Dr. Agnese Augello
Institute for High Performance Computing and Networking ( ICAR ), National Research Council (CNR), Italy
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Academic Career Length
17Years (2010-Present)
(Calculated once Scilit publication data is synced: current year − year of first publication + 1)
Representative Publications
View All Publications22 December 2021 in International Journal of Social Robotics
Journal Article
Agnese AugelloGCGiuseppe Città
Giuseppe CittàMGManuel Gentile
Manuel GentileALAntonio Lieto
Antonio LietoWe present a storytelling robot, controlled via the ACT-R cognitive architecture, able to adopt different persuasive techniques and ethical stances while conversing about some topics concerning COVID-19. The main contribution of the paper consists in the proposal of a needs-driven model that guides and evaluates, during the dialogue, the use (if any) of persuasive techniques available in the agent procedural memory. The portfolio of persuasive techniques tested in such a model ranges from the use of storytelling to framing techniques and rhetorical-based arguments. To the best of our knowledge, this represents the first attempt of building a persuasive agent able to integrate a mix of explicitly grounded cognitive assumptions about dialogue management, storytelling and persuasive techniques as well as ethical attitudes. The paper presents the results of an exploratory evaluation of the system on 63 participants.
1 January 2016 in Biologically Inspired Cognitive Architectures
Journal Article
Agnese AugelloIIIgnazio Infantino
Ignazio Infantino
ALAntonio Lieto
Antonio Lieto
Giovanni Pilato
Riccardo RizzoFVFilippo Vella
Filippo Vella
Journal Article
Agnese AugelloIIIgnazio Infantino
Ignazio InfantinoGiovanni Pilato
Gianpaolo VitaleThis paper deals with innovative fruition modalities of cultural heritage sites. Based on two ongoing experiments, four pillars are considered, that is, User Localization, Multimodal Interaction, User Understanding and Gamification. A survey of the existing literature regarding one or more issues related to the four pillars is proposed. It aims to put in evidence the exploitation of these contributions to cultural heritage. It is discussed how a cultural site can be enriched, extended and transformed into an intelligent multimodal environment in this perspective. This new augmented environment can focus on the visitor, analyze his activity and behavior, and make his experience more satisfying, fulfilling and unique. After an in-depth overview of the existing technologies and methodologies for the fruition of cultural interest sites, the two experiments are described in detail and the authors’ vision of the future is proposed.
Journal Article
ABAdriana Bono
Adriana BonoAgnese AugelloGiovanni Pilato
Filippo VellaSGSalvatore Gaglio
Salvatore GaglioThis paper describes an interactive storytelling system, accessible through the SoftBank robotic platforms NAO and Pepper. The main contribution consists of the interpretation of the story characters by humanoid robots, obtained through the definition of appropriate cognitive models, relying on the ACT-R cognitive architecture. The reasoning processes leading to the story evolution are based on the represented knowledge and the suggestions of the listener in critical points of the story. They are disclosed during the narration, to make clear the dynamics of the story and the feelings of the characters. We analyzed the impact of such externalization of the internal status of the characters to set the basis for future experimentation with primary school children.
1 June 2014
Conference Paper
In this paper we propose a simple and completely automatic methodology for analyzing sentiment of users in Twitter. Firstly, we built a Twitter corpus by grouping tweets expressing positive and negative polarity through a completely automatic procedure by using only emoticons in tweets. Then, we have built a simple sentiment classifier where an actual stream of tweets from Twitter is processed and its content classified as positive, negative or neutral. The classification is made without the use of any pre-defined polarity lexicon. The lexicon is automatically inferred from the streaming of tweets. Experimental results show that our method reduces human intervention and, consequently, the cost of the whole classification process. We observe that our simple system captures polarity distinctions matching reasonably well the classification done by human judges.
4 June 2016
Book Chapter
Agnese AugelloMGManuel Gentile
Manuel GentileLWLucas Weideveld
Lucas Weideveld
FDFrank Dignum
Frank Dignum
About Me
Agnese Augello is a Research Scientist at the National Research Council of Italy (CNR), Institute for High-Performance Computing and Networking (ICAR). She received a Laurea degree in Computer Engineering (cum laude) from the University of Palermo and achieved, in 2008, a PhD degree in Computer Science Engineering. From 2008 to 2014 and from 2018 to 2022, she was an adjunct professor at the University of Palermo; from 2019 to 2022, she was a Reference Professor at DAMS, University of Palermo. Her main research interest regards the modelling of cognitive agents, with a particular focus on issues regarding the modelling and implementation of cognitive architectures, conversational modules, and methodologies for the representation and processing of knowledge at multiple levels of abstraction. Her research activity also deals with the modelling of higher-level capabilities, such as computational creativity and ethical behaviour.