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A Mind-inspired Architecture for Adaptive HRI

Bibliographic Data

ID8068066
AuthorsAlessandro Umbrico (0000-0002-1184-5944, corresponding author), Riccardo De Benedictis (0000-0003-2344-4088), Francesca Fracasso (0000-0001-9442-870X), Amedeo Cesta (0000-0002-0703-9122), Andrea Orlandini (0000-0001-6458-5202), Gabriella Cortellessa (0000-0002-9835-1575)
Year2022
Volume15
Issue3
Pages371-391
Publication date2022-07-25
Open AccessYes
TypeARTICLE
VenueInternational Journal of Social Robotics (JOURNAL)
Journal identifiersISSN: 1875-4791 • E-ISSN: 1875-4805
PublisherSpringer Science+Business Media (PUBLISHER • DE)
DOI10.1007/s12369-022-00897-8
OpenAlexW4287147246
LanguageEN
Citations received2
References cited55

One of the main challenges of social robots concerns the ability to guarantee robust, contextualized and intelligent behavior capable of supporting continuous and personalized interaction with different users over time. This implies that robot behaviors should consider the specificity of a person (e.g., personality, preferences, assistive needs), the social context as well as the dynamics of the interaction. Ideally, robots should have a “mind" to properly interact in real social environments allowing them to continuously adapt and exhibit engaging behaviors. The authors’ long-term research goal is to create an advanced mind-inspired system capable of supporting multiple assistance scenarios fostering personalization of robot’s behavior. This article introduces the idea of a dual process-inspired cognitive architecture that integrates two reasoning layers working on different time scales and making decisions over different temporal horizons. The general goal is also to support an empathetic relationship with the user through a multi-modal interaction inclusive of verbal and non-verbal expressions based on the emotional-cognitive profile of the person. The architecture is exemplified on a cognitive stimulation domain where some experiments show personalization capabilities of the approach as well as the joint work of the two layers. In particular, a feasibility assessment shows the customization of robot behaviors and the adaptation of robot interactions to the online detected state of a user. Usability sessions were performed in laboratory settings involving 10 healthy participants to assess the user interaction and the robot’s dialogue performance.

Adaptation (eye · Cognition · Cognitive architecture · Context (archaeology · Human–computer interaction · Human–robot interaction · Mobile robot · Personalization · Robot · Robot control · Robotics · Social robot · Usability · World Wide Web · AI in Service Interactions · Computer Science · Psychology · Reinforcement Learning in Robotics · Social Robot Interaction and HRI · Artificial Intelligence

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Citations per year2
Citation span2025 - 2026 (2)
Highly citedNo

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