Speakers
University of Manchester, UK
Angelo Cangelosi is Professor of Machine Learning and Robotics at the University of Manchester (UK) and co-director and founder of the Manchester Centre for Robotics and AI. He was selected for the award of the European Research Council (ERC) Advanced grant (funded by UKRI). His research interests are in cognitive and developmental robotics, neural networks, language grounding, human robot-interaction and trust, and robot companions for health and social care. Overall, he has secured over £38m of research grants as coordinator/PI, including the ERC Advanced eTALK, the UKRI TAS Trust Node and CRADLE Prosperity, the US AFRL project THRIVE++, and numerous Horizon and MSCAs grants. Cangelosi has produced more than 300 scientific publications. He is Editor-in-Chief of the journals Interaction Studies and IET Cognitive Computation and Systems, and in 2015 was Editor-in-Chief of IEEE Transactions on Autonomous Development. He has chaired numerous international conferences, including ICANN2022 Bristol, and ICDL2021 Beijing. His book “Developmental Robotics: From Babies to Robots” (MIT Press) was published in January 2015, and translated in Chinese and Japanese. His latest book “Cognitive Robotics” (MIT Press), coedited with Minoru Asada, was recently published in 2022.
Growing theoretical and experimental psychology research
on action and language processing and on number learning and gestures in
children and adults clearly demonstrates the role of embodiment in cognition
and language processing. In psychology and neuroscience, this evidence
constitutes the basis of embodied cognition, also known as grounded cognition.
In robotics and AI, these studies have important implications for the design of
linguistic capabilities, in particular language understanding, in robots and
machines for human-robot collaboration. This focus on language acquisition and
development uses Developmental Robotics methods, as part of the wider Cognitive
Robotics approach. During the talk we will present examples of developmental
robotics models and experimental results with the baby robot iCub and with the Pepper
robot. One study focuses on the embodiment biases in early word acquisition and
grammar learning. The same developmental robotics method is used for experiments
on pointing gestures and finger counting to allow robots to learning abstract
concepts such as numbers. We will then present a novel developmental robotics model,
and human-robot interaction experiments, on Theory of Mind and its relationship
to trust. This considers both people’s Theory of Mind of robots’ capabilities,
and robot’s own ‘Artificial Theory of Mind’ of people’s intention. Results show
that trust and collaboration is enhanced when we can understand the intention
of the other agents and when robots can explain to people their decision making
strategies.
The implications for the use of such cognitive
robotics approaches for embodied cognition in AI and cognitive sciences, and
for robot companion applications will also be discussed. The talk will also
consider philosophy of science issues on embodiment and on machine’s understanding
of language, the ethical issues of trustworthy AI and robots, and the limits of
current big-data large language models.
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