AHCI RESEARCH GROUP
Publications
Papers published in international journals,
proceedings of conferences, workshops and books.
OUR RESEARCH
Scientific Publications
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You can expand the Abstract, Links and BibTex record for each paper.
2025
Li, J.; Neshaei, S. P.; Müller, L.; Rietsche, R.; Davis, R. L.; Wambsganss, T.
SpatiaLearn: Exploring XR Learning Environments for Reflective Writing Proceedings Article
In: Conf Hum Fact Comput Syst Proc, Association for Computing Machinery, 2025, ISBN: 979-840071395-8 (ISBN).
Abstract | Links | BibTeX | Tags: Adaptive Education, Conversational Agents, Conversational Tutoring, Critical thinking, Extended reality (XR), Immersive, Learning Environments, Metacognitive awareness, Reflective writing, Spatial computing
@inproceedings{li_spatialearn_2025,
title = {SpatiaLearn: Exploring XR Learning Environments for Reflective Writing},
author = {J. Li and S. P. Neshaei and L. Müller and R. Rietsche and R. L. Davis and T. Wambsganss},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105005757843&doi=10.1145%2f3706599.3719742&partnerID=40&md5=6e9ce83d3508cb377e209edd6884c505},
doi = {10.1145/3706599.3719742},
isbn = {979-840071395-8 (ISBN)},
year = {2025},
date = {2025-01-01},
booktitle = {Conf Hum Fact Comput Syst Proc},
publisher = {Association for Computing Machinery},
abstract = {Reflective writing promotes deeper learning by enhancing metacognitive awareness and critical thinking, but learners often struggle with structuring their reflections and maintaining focus. Generative AI and advances in spatial computing offer promising solutions. Extended reality (XR) environments create immersive, distraction-free settings, while conversational agents use dialog-based scaffolding guides to structure learners’ thoughts. However, research on combining dialog-based scaffolding with XR for reflective writing remains limited. To address this, we introduce SpatiaLearn, an adaptive XR tool that enhances reflective writing through conversational guidance in both traditional and immersive environments. A within-subjects study (N = 19) compared participants’ performance in traditional laptop and XR environments. Qualitative analysis shows the spatial interface enhances engagement but raises challenges like unfamiliar interactions and health concerns, requiring task adaptation for XR. This study advances the design of immersive tools for reflective writing, highlighting both the opportunities and challenges of spatial interfaces. © 2025 Copyright held by the owner/author(s).},
keywords = {Adaptive Education, Conversational Agents, Conversational Tutoring, Critical thinking, Extended reality (XR), Immersive, Learning Environments, Metacognitive awareness, Reflective writing, Spatial computing},
pubstate = {published},
tppubtype = {inproceedings}
}
Reflective writing promotes deeper learning by enhancing metacognitive awareness and critical thinking, but learners often struggle with structuring their reflections and maintaining focus. Generative AI and advances in spatial computing offer promising solutions. Extended reality (XR) environments create immersive, distraction-free settings, while conversational agents use dialog-based scaffolding guides to structure learners’ thoughts. However, research on combining dialog-based scaffolding with XR for reflective writing remains limited. To address this, we introduce SpatiaLearn, an adaptive XR tool that enhances reflective writing through conversational guidance in both traditional and immersive environments. A within-subjects study (N = 19) compared participants’ performance in traditional laptop and XR environments. Qualitative analysis shows the spatial interface enhances engagement but raises challenges like unfamiliar interactions and health concerns, requiring task adaptation for XR. This study advances the design of immersive tools for reflective writing, highlighting both the opportunities and challenges of spatial interfaces. © 2025 Copyright held by the owner/author(s).
Graziano, M.; Cante, L. Colucci; Martino, B. Di
Deploying Large Language Model on Cloud-Edge Architectures: A Case Study for Conversational Historical Characters Book Section
In: Lecture Notes on Data Engineering and Communications Technologies, vol. 250, pp. 196–205, Springer Science and Business Media Deutschland GmbH, 2025, ISBN: 23674512 (ISSN).
Abstract | Links | BibTeX | Tags: Agent based, Augmented Reality, Case-studies, Chatbots, Cloud computing architecture, Conversational Agents, EDGE architectures, Historical characters, Language Model, Modeling languages, Real time performance, WEB application, Web applications, Work analysis
@incollection{graziano_deploying_2025,
title = {Deploying Large Language Model on Cloud-Edge Architectures: A Case Study for Conversational Historical Characters},
author = {M. Graziano and L. Colucci Cante and B. Di Martino},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105002995405&doi=10.1007%2f978-3-031-87778-0_19&partnerID=40&md5=c54e9ce66901050a05de68602e4a8266},
doi = {10.1007/978-3-031-87778-0_19},
isbn = {23674512 (ISSN)},
year = {2025},
date = {2025-01-01},
booktitle = {Lecture Notes on Data Engineering and Communications Technologies},
volume = {250},
pages = {196–205},
publisher = {Springer Science and Business Media Deutschland GmbH},
abstract = {This work analyzes the deployment of conversational agents based on large language models (LLMs) in cloud-edge architectures, placing emphasis on scalability, efficiency and real-time performance. Through a case study, we present a web application that allows users to interact with an augmented reality avatar that impersonates a historical character. The agent, powered by an LLM delivers immersive and contextually coherent dialogues. We discuss the solutions adopted to manage latency and distribute the computational load between the cloud, which takes care of language processing, and the edge nodes, ensuring a smooth user experience. The results obtained demonstrate how accurate design can optimize the use of LLMs in distributed environments, offering advanced and high-performance interactions even in applications with high reactivity and customization requirements. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.},
keywords = {Agent based, Augmented Reality, Case-studies, Chatbots, Cloud computing architecture, Conversational Agents, EDGE architectures, Historical characters, Language Model, Modeling languages, Real time performance, WEB application, Web applications, Work analysis},
pubstate = {published},
tppubtype = {incollection}
}
This work analyzes the deployment of conversational agents based on large language models (LLMs) in cloud-edge architectures, placing emphasis on scalability, efficiency and real-time performance. Through a case study, we present a web application that allows users to interact with an augmented reality avatar that impersonates a historical character. The agent, powered by an LLM delivers immersive and contextually coherent dialogues. We discuss the solutions adopted to manage latency and distribute the computational load between the cloud, which takes care of language processing, and the edge nodes, ensuring a smooth user experience. The results obtained demonstrate how accurate design can optimize the use of LLMs in distributed environments, offering advanced and high-performance interactions even in applications with high reactivity and customization requirements. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
2024
Pester, A.; Tammaa, A.; Gütl, C.; Steinmaurer, A.; El-Seoud, S. A.
