ‘animacy’, in robotically driven artefacts. This perception is irresistible, pervasive, aesthetically potent and poorly understood. I argue that the Cartesian rationalist tendencies of robotic and artificial intelligence research cultures, and associated cognitivist theories of mind, fail to acknowledge the perceptual and instinctual emotional affects that lively artefacts elicit. The thesis examines how we see artefacts with particular qualities of motion to be alive, and asks what notions of cognition can explain these perceptions. ‘Irresistible Animacy’ is our human tendency to be drawn to the primitive and strangely thrilling nature of experiencing lively artefacts. I have two research methodologies; one is interdisciplinary scholarship and the other is my artistic practice of building lively artefacts. I have developed an approach that draws on first-order cybernetics’ central animating principle of feedback-control, and second-order cybernetics’ concerns with cognition. The foundations of this approach are based upon practices of machine making to embody and perform animate behaviour, both as scientific and artistic pursuits. These have inspired embodied, embedded, enactive, and extended notions of cognition. I have developed an understanding using a theoretical framework, drawing upon literature on visual perception, behavioural and social psychology, puppetry, animation, cybernetics, robotics, interaction and aesthetics. I take as a starting point, the understanding that the visual cortex of the vertebrate eye includes active feature-detection for animate agents in our environment, and actively constructs the causal and social structure of this environment. I suggest perceptual ambiguity is at the centre of all animated art forms. Ambiguity encourages natural curiosity and interactive participation. It also elicits complex visceral qualities of presence and the uncanny. In the making of my own Lively Artefacts, I demonstrate a series of different approaches including the use of abstraction, artificial life algorithms, and reactive techniques

Grounding semantic cognition using computational modelling and network analysis

The overarching objective of this thesis is to further the field of grounded semantics using a range of computational and empirical studies. Over the past thirty years, there have been many algorithmic advances in the modelling of semantic cognition. A commonality across these cognitive models is a reliance on hand-engineering “toy-models”. Despite incorporating newer techniques (e.g. Long short-term memory), the model inputs remain unchanged. We argue that the inputs to these traditional semantic models have little resemblance with real human experiences. In this dissertation, we ground our neural network models by training them with real-world visual scenes using naturalistic photographs. Our approach is an alternative to both hand-coded features and embodied raw sensorimotor signals. We conceptually replicate the mutually reinforcing nature of hybrid (feature-based and grounded) representations using silhouettes of concrete concepts as model inputs. We next gradually develop a novel grounded cognitive semantic representation which we call scene2vec, starting with object co-occurrences and then adding emotions and language-based tags. Limitations of our scene-based representation are identified for more abstract concepts (e.g. freedom). We further present a large-scale human semantics study, which reveals small-world semantic network topologies are context-dependent and that scenes are the most dominant cognitive dimension. This finding leads us to conclude that there is no meaning without context. Lastly, scene2vec shows promising human-like context-sensitive stereotypes (e.g. gender role bias), and we explore how such stereotypes are reduced by targeted debiasing. In conclusion, this thesis provides support for a novel computational viewpoint on investigating meaning - scene-based grounded semantics. Future research scaling scene-based semantic models to human-levels through virtual grounding has the potential to unearth new insights into the human mind and concurrently lead to advancements in artificial general intelligence by enabling robots, embodied or otherwise, to acquire and represent meaning directly from the environment

Stephen Harper as killer robot

In popular culture and public discourse, especially on the Internet, the image of Canada’s former Prime Minister Stephen Harper is conspicuously characterized and caricatured as robotic [...] Amidst popular culture’s hordes of anthropomorphized robots, Harper attained a peculiarly converse characterization as a robotized anthropomorph. [...] The image of Stephen Harper as killer robot figures anxieties about the automation of governance and ensuing loss of democracy. The image of Harper as robot provides a suggestive case for analyzing Canadian popular culture and the spectre of an automated body politic. This essay documents and theorizes the pattern of critical representations of the Harper government of 2006 to 2015 in popular culture, especially in digital media

Machine Performers: Agents in a Multiple Ontological State

In this thesis, the author explores and develops new attributes for machine performers and merges the trans-disciplinary fields of the performing arts and artificial intelligence. The main aim is to redefine the term “embodiment” for robots on the stage and to demonstrate that this term requires broadening in various fields of research. This redefining has required a multifaceted theoretical analysis of embodiment in the field of artificial intelligence (e.g. the uncanny valley), as well as the construction of new robots for the stage by the author. It is hoped that these practical experimental examples will generate more research by others in similar fields. Even though the historical lineage of robotics is engraved with theatrical strategies and dramaturgy, further application of constructive principles from the performing arts and evidence from psychology and neurology can shift the perception of robotic agents both on stage and in other cultural environments. In this light, the relation between representation, movement and behaviour of bodies has been further explored to establish links between constructed bodies (as in artificial intelligence) and perceived bodies (as performers on the theatrical stage). In the course of this research, several practical works have been designed and built, and subsequently presented to live audiences and research communities. Audience reactions have been analysed with surveys and discussions. Interviews have also been conducted with choreographers, curators and scientists about the value of machine performers. The main conclusions from this study are that fakery and mystification can be used as persuasive elements to enhance agency. Morphologies can also be applied that tightly couple brain and sensorimotor actions and lead to a stronger stage presence. In fact, if this lack of presence is left out of human replicants, it causes an “uncanny” lack of agency. Furthermore, the addition of stage presence leads to stronger identification from audiences, even for bodies dissimilar to their own. The author demonstrates that audience reactions are enhanced by building these effects into machine body structures: rather than identification through mimicry, this causes them to have more unambiguously biological associations. Alongside these traits, atmospheres such as those created by a cast of machine performers tend to cause even more intensely visceral responses. In this thesis, “embodiment” has emerged as a paradigm shift – as well as within this shift – and morphological computing has been explored as a method to deepen this visceral immersion. Therefore, this dissertation considers and builds machine performers as “true” performers for the stage, rather than mere objects with an aura. Their singular and customized embodiment can enable the development of non-anthropocentric performances that encompass the abstract and conceptual patterns in motion and generate – as from human performers – empathy, identification and experiential reactions in live audiences

Abstract expressions of affect

What form should happiness take? And how is disgust shaped? This research investigates how synthetic affective expressions can be designed with minimal reference to the human body. The authors propose that the recognition and attribution of affect expression can be triggered by appropriately presenting the bare essentials used in the mental processes that mediate the recognition and attribution of affect. The novelty of the proposed approach lies in the fact that it is based on mental processes involved in the recognition of affect, independent of the configuration of the human body and face. The approach is grounded in (a) research on the role of abstraction in perception, (b) the elementary processes and features relevant to visual emotion recognition and emotion attribution, and (c) how such features can be used (and combined) to generate a synthetic emotion expression. To further develop the argument for this approach they present a pilot study that shows the feasibility of combining affective features independently of the human configuration by using abstraction to create consistent emotional attributions. Finally, the authors discuss the potential implications of their approach for the design of affective robots. The developed design approach promises a maximization of freedom to integrate intuitively understandable affective expressions with other morphological design factors a technology may require, providing synthetic affective expressions that suit the inherently artificial and applied nature of affective technology

Human-Machine Communication: Complete Volume 5. Gender and Human-Machine Communication

This is the complete volume of HMC Volume

Human Machine Interaction

In this book, the reader will find a set of papers divided into two sections. The first section presents different proposals focused on the human-machine interaction development process. The second section is devoted to different aspects of interaction, with a special emphasis on the physical interaction