Laura Cohen

Cergy-Pontoise University

Owing to the recent success of Large Language Models, Modern A.I has been much focused on linguistic interactions with humans but less focused on non-linguistic forms of communication between man and machine. In the present paper, we test how affective-linguistic communication, in combination with differential outcomes training, affects mutual lear...

This paper presents a novel human-robot interaction setup for robot and human learning of symbolic language for identifying robot homeostatic needs. The robot and human learn to use and respond to the same language symbols that convey homeostatic needs and the stimuli that satisfy the homeostatic needs, respectively. We adopted a differential outco...

Language acquisition theories classically distinguish passive language understanding from active language production. However, recent findings show that brain areas such as Broca's region are shared in language understanding and production. Furthermore, these areas are also implicated in understanding and producing goal-oriented actions. These obse...

Manipulation at micro and nano scales is a particular case for remote handling. Although novel robotic approaches emerge, these tools are not yet commonly adopted due to their inherent complexity and their lack of user-friendly interfaces. In order to fill this gap, this work first introduces a novel paradigm dubbed semi-autonomous. Its aim is to c...

The aim of the present study was to explore how schizophrenia patients attribute mind to a humanoid robot compared to healthy individuals. Results show that if there is no doubt that robots could assist schizophrenia patients in a variety of their living daily tasks, mind perception and other social cognition deficits could negatively impact their...

Rapid progress in the area of humanoid robots offers tremendous possibilities for investigating and improving social competences in people with social deficits, but remains yet unexplored in schizophrenia. In this study, we examined the influence of social feedbacks elicited by a humanoid robot on motor coordination during a human-robot interaction...

Mirror game test could detect schizophrenia A new test of movement and social interaction could detect markers of schizophrenia, and help to diagnose and manage the condition. In an effort to establish reliable indicators of schizophrenia, Piotr Slowinski at the University of Exeter, UK and colleagues developed a test that could detect deficits in...

Among the symptoms of schizophrenia, deficits in the recognition of intention is one of the most studied. However, there is no cognitive model of intention recognition that takes into account both innate and environmental/developmental factors. This work proposes a developmental model of intention recognition based on a neural network. This model e...

Humans are experts in understanding others' intention. This capacity is essential to interact and collaborate with others. Thus, providing a robot with this capacity is a key improvement for further developments in socially interactive robotics. This work exploits a mirroring scenario between aa caregiver and a robot to develop an intention inferen...

Humans are experts in understanding others' intention. This capacity is essential to interact and collaborate with others. Thus, providing a robot with this capacity is a key improvement for further developments in socially interactive robotics. This work exploits a mirroring scenario between aa caregiver and a robot to develop an intention inferen...

Micromanipulation tools are not yet commonly used in the industry or in the research due to the lack of natural and intuitive human-computer interfaces. This work proposes a vision based approach using a Kinect RGB-Depth sensor to provide a "metaphor-free" interface. An intention prediction approach is proposed, based on a cognitive science computa...

Micromanipulation tools are not yet commonly used in the industry or in the research due to the lack of natural and intuitive human-computer interfaces. This work proposes a vision based approach using a Kinect RGB-Depth sensor to provide a “metaphor-free” interface. An intention prediction approach is proposed, based on a cognitive science computa...