Conversational Agents, Virtual Worlds, and Beyond: A Review of Large Language Models Enabling Immersive Learning Proceedings Article
In: IEEE Global Eng. Edu. Conf., EDUCON, IEEE Computer Society, 2024, ISBN: 21659559 (ISSN); 979-835039402-3 (ISBN).
Abstract | Links | BibTeX | Tags: Computational Linguistics, Computer aided instruction, Conversational Agents, Education, Immersive learning, Language Model, Large language model, Learning systems, Literature reviews, LLM, Metaverse, Metaverses, Natural language processing systems, Pedagogy, Survey literature review, Virtual Reality, Virtual worlds
@inproceedings{pester_conversational_2024,
title = {Conversational Agents, Virtual Worlds, and Beyond: A Review of Large Language Models Enabling Immersive Learning},
author = {A. Pester and A. Tammaa and C. Gütl and A. Steinmaurer and S. A. El-Seoud},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85199068668&doi=10.1109%2fEDUCON60312.2024.10578895&partnerID=40&md5=1b904fd8a5e06d7ced42a328c028bbb7},
doi = {10.1109/EDUCON60312.2024.10578895},
isbn = {21659559 (ISSN); 979-835039402-3 (ISBN)},
year = {2024},
date = {2024-01-01},
booktitle = {IEEE Global Eng. Edu. Conf., EDUCON},
publisher = {IEEE Computer Society},
abstract = {Large Language Models represent a significant breakthrough in Natural Language Processing research and opened a wide range of application domains. This paper demonstrates the successful integration of Large Language Models into immersive learning environments. The review highlights how this emerging technology aligns with pedagogical principles, enhancing the effectiveness of current educational systems. It also reflects recent advancements in integrating Large Language Models, including fine-tuning, hallucination reduction, fact-checking, and human evaluation of generated results. © 2024 IEEE.},
keywords = {Computational Linguistics, Computer aided instruction, Conversational Agents, Education, Immersive learning, Language Model, Large language model, Learning systems, Literature reviews, LLM, Metaverse, Metaverses, Natural language processing systems, Pedagogy, Survey literature review, Virtual Reality, Virtual worlds},
pubstate = {published},
tppubtype = {inproceedings}
}
Large Language Models represent a significant breakthrough in Natural Language Processing research and opened a wide range of application domains. This paper demonstrates the successful integration of Large Language Models into immersive learning environments. The review highlights how this emerging technology aligns with pedagogical principles, enhancing the effectiveness of current educational systems. It also reflects recent advancements in integrating Large Language Models, including fine-tuning, hallucination reduction, fact-checking, and human evaluation of generated results. © 2024 IEEE.
Amato, N.; Carolis, B. De; Gioia, F.; Venezia, M. N.; Palestra, G.; Loglisci, C.
Can an AI-driven VTuber engage People? The KawAIi Case Study Proceedings Article
In: A., Soto; E., Zangerle (Ed.): CEUR Workshop Proc., CEUR-WS, 2024, ISBN: 16130073 (ISSN).
Abstract | Links | BibTeX | Tags: 3D Avatars, Case-studies, Conversational Agents, Facial Expressions, Language Model, Live streaming, LLM, LLMs, Real- time, Three dimensional computer graphics, Virtual agent, Virtual Reality, YouTube
@inproceedings{amato_can_2024,
title = {Can an AI-driven VTuber engage People? The KawAIi Case Study},
author = {N. Amato and B. De Carolis and F. Gioia and M. N. Venezia and G. Palestra and C. Loglisci},
editor = {Soto A. and Zangerle E.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85190754935&partnerID=40&md5=bd76d56b13e328027aa1b458849cf73f},
isbn = {16130073 (ISSN)},
year = {2024},
date = {2024-01-01},
booktitle = {CEUR Workshop Proc.},
volume = {3660},
publisher = {CEUR-WS},
abstract = {Live streaming has become increasingly popular, with most streamers presenting their real-life appearance. However, Virtual YouTubers (VTubers), virtual 2D or 3D avatars that are voiced by humans, are emerging as live streamers and attracting a growing viewership. This paper presents the development of a conversational agent, named KawAIi, embodied in a 2D character that, while accurately and promptly responding to user requests, provides an entertaining experience in streaming chat platforms such as YouTube while providing adequate real-time support. The agent relies on the Vicuna 7B GPTQ 4-bit Large Language Model (LLM). In addition, KawAIi uses a BERT-based model for analyzing the sentence generated by the model in terms of conveyed emotion and shows self-emotion awareness through facial expressions. Tested with users, the system has demonstrated a good ability to handle the interaction with the user while maintaining a pleasant user experience. In particular, KawAIi has been evaluated positively in terms of engagement and competence on various topics. The results show the potential of this technology to enrich interactivity in streaming platforms and offer a promising model for future online assistance contexts. © 2024 Copyright for this paper by its authors.},
keywords = {3D Avatars, Case-studies, Conversational Agents, Facial Expressions, Language Model, Live streaming, LLM, LLMs, Real- time, Three dimensional computer graphics, Virtual agent, Virtual Reality, YouTube},
pubstate = {published},
tppubtype = {inproceedings}
}
Live streaming has become increasingly popular, with most streamers presenting their real-life appearance. However, Virtual YouTubers (VTubers), virtual 2D or 3D avatars that are voiced by humans, are emerging as live streamers and attracting a growing viewership. This paper presents the development of a conversational agent, named KawAIi, embodied in a 2D character that, while accurately and promptly responding to user requests, provides an entertaining experience in streaming chat platforms such as YouTube while providing adequate real-time support. The agent relies on the Vicuna 7B GPTQ 4-bit Large Language Model (LLM). In addition, KawAIi uses a BERT-based model for analyzing the sentence generated by the model in terms of conveyed emotion and shows self-emotion awareness through facial expressions. Tested with users, the system has demonstrated a good ability to handle the interaction with the user while maintaining a pleasant user experience. In particular, KawAIi has been evaluated positively in terms of engagement and competence on various topics. The results show the potential of this technology to enrich interactivity in streaming platforms and offer a promising model for future online assistance contexts. © 2024 Copyright for this paper by its authors.
