Corrigendum: A Socially Adaptable Framework for Human-Robot Interaction

Autor: Ana Tanevska, Francesco Rea, Giulio Sandini, Lola Cañamero, Alessandra Sciutti

Publikováno v: Frontiers in Robotics and AI, Vol 8 (2021)

Externí odkaz: https://doaj.org/article/52b854602c324d6382339c789ac85f36

Inclusive HRI II

Autor: Ana Tanevska, Shruti Chandra, Giulia Barbareschi, Amy Eguchi, Zhao Han, Raj Korpan, Anastasia K. Ostrowski, Giulia Perugia, Sindhu Ravindranath, Katie Seaborn, Katie Winkle

Publikováno v: HRI '23: Companion of the 2023 ACM/IEEE International Conference on Human-Robot Interaction, Proceedings, 956-958
STARTPAGE=956;ENDPAGE=958;TITLE=HRI '23: Companion of the 2023 ACM/IEEE International Conference on Human-Robot Interaction, Proceedings

Diversity, equality, and inclusion (DEI) are critical factors that need to be considered when developing AI and robotic technologies for people. The lack of such considerations exacerbates and can also perpetuate existing forms of discrimination and

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::11453cbd1e989342a0fadebc5cadca5d
https://doi.org/10.1145/3568294.3579965

Affect-Aware Learning for Social Robots

Autor: Alessandra Sciutti, Pablo Alves De Barros, Ana Tanevska

Publikováno v: UMAP (Adjunct Publication)

Robots designed to collaborate with human partners should be able to implicitly anticipate and adapt to their needs. To do so, robots need a framework supporting cognition and mutual understanding in social settings. We posit that even basic cognitiv

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::4af6369597f93a7e855ddb1cb983c5c3
https://doi.org/10.1145/3450614.3463417

Moody Learners -- Explaining Competitive Behaviour of Reinforcement Learning Agents

Autor: Ana Tanevska, Pablo Barros, Francisco Cruz, Alessandra Sciutti

Publikováno v: 2020 Joint IEEE 10th International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob)
ICDL-EPIROB

Designing the decision-making processes of artificial agents that are involved in competitive interactions is a challenging task. In a competitive scenario, the agent does not only have a dynamic environment but also is directly affected by the oppon

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2a9174a6689bd377acea85dba547d18f

Designing an Affective Cognitive Architecture for Human-Humanoid Interaction

Autor: Ana Tanevska, Francesco Rea, Alessandra Sciutti, Giulio Sandini

Publikováno v: HRI (Companion)

Robots involved in HRI should be able to adapt to their partners by learning to select autonomously the behaviors that maximize the pleasantness of the interaction for them. To this aim, affect could play two important roles: serve as perceptual inpu

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eac8803a390d762f55fdee8d9a536fc3
https://doi.org/10.1145/3173386.3177035