Social Situatedness: Vygotsky and Beyond

The concept of ‘social situatedness’, i.e. the idea that the development of individual intelligence requires a social (and cultural) embedding, has recently received much attention in cognitive science and artificial intelligence research. The work of Lev Vygotsky who put forward this view already in the 1920s has influenced the discussion to some degree, but still remains far from well known. This paper therefore aims to give an overview of his cognitive development theory and discuss its relation to more recent work in primatology and socially situated artificial intelligence, in particular humanoid robotics

Geometric reasoning

Cognitive robot systems are ones in which sensing and representation occur, from which task plans and tactics are determined. Such a robot system accomplishes a task after being told what to do, but determines for itself how to do it. Cognition is required when the work environment is uncontrolled, when contingencies are prevalent, or when task complexity is large; it is useful in any robotic mission. A number of distinguishing features can be associated with cognitive robotics, and one emphasized here is the role of artificial intelligence in knowledge representation and in planning. While space telerobotics may elude some of the problems driving cognitive robotics, it shares many of the same demands, and it can be assumed that capabilities developed for cognitive robotics can be employed advantageously for telerobotics in general. The top level problem is task planning, and it is appropriate to introduce a hierarchical view of control. Presented with certain mission objectives, the system must generate plans (typically) at the strategic, tactical, and reflexive levels. The structure by which knowledge is used to construct and update these plans endows the system with its cognitive attributes, and with the ability to deal with contingencies, changes, unknowns, and so on. Issues of representation and reasoning which are absolutely fundamental to robot manipulation, decisions based upon geometry, are discussed here, not AI task planning per se

Cognitive Robotics

The current state of the art in cognitive robotics, covering the challenges of building AI-powered intelligent robots inspired by natural cognitive systems. A novel approach to building AI-powered intelligent robots takes inspiration from the way natural cognitive systems—in humans, animals, and biological systems—develop intelligence by exploiting the full power of interactions between body and brain, the physical and social environment in which they live, and phylogenetic, developmental, and learning dynamics. This volume reports on the current state of the art in cognitive robotics, offering the first comprehensive coverage of building robots inspired by natural cognitive systems. Contributors first provide a systematic definition of cognitive robotics and a history of developments in the field. They describe in detail five main approaches: developmental, neuro, evolutionary, swarm, and soft robotics. They go on to consider methodologies and concepts, treating topics that include commonly used cognitive robotics platforms and robot simulators, biomimetic skin as an example of a hardware-based approach, machine-learning methods, and cognitive architecture. Finally, they cover the behavioral and cognitive capabilities of a variety of models, experiments, and applications, looking at issues that range from intrinsic motivation and perception to robot consciousness. Cognitive Robotics is aimed at an interdisciplinary audience, balancing technical details and examples for the computational reader with theoretical and experimental findings for the empirical scientist

In search of a common, information-processing, agency-based framework for anthropogenic, biogenic, and abiotic cognition and intelligence

Learning from contemporary natural, formal, and social sciences, especially from biology, as well as from humanities, particularly contemporary philosophy of nature, requires updates of our old definitions of cognition and intelligence. The result of current insights into basal cognition of single cells and evolution of multicellular cognitive systems within the framework of extended evolutionary synthesis (EES) helps us better to understand mechanisms of cognition and intelligence as they appear in nature. New understanding of information and processes of physical (morphological) computation contribute to novel possibilities that can be used to inspire the development of abiotic cognitive systems (cognitive robotics), cognitive computing and artificial intelligence

Whole brain Probabilistic Generative Model toward Realizing Cognitive Architecture for Developmental Robots

Building a humanlike integrative artificial cognitive system, that is, an artificial general intelligence, is one of the goals in artificial intelligence and developmental robotics. Furthermore, a computational model that enables an artificial cognitive system to achieve cognitive development will be an excellent reference for brain and cognitive science. This paper describes the development of a cognitive architecture using probabilistic generative models (PGMs) to fully mirror the human cognitive system. The integrative model is called a whole-brain PGM (WB-PGM). It is both brain-inspired and PGMbased. In this paper, the process of building the WB-PGM and learning from the human brain to build cognitive architectures is described.Comment: 55 pages, 8 figures, submitted to Neural Network

Dewey, Enactivism and Greek Thought

In this chapter, I examine how Dewey circumnavigated debates between empiricists and a priorists by showing that active bodies can perform integrative operations traditionally attributed to “inner” mechanisms, and how he thereby realized developments at which the artificial intelligence, robotics and cognitive science communities only later arrived. Some of his ideas about experience being constituted through skills actively deployed in cultural settings were inspired by ancient Greek sources. Thus in some of his more radical moments, Dewey refined rather than invented the wheel, and I suggest that prominent embodiment figures have done the same, Dewey having anticipated them, particularly Noë and his version of enactivism. I urge that cognitive science may progress into relatively unexplored territory by traveling Dewey’s historically sensitive path

ECMR’13 Special Issue

This special issue contains extended versions of the best papers from the 6th European Conference on Mobile Robots (ECMR). ECMR is a biennial European forum, internationally open, that allows roboticists throughout Europe to become acquainted with the latest research accomplishments and innovations in mobile robotics and mobile human–robot systems. ECMR covers most aspects of mobile robotics research and machine intelligence, including (but not limited to) the following topics: multi-sensor fusion, localization, map building, navigation, active perception, behavior-based robotics, path and task planning, learning and adaptation, robot vision, human–robot interaction, cognitive robotics, experimental evaluation and benchmarking, 3D sensing, and applications of mobile robotics in land, water, air, underground, and space.Peer ReviewedPostprint (author's final draft

Assessment of Cognitive skills via Human-robot Interaction and Cloud Computing

Technological advances are increasing the range of applications for artificial intelligence, especially through its embodiment within humanoid robotics platforms. This promotes the development of novel systems for automated screening of neurological conditions to assist the clinical practitioners in the detection of early signs of mild cognitive impairments. This article presents the implementation and the experimental validation of the first robotic system for cognitive assessment, based on one of the most popular platforms for social robotics, Softbank "Pepper", which administers and records a set of multi-modal interactive tasks to engage the user cognitive abilities. The robot intelligence is programmed using the state-of-the-art IBM Watson AI Cloud services, which provide the necessary capabilities for improving the social interaction and scoring the tests. The system has been tested by healthy adults (N = 35) and we found a significant correlation between the automated scoring and the MoCA, one of the most widely used paper-and-pencil tests. We conclude that the system can be considered as a screening instrument for cognitive assessment

Intelligence without Representation: A Historical Perspective

This paper reflects on a seminal work in the history of AI and representation: Rodney Brooks’ 1991 paper Intelligence without Representation. Brooks advocated the removal of explicit representations and engineered environments from the domain of his robotic intelligence experimentation, in favour of an evolutionary-inspired approach using layers of reactive behaviour that operated independently of each other. Brooks criticised the current progress in AI research and believed that removing complex representation from AI would help address problematic areas in modelling the mind. His belief was that we should develop artificial intelligence by being guided by evolutionary development of our own intelligence, and that his approach mirrored how our own intelligence functions. Thus the field of behaviour-based robotics emerged. This paper offers a historical analysis of Brooks’ behaviour-based robotics approach and its impact in artificial intelligence and cognitive theory at the time, as well as in modern-day approaches to AI