Hong, J.; Lee, Y.; Kim, D. H.; Choi, D.; Yoon, Y. -J.; Lee, G. -C.; Lee, Z.; Kim, J.
A Context-Aware Onboarding Agent for Metaverse Powered by Large Language Models Proceedings Article
In: A., Vallgarda; L., Jonsson; J., Fritsch; S.F., Alaoui; C.A., Le Dantec (Ed.): Proc. ACM Des. Interact. Syst. Conf., pp. 1857–1874, Association for Computing Machinery, Inc, 2024, ISBN: 979-840070583-0 (ISBN).
Abstract | Links | BibTeX | Tags: 'current, Computational Linguistics, Context- awareness, Context-Aware, context-awareness, conversational agent, Conversational Agents, Divergents, Language Model, Large-language model, large-language models, Metaverse, Metaverses, Model-based OPC, Onboarding, User interfaces, Virtual Reality
@inproceedings{hong_context-aware_2024,
title = {A Context-Aware Onboarding Agent for Metaverse Powered by Large Language Models},
author = {J. Hong and Y. Lee and D. H. Kim and D. Choi and Y. -J. Yoon and G. -C. Lee and Z. Lee and J. Kim},
editor = {Vallgarda A. and Jonsson L. and Fritsch J. and Alaoui S.F. and Le Dantec C.A.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200340104&doi=10.1145%2f3643834.3661579&partnerID=40&md5=5fe96b5155ca45c6d7a0d239b68f2b30},
doi = {10.1145/3643834.3661579},
isbn = {979-840070583-0 (ISBN)},
year = {2024},
date = {2024-01-01},
booktitle = {Proc. ACM Des. Interact. Syst. Conf.},
pages = {1857–1874},
publisher = {Association for Computing Machinery, Inc},
abstract = {One common asset of metaverse is that users can freely explore places and actions without linear procedures. Thus, it is hard yet important to understand the divergent challenges each user faces when onboarding metaverse. Our formative study (N = 16) shows that frst-time users ask questions about metaverse that concern 1) a short-term spatiotemporal context, regarding the user’s current location, recent conversation, and actions, and 2) a long-term exploration context regarding the user’s experience history. Based on the fndings, we present PICAN, a Large Language Model-based pipeline that generates context-aware answers to users when onboarding metaverse. An ablation study (N = 20) reveals that PICAN’s usage of context made responses more useful and immersive than those generated without contexts. Furthermore, a user study (N = 21) shows that the use of long-term exploration context promotes users’ learning about the locations and activities within the virtual environment. © 2024 Copyright held by the owner/author(s).},
keywords = {'current, Computational Linguistics, Context- awareness, Context-Aware, context-awareness, conversational agent, Conversational Agents, Divergents, Language Model, Large-language model, large-language models, Metaverse, Metaverses, Model-based OPC, Onboarding, User interfaces, Virtual Reality},
pubstate = {published},
tppubtype = {inproceedings}
}
One common asset of metaverse is that users can freely explore places and actions without linear procedures. Thus, it is hard yet important to understand the divergent challenges each user faces when onboarding metaverse. Our formative study (N = 16) shows that frst-time users ask questions about metaverse that concern 1) a short-term spatiotemporal context, regarding the user’s current location, recent conversation, and actions, and 2) a long-term exploration context regarding the user’s experience history. Based on the fndings, we present PICAN, a Large Language Model-based pipeline that generates context-aware answers to users when onboarding metaverse. An ablation study (N = 20) reveals that PICAN’s usage of context made responses more useful and immersive than those generated without contexts. Furthermore, a user study (N = 21) shows that the use of long-term exploration context promotes users’ learning about the locations and activities within the virtual environment. © 2024 Copyright held by the owner/author(s).
2019
Augello, Agnese; Infantino, Ignazio; Maniscalco, Umberto; Pilato, Giovanni; Vella, Filippo
Introducing NarRob, a Robotic Storyteller Proceedings Article
In: Gentile, M; Allegra, M; Sobke, H (Ed.): GAMES AND LEARNING ALLIANCE, GALA 2018, pp. 387–396, SPRINGER INTERNATIONAL PUBLISHING AG, GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND, 2019, ISBN: 978-3-030-11548-7 978-3-030-11547-0.
Abstract | Links | BibTeX | Tags: Bullying, Chatbots, Conversational Agents, Education, Robotics, Social Practices, Storytelling Robots
@inproceedings{augelloIntroducingNarRobRobotic2019,
title = {Introducing NarRob, a Robotic Storyteller},
author = { Agnese Augello and Ignazio Infantino and Umberto Maniscalco and Giovanni Pilato and Filippo Vella},
editor = { M Gentile and M Allegra and H Sobke},
doi = {10.1007/978-3-030-11548-7_36},
isbn = {978-3-030-11548-7 978-3-030-11547-0},
year = {2019},
date = {2019-01-01},
booktitle = {GAMES AND LEARNING ALLIANCE, GALA 2018},
volume = {11385},
pages = {387--396},
publisher = {SPRINGER INTERNATIONAL PUBLISHING AG},
address = {GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND},
series = {Lecture Notes in Computer Science},
abstract = {In this work we introduce NarRob, a robot able to engage in conversations and tell stories, by accompanying the speech with proper gestures. We discuss about the main components of the robot's architecture, and some possible education experiments that we are planning to carry out in real scholastic contexts.},
keywords = {Bullying, Chatbots, Conversational Agents, Education, Robotics, Social Practices, Storytelling Robots},
pubstate = {published},
tppubtype = {inproceedings}
}
In this work we introduce NarRob, a robot able to engage in conversations and tell stories, by accompanying the speech with proper gestures. We discuss about the main components of the robot's architecture, and some possible education experiments that we are planning to carry out in real scholastic contexts.
Augello, Agnese; Infantino, Ignazio; Maniscalco, Umberto; Pilato, Giovanni; Vella, Filippo
Introducing NarRob, a Robotic Storyteller Proceedings Article
In: Gentile, M; Allegra, M; Sobke, H (Ed.): GAMES AND LEARNING ALLIANCE, GALA 2018, pp. 387–396, SPRINGER INTERNATIONAL PUBLISHING AG, GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND, 2019, ISBN: 978-3-030-11548-7 978-3-030-11547-0.
Abstract | Links | BibTeX | Tags: Bullying, Chatbots, Conversational Agents, Education, Robotics, Social Practices, Storytelling Robots
@inproceedings{augello_introducing_2019,
title = {Introducing NarRob, a Robotic Storyteller},
author = {Agnese Augello and Ignazio Infantino and Umberto Maniscalco and Giovanni Pilato and Filippo Vella},
editor = {M Gentile and M Allegra and H Sobke},
doi = {10.1007/978-3-030-11548-7_36},
isbn = {978-3-030-11548-7 978-3-030-11547-0},
year = {2019},
date = {2019-01-01},
booktitle = {GAMES AND LEARNING ALLIANCE, GALA 2018},
volume = {11385},
pages = {387–396},
publisher = {SPRINGER INTERNATIONAL PUBLISHING AG},
address = {GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND},
series = {Lecture Notes in Computer Science},
abstract = {In this work we introduce NarRob, a robot able to engage in conversations and tell stories, by accompanying the speech with proper gestures. We discuss about the main components of the robot's architecture, and some possible education experiments that we are planning to carry out in real scholastic contexts.},
keywords = {Bullying, Chatbots, Conversational Agents, Education, Robotics, Social Practices, Storytelling Robots},
pubstate = {published},
tppubtype = {inproceedings}
}
In this work we introduce NarRob, a robot able to engage in conversations and tell stories, by accompanying the speech with proper gestures. We discuss about the main components of the robot's architecture, and some possible education experiments that we are planning to carry out in real scholastic contexts.
2018
Augello, Agnese; Gentile, Manuel; Dignum, Frank
An Overview of Open-Source Chatbots Social Skills Proceedings Article
In: Diplaris, S; Satsiou, A; Folstad, A; Vafopoulos, M; Vilarinho, T (Ed.): INTERNET SCIENCE, INSCI 2017, pp. 236–248, SPRINGER INTERNATIONAL PUBLISHING AG, GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND, 2018, ISBN: 978-3-319-77547-0 978-3-319-77546-3.
Abstract | Links | BibTeX | Tags: Chatbots, Conversational Agents, Social Practices
@inproceedings{augelloOverviewOpenSourceChatbots2018,
title = {An Overview of Open-Source Chatbots Social Skills},
author = { Agnese Augello and Manuel Gentile and Frank Dignum},
editor = { S Diplaris and A Satsiou and A Folstad and M Vafopoulos and T Vilarinho},
doi = {10.1007/978-3-319-77547-0_18},
isbn = {978-3-319-77547-0 978-3-319-77546-3},
year = {2018},
date = {2018-01-01},
booktitle = {INTERNET SCIENCE, INSCI 2017},
volume = {10750},
pages = {236--248},
publisher = {SPRINGER INTERNATIONAL PUBLISHING AG},
address = {GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND},
series = {Lecture Notes in Computer Science},
abstract = {This paper aims to analyze and compare some of the most known open source chatbot technologies focusing on their potential to model a conversational agent able to show a form of ``social intelligence''. The main features and drawbacks of each system will be examined. Then, we will discuss their flexibility to produce more realistic social conversational scenarios adopting as the reference the social practice theory.},
keywords = {Chatbots, Conversational Agents, Social Practices},
pubstate = {published},
tppubtype = {inproceedings}
}
This paper aims to analyze and compare some of the most known open source chatbot technologies focusing on their potential to model a conversational agent able to show a form of ``social intelligence''. The main features and drawbacks of each system will be examined. Then, we will discuss their flexibility to produce more realistic social conversational scenarios adopting as the reference the social practice theory.
Augello, Agnese; Gentile, Manuel; Dignum, Frank
An Overview of Open-Source Chatbots Social Skills Proceedings Article
In: Diplaris, S; Satsiou, A; Folstad, A; Vafopoulos, M; Vilarinho, T (Ed.): INTERNET SCIENCE, INSCI 2017, pp. 236–248, SPRINGER INTERNATIONAL PUBLISHING AG, GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND, 2018, ISBN: 978-3-319-77547-0 978-3-319-77546-3.
Abstract | Links | BibTeX | Tags: Chatbots, Conversational Agents, Social Practices
@inproceedings{augello_overview_2018,
title = {An Overview of Open-Source Chatbots Social Skills},
author = {Agnese Augello and Manuel Gentile and Frank Dignum},
editor = {S Diplaris and A Satsiou and A Folstad and M Vafopoulos and T Vilarinho},
doi = {10.1007/978-3-319-77547-0_18},
isbn = {978-3-319-77547-0 978-3-319-77546-3},
year = {2018},
date = {2018-01-01},
booktitle = {INTERNET SCIENCE, INSCI 2017},
volume = {10750},
pages = {236–248},
publisher = {SPRINGER INTERNATIONAL PUBLISHING AG},
address = {GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND},
series = {Lecture Notes in Computer Science},
abstract = {This paper aims to analyze and compare some of the most known open source chatbot technologies focusing on their potential to model a conversational agent able to show a form of “social intelligence”. The main features and drawbacks of each system will be examined. Then, we will discuss their flexibility to produce more realistic social conversational scenarios adopting as the reference the social practice theory.},
keywords = {Chatbots, Conversational Agents, Social Practices},
pubstate = {published},
tppubtype = {inproceedings}
}
This paper aims to analyze and compare some of the most known open source chatbot technologies focusing on their potential to model a conversational agent able to show a form of “social intelligence”. The main features and drawbacks of each system will be examined. Then, we will discuss their flexibility to produce more realistic social conversational scenarios adopting as the reference the social practice theory.
2016
Augello, Agnese; Gentile, Manuel; Weideveld, Lucas; Dignum, Frank
Dialogues as Social Practices for Serious Games Journal Article
In: Frontiers in Artificial Intelligence and Applications, vol. 285, pp. 1732–1733, 2016, ISSN: 09226389.
Abstract | Links | BibTeX | Tags: Artificial intelligence, Chatbots, Conversational Agents, Gamification, Serious game, Social Practices
@article{augelloDialoguesSocialPractices2016,
title = {Dialogues as Social Practices for Serious Games},
author = { Agnese Augello and Manuel Gentile and Lucas Weideveld and Frank Dignum},
editor = { Dignum F. Hullermeier E. Bouquet P. Dignum V. Fox M. van Harmelen F. Kaminka G.A.},
doi = {10.3233/978-1-61499-672-9-1732},
issn = {09226389},
year = {2016},
date = {2016-01-01},
journal = {Frontiers in Artificial Intelligence and Applications},
volume = {285},
pages = {1732--1733},
abstract = {The paper describes an architecture for a social conversational agent. The aim is to use the agent in a serious game to improve the social and communicative skills of the players, showing the social effects of conversational choices on the emotions and behavioural changes of the interlocutors.},
keywords = {Artificial intelligence, Chatbots, Conversational Agents, Gamification, Serious game, Social Practices},
pubstate = {published},
tppubtype = {article}
}
The paper describes an architecture for a social conversational agent. The aim is to use the agent in a serious game to improve the social and communicative skills of the players, showing the social effects of conversational choices on the emotions and behavioural changes of the interlocutors.
Augello, Agnese; Maniscalco, Umberto; Pilato, Giovanni; Vella, Filippo
Disaster Prevention Virtual Advisors through Soft Sensor Paradigm Journal Article
In: Smart Innovation, Systems and Technologies, vol. 55, pp. 619–627, 2016, ISSN: 21903018.
Abstract | Links | BibTeX | Tags: Artificial intelligence, Conversational Agents, Decision Support Systems, Disaster Prevention, Human computer interaction, Natural Language Processing, Ontologies, Sensor systems
@article{augelloDisasterPreventionVirtual2016,
title = {Disaster Prevention Virtual Advisors through Soft Sensor Paradigm},
author = { Agnese Augello and Umberto Maniscalco and Giovanni Pilato and Filippo Vella},
editor = { Giuseppe De Pietro and Luigi Gallo and Robert J. Howlett and Lakhmi C. Jain},
doi = {10.1007/978-3-319-39345-2_55},
issn = {21903018},
year = {2016},
date = {2016-01-01},
journal = {Smart Innovation, Systems and Technologies},
volume = {55},
pages = {619--627},
abstract = {In this paper we illustrate the architecture of an intelligent advisor agent aimed at limiting, or as far as possible preventing, the damages caused by catastrophic events, such as floods and landslides. The agent models the domain and makes forecasting by exploiting both ontology models and belief network models. Furthermore, it uses a monitoring network to recommend preventive measures and giving alerts, if necessary, before that the event happens. The monitoring network can be implemented through both physical and soft sensors: this choice makes the measurements more adequate and available also in case of failure of some of the physical sensors. The front-end of the agent is made by a chat-bot, capable to interact with human users using natural language. textcopyright Springer International Publishing Switzerland 2016.},
keywords = {Artificial intelligence, Conversational Agents, Decision Support Systems, Disaster Prevention, Human computer interaction, Natural Language Processing, Ontologies, Sensor systems},
pubstate = {published},
tppubtype = {article}
}
In this paper we illustrate the architecture of an intelligent advisor agent aimed at limiting, or as far as possible preventing, the damages caused by catastrophic events, such as floods and landslides. The agent models the domain and makes forecasting by exploiting both ontology models and belief network models. Furthermore, it uses a monitoring network to recommend preventive measures and giving alerts, if necessary, before that the event happens. The monitoring network can be implemented through both physical and soft sensors: this choice makes the measurements more adequate and available also in case of failure of some of the physical sensors. The front-end of the agent is made by a chat-bot, capable to interact with human users using natural language. textcopyright Springer International Publishing Switzerland 2016.
Augello, Agnese; Gentile, Manuel; Dignum, Frank
Social Agents for Learning in Virtual Environments Journal Article
In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10056 LNCS, pp. 133–143, 2016, ISSN: 03029743.
Abstract | Links | BibTeX | Tags: Conversational Agents, E-Learning, Education, IVA, Serious game, Social Agents, Social Context, Social Practices, Virtual Reality
@article{augelloSocialAgentsLearning2016,
title = {Social Agents for Learning in Virtual Environments},
author = { Agnese Augello and Manuel Gentile and Frank Dignum},
editor = { Jeuring J. Veltkamp R.C. Bottino R.},
doi = {10.1007/978-3-319-50182-6_12},
issn = {03029743},
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date = {2016-01-01},
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abstract = {Several serious games have been proposed to practice communication strategies in formal contexts. Intelligent virtual agents (IVA) can be used to show the player the effects of a conversational move. In this paper we discuss the key role of using social context for the virtual agents in these serious games. Social practices are exploited to bundle social interactions into standard packages and as a basis to model the deliberation processes of IVAs. We describe a social practice oriented IVA architecture used in the implementation of a serious game for the practicing of communication in medical interviews. textcopyright Springer International Publishing AG 2016.},
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Several serious games have been proposed to practice communication strategies in formal contexts. Intelligent virtual agents (IVA) can be used to show the player the effects of a conversational move. In this paper we discuss the key role of using social context for the virtual agents in these serious games. Social practices are exploited to bundle social interactions into standard packages and as a basis to model the deliberation processes of IVAs. We describe a social practice oriented IVA architecture used in the implementation of a serious game for the practicing of communication in medical interviews. textcopyright Springer International Publishing AG 2016.
Augello, Agnese; Gentile, Manuel; Dignum, Frank
Social Practices for Social Driven Conversations in Serious Games Journal Article
In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9599, pp. 100–110, 2016, ISSN: 03029743.
Abstract | Links | BibTeX | Tags: Artificial intelligence, Chatbots, Conversational Agents, Education, Serious game, Social Practices
@article{augelloSocialPracticesSocial2016,
title = {Social Practices for Social Driven Conversations in Serious Games},
author = { Agnese Augello and Manuel Gentile and Frank Dignum},
editor = { de Gloria A. Veltkamp R.},
doi = {10.1007/978-3-319-40216-1_11},
issn = {03029743},
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date = {2016-01-01},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
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abstract = {This paper describes the model of social practice as a theoretical framework to manage conversation with the specific goal of training physicians in communicative skills. To this aim, the domain reasoner that manages the conversation in the Communicate! [1] serious game is taken as a basis. Because the choice of a specific Social Practice to follow in a situation is non-trivial we use a probabilistic model for the selection of social practices as a step toward the implementation of an agent architecture compliant with the social practice model. textcopyright Springer International Publishing Switzerland 2016.},
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This paper describes the model of social practice as a theoretical framework to manage conversation with the specific goal of training physicians in communicative skills. To this aim, the domain reasoner that manages the conversation in the Communicate! [1] serious game is taken as a basis. Because the choice of a specific Social Practice to follow in a situation is non-trivial we use a probabilistic model for the selection of social practices as a step toward the implementation of an agent architecture compliant with the social practice model. textcopyright Springer International Publishing Switzerland 2016.
Augello, Agnese; Maniscalco, Umberto; Pilato, Giovanni; Vella, Filippo
Disaster prevention virtual advisors through soft sensor paradigm Journal Article
In: Smart Innovation, Systems and Technologies, vol. 55, pp. 619–627, 2016, ISSN: 21903018.
Abstract | Links | BibTeX | Tags: Artificial intelligence, Conversational Agents, Decision Support Systems, Disaster Prevention, Human computer interaction, Natural Language Processing, Ontologies, Sensor systems
@article{augello_disaster_2016,
title = {Disaster prevention virtual advisors through soft sensor paradigm},
author = {Agnese Augello and Umberto Maniscalco and Giovanni Pilato and Filippo Vella},
editor = {Giuseppe De Pietro and Luigi Gallo and Robert J. Howlett and Lakhmi C. Jain},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84977119923&doi=10.1007%2f978-3-319-39345-2_55&partnerID=40&md5=a54a699ddea48ce7e9ab353ef5ce4ba0},
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year = {2016},
date = {2016-01-01},
journal = {Smart Innovation, Systems and Technologies},
volume = {55},
pages = {619–627},
abstract = {In this paper we illustrate the architecture of an intelligent advisor agent aimed at limiting, or as far as possible preventing, the damages caused by catastrophic events, such as floods and landslides. The agent models the domain and makes forecasting by exploiting both ontology models and belief network models. Furthermore, it uses a monitoring network to recommend preventive measures and giving alerts, if necessary, before that the event happens. The monitoring network can be implemented through both physical and soft sensors: this choice makes the measurements more adequate and available also in case of failure of some of the physical sensors. The front-end of the agent is made by a chat-bot, capable to interact with human users using natural language. © Springer International Publishing Switzerland 2016.},
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In this paper we illustrate the architecture of an intelligent advisor agent aimed at limiting, or as far as possible preventing, the damages caused by catastrophic events, such as floods and landslides. The agent models the domain and makes forecasting by exploiting both ontology models and belief network models. Furthermore, it uses a monitoring network to recommend preventive measures and giving alerts, if necessary, before that the event happens. The monitoring network can be implemented through both physical and soft sensors: this choice makes the measurements more adequate and available also in case of failure of some of the physical sensors. The front-end of the agent is made by a chat-bot, capable to interact with human users using natural language. © Springer International Publishing Switzerland 2016.
Augello, Agnese; Gentile, Manuel; Dignum, Frank
Social agents for learning in virtual environments Journal Article
In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10056 LNCS, pp. 133–143, 2016, ISSN: 03029743.
Abstract | Links | BibTeX | Tags: Conversational Agents, E-Learning, Education, IVA, Serious game, Social Agents, Social Context, Social Practices, Virtual Reality
@article{augello_social_2016,
title = {Social agents for learning in virtual environments},
author = {Agnese Augello and Manuel Gentile and Frank Dignum},
editor = {Veltkamp R. C. Jeuring J. Bottino R.},
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abstract = {Several serious games have been proposed to practice communication strategies in formal contexts. Intelligent virtual agents (IVA) can be used to show the player the effects of a conversational move. In this paper we discuss the key role of using social context for the virtual agents in these serious games. Social practices are exploited to bundle social interactions into standard packages and as a basis to model the deliberation processes of IVAs. We describe a social practice oriented IVA architecture used in the implementation of a serious game for the practicing of communication in medical interviews. © Springer International Publishing AG 2016.},
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Several serious games have been proposed to practice communication strategies in formal contexts. Intelligent virtual agents (IVA) can be used to show the player the effects of a conversational move. In this paper we discuss the key role of using social context for the virtual agents in these serious games. Social practices are exploited to bundle social interactions into standard packages and as a basis to model the deliberation processes of IVAs. We describe a social practice oriented IVA architecture used in the implementation of a serious game for the practicing of communication in medical interviews. © Springer International Publishing AG 2016.
Augello, Agnese; Gentile, Manuel; Weideveld, Lucas; Dignum, Frank
Dialogues as social practices for serious games Journal Article
In: Frontiers in Artificial Intelligence and Applications, vol. 285, pp. 1732–1733, 2016, ISSN: 09226389.
Abstract | Links | BibTeX | Tags: Artificial intelligence, Chatbots, Conversational Agents, Gamification, Serious game, Social Practices
@article{augello_dialogues_2016,
title = {Dialogues as social practices for serious games},
author = {Agnese Augello and Manuel Gentile and Lucas Weideveld and Frank Dignum},
editor = {Hullermeier E. Dignum F. Kaminka G.A.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85013030288&doi=10.3233%2f978-1-61499-672-9-1732&partnerID=40&md5=74ecb65d76d015d983181d4f99fdf159},
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The paper describes an architecture for a social conversational agent. The aim is to use the agent in a serious game to improve the social and communicative skills of the players, showing the social effects of conversational choices on the emotions and behavioural changes of the interlocutors.
Augello, Agnese; Gentile, Manuel; Dignum, Frank
Social practices for social driven conversations in serious games Journal Article
In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9599, pp. 100–110, 2016, ISSN: 03029743.
Abstract | Links | BibTeX | Tags: Artificial intelligence, Chatbots, Conversational Agents, Education, Serious game, Social Practices
@article{augello_social_2016-1,
title = {Social practices for social driven conversations in serious games},
author = {Agnese Augello and Manuel Gentile and Frank Dignum},
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This paper describes the model of social practice as a theoretical framework to manage conversation with the specific goal of training physicians in communicative skills. To this aim, the domain reasoner that manages the conversation in the Communicate! [1] serious game is taken as a basis. Because the choice of a specific Social Practice to follow in a situation is non-trivial we use a probabilistic model for the selection of social practices as a step toward the implementation of an agent architecture compliant with the social practice model. © Springer International Publishing Switzerland 2016.
2014
Augello, Agnese; Pilato, Giovanni; Vassallo, Giorgio; Gaglio, Salvatore
Chatbots as Interface to Ontologies Journal Article
In: Advances in Intelligent Systems and Computing, vol. 260, pp. 285–299, 2014, ISSN: 21945357.
Abstract | Links | BibTeX | Tags: Chatbots, Conversational Agents, Knowledge Representation, Natural Language Processing, Ontologies
@article{augelloChatbotsInterfaceOntologies2014,
title = {Chatbots as Interface to Ontologies},
author = { Agnese Augello and Giovanni Pilato and Giorgio Vassallo and Salvatore Gaglio},
doi = {10.1007/978-3-319-03992-3_20},
issn = {21945357},
year = {2014},
date = {2014-01-01},
journal = {Advances in Intelligent Systems and Computing},
volume = {260},
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abstract = {Chatbots are simple conversational agents using 'pattern matching rules' to carry out the dialogue with the user and various expedients to improve their credibility. However, the rules on which they are based on are too restrictive and their language understanding capability is very limited. Nevertheless chatbots are widespread in several applications, especially to provide information to users in a new and enjoyable way. In this chapter we describe different chatbot architectures, exploiting the use of ontologies in order to create clever information suppliers overcoming the main limits of chatbots: The knowledge base building and the rigidness of the dialogue mechanism. textcopyright Springer International Publishing Switzerland 2014.},
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Chatbots are simple conversational agents using 'pattern matching rules' to carry out the dialogue with the user and various expedients to improve their credibility. However, the rules on which they are based on are too restrictive and their language understanding capability is very limited. Nevertheless chatbots are widespread in several applications, especially to provide information to users in a new and enjoyable way. In this chapter we describe different chatbot architectures, exploiting the use of ontologies in order to create clever information suppliers overcoming the main limits of chatbots: The knowledge base building and the rigidness of the dialogue mechanism. textcopyright Springer International Publishing Switzerland 2014.
Augello, Agnese; Pilato, Giovanni; Vassallo, Giorgio; Gaglio, Salvatore
Chatbots as interface to ontologies Journal Article
In: Advances in Intelligent Systems and Computing, vol. 260, pp. 285–299, 2014, ISSN: 21945357.
Abstract | Links | BibTeX | Tags: Chatbots, Conversational Agents, Knowledge Representation, Natural Language Processing, Ontologies
@article{augello_chatbots_2014,
title = {Chatbots as interface to ontologies},
author = {Agnese Augello and Giovanni Pilato and Giorgio Vassallo and Salvatore Gaglio},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84903692272&doi=10.1007%2f978-3-319-03992-3_20&partnerID=40&md5=55d82e9b0b5fdbf8176e8c168c729e14},
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abstract = {Chatbots are simple conversational agents using 'pattern matching rules' to carry out the dialogue with the user and various expedients to improve their credibility. However, the rules on which they are based on are too restrictive and their language understanding capability is very limited. Nevertheless chatbots are widespread in several applications, especially to provide information to users in a new and enjoyable way. In this chapter we describe different chatbot architectures, exploiting the use of ontologies in order to create clever information suppliers overcoming the main limits of chatbots: The knowledge base building and the rigidness of the dialogue mechanism. © Springer International Publishing Switzerland 2014.},
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Chatbots are simple conversational agents using 'pattern matching rules' to carry out the dialogue with the user and various expedients to improve their credibility. However, the rules on which they are based on are too restrictive and their language understanding capability is very limited. Nevertheless chatbots are widespread in several applications, especially to provide information to users in a new and enjoyable way. In this chapter we describe different chatbot architectures, exploiting the use of ontologies in order to create clever information suppliers overcoming the main limits of chatbots: The knowledge base building and the rigidness of the dialogue mechanism. © Springer International Publishing Switzerland 2014.
2011
Augello, Agnese; Scriminaci, Mario; Gaglio, Salvatore; Pilato, Giovanni
A Modular Framework for Versatile Conversational Agent Building Proceedings Article
In: Proceedings of the International Conference on Complex, Intelligent and Software Intensive Systems, CISIS 2011, pp. 577–582, 2011, ISBN: 978-0-7695-4373-4.
Abstract | Links | BibTeX | Tags: Conversational Agents, Intelligent Agents, Knowledge Representation, Ontologies, Semantic Computing, Semantic Spaces
@inproceedings{augelloModularFrameworkVersatile2011,
title = {A Modular Framework for Versatile Conversational Agent Building},
author = { Agnese Augello and Mario Scriminaci and Salvatore Gaglio and Giovanni Pilato},
doi = {10.1109/CISIS.2011.95},
isbn = {978-0-7695-4373-4},
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date = {2011-01-01},
booktitle = {Proceedings of the International Conference on Complex, Intelligent and Software Intensive Systems, CISIS 2011},
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abstract = {This paper illustrates a web-based infrastructure of an architecture for conversational agents equipped with a modular knowledge base. This solution has the advantage to allow the building of specific modules that deal with particular features of a conversation (ranging from its topic to the manner of reasoning of the chatbot). This enhances the agent interaction capabilities. The approach simplifies the chatbot knowledge base design process: extending, generalizing or even restricting the chatbot knowledge base in order to suit it to manage specific dialoguing tasks as much as possible. textcopyright 2011 IEEE.},
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This paper illustrates a web-based infrastructure of an architecture for conversational agents equipped with a modular knowledge base. This solution has the advantage to allow the building of specific modules that deal with particular features of a conversation (ranging from its topic to the manner of reasoning of the chatbot). This enhances the agent interaction capabilities. The approach simplifies the chatbot knowledge base design process: extending, generalizing or even restricting the chatbot knowledge base in order to suit it to manage specific dialoguing tasks as much as possible. textcopyright 2011 IEEE.
Pilato, Giovanni; Augello, Agnese; Gaglio, Salvatore
A Modular Architecture for Adaptive ChatBots Proceedings Article
In: Proceedings - 5th IEEE International Conference on Semantic Computing, ICSC 2011, pp. 177–180, 2011, ISBN: 978-0-7695-4492-2.
Abstract | Links | BibTeX | Tags: Chatbots, Conversational Agents, Intelligent Agents, Knowledge Representation, Semantic Computing
@inproceedings{pilatoModularArchitectureAdaptive2011,
title = {A Modular Architecture for Adaptive ChatBots},
author = { Giovanni Pilato and Agnese Augello and Salvatore Gaglio},
doi = {10.1109/ICSC.2011.68},
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abstract = {We illustrate an architecture for a conversational agent based on a modular knowledge representation. This solution provides intelligent conversational agents with a dynamic and flexible behavior. The modularity of the architecture allows a concurrent and synergic use of different techniques, making it possible to use the most adequate methodology for the management of a specific characteristic of the domain, of the dialogue, or of the user behavior. We show the implementation of a proof-of-concept prototype: a set of modules exploiting different knowledge representation techniques and capable to differently manage conversation features has been developed. Each module is automatically triggered through a component, named corpus callosum, whose task is to choose, time by time, the most adequate chatbot knowledge section to activate. textcopyright 2011 IEEE.},
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We illustrate an architecture for a conversational agent based on a modular knowledge representation. This solution provides intelligent conversational agents with a dynamic and flexible behavior. The modularity of the architecture allows a concurrent and synergic use of different techniques, making it possible to use the most adequate methodology for the management of a specific characteristic of the domain, of the dialogue, or of the user behavior. We show the implementation of a proof-of-concept prototype: a set of modules exploiting different knowledge representation techniques and capable to differently manage conversation features has been developed. Each module is automatically triggered through a component, named corpus callosum, whose task is to choose, time by time, the most adequate chatbot knowledge section to activate. textcopyright 2011 IEEE.
Pilato, Giovanni; Augello, Agnese; Gaglio, Salvatore
Modular Knowledge Representation in Advisor Agents for Situation Awareness Journal Article
In: International Journal of Semantic Computing, vol. 5, no. 1, pp. 33–53, 2011, ISSN: 1793351X.
Abstract | Links | BibTeX | Tags: Chatbots, Context awareness, Conversational Agents, Decision Support Systems, Knowledge Representation, Semantic Computing
@article{pilatoModularKnowledgeRepresentation2011,
title = {Modular Knowledge Representation in Advisor Agents for Situation Awareness},
author = { Giovanni Pilato and Agnese Augello and Salvatore Gaglio},
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A modular knowledge representation framework for conversational agents is presented. The approach has been realized to suit the situation awareness paradigm. The modularity of the framework makes possible the composition of specific modules that deal with particular features, simplifying both the chatbot design process and its smartness. As a proof of concepts we have developed a modular, situation awareness oriented, KB for a conversational agent, which plays the role of an advisor aimed at helping a user to be in charge of a virtual town, inspired to the SimCity series game. The agent makes an extensive use of semantic computing techniques and is able to perceive, comprehend and project consequences of actions in order to handle strategic decision under uncertainty conditions. textcopyright 2011 World Scientific Publishing Company.
Augello, Agnese; Scriminaci, Mario; Gaglio, Salvatore; Pilato, Giovanni
A modular framework for versatile conversational agent building Proceedings Article
In: Proceedings of the International Conference on Complex, Intelligent and Software Intensive Systems, CISIS 2011, pp. 577–582, 2011, ISBN: 978-0-7695-4373-4.
Abstract | Links | BibTeX | Tags: Conversational Agents, Intelligent Agents, Knowledge Representation, Ontologies, Semantic Computing, Semantic Spaces
@inproceedings{augello_modular_2011,
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This paper illustrates a web-based infrastructure of an architecture for conversational agents equipped with a modular knowledge base. This solution has the advantage to allow the building of specific modules that deal with particular features of a conversation (ranging from its topic to the manner of reasoning of the chatbot). This enhances the agent interaction capabilities. The approach simplifies the chatbot knowledge base design process: extending, generalizing or even restricting the chatbot knowledge base in order to suit it to manage specific dialoguing tasks as much as possible. © 2011 IEEE.
Pilato, Giovanni; Augello, Agnese; Gaglio, Salvatore
Modular knowledge representation in advisor agents for situation awareness Journal Article
In: International Journal of Semantic Computing, vol. 5, no. 1, pp. 33–53, 2011, ISSN: 1793351X.
Abstract | Links | BibTeX | Tags: Chatbots, Context awareness, Conversational Agents, Decision Support Systems, Knowledge Representation, Semantic Computing
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title = {Modular knowledge representation in advisor agents for situation awareness},
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A modular knowledge representation framework for conversational agents is presented. The approach has been realized to suit the situation awareness paradigm. The modularity of the framework makes possible the composition of specific modules that deal with particular features, simplifying both the chatbot design process and its smartness. As a proof of concepts we have developed a modular, situation awareness oriented, KB for a conversational agent, which plays the role of an advisor aimed at helping a user to be in charge of a virtual town, inspired to the SimCity series game. The agent makes an extensive use of semantic computing techniques and is able to perceive, comprehend and project consequences of actions in order to handle strategic decision under uncertainty conditions. © 2011 World Scientific Publishing Company.
Pilato, Giovanni; Augello, Agnese; Gaglio, Salvatore
A modular architecture for adaptive ChatBots Proceedings Article
In: Proceedings - 5th IEEE International Conference on Semantic Computing, ICSC 2011, pp. 177–180, 2011, ISBN: 978-0-7695-4492-2.
Abstract | Links | BibTeX | Tags: Chatbots, Conversational Agents, Intelligent Agents, Knowledge Representation, Semantic Computing
@inproceedings{pilato_modular_2011-1,
title = {A modular architecture for adaptive ChatBots},
author = {Giovanni Pilato and Agnese Augello and Salvatore Gaglio},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-81255172186&doi=10.1109%2fICSC.2011.68&partnerID=40&md5=dbd3f0eed38f766e910e14a22cde59d9},
doi = {10.1109/ICSC.2011.68},
isbn = {978-0-7695-4492-2},
year = {2011},
date = {2011-01-01},
booktitle = {Proceedings - 5th IEEE International Conference on Semantic Computing, ICSC 2011},
pages = {177–180},
abstract = {We illustrate an architecture for a conversational agent based on a modular knowledge representation. This solution provides intelligent conversational agents with a dynamic and flexible behavior. The modularity of the architecture allows a concurrent and synergic use of different techniques, making it possible to use the most adequate methodology for the management of a specific characteristic of the domain, of the dialogue, or of the user behavior. We show the implementation of a proof-of-concept prototype: a set of modules exploiting different knowledge representation techniques and capable to differently manage conversation features has been developed. Each module is automatically triggered through a component, named corpus callosum, whose task is to choose, time by time, the most adequate chatbot knowledge section to activate. © 2011 IEEE.},
keywords = {Chatbots, Conversational Agents, Intelligent Agents, Knowledge Representation, Semantic Computing},
pubstate = {published},
tppubtype = {inproceedings}
}
We illustrate an architecture for a conversational agent based on a modular knowledge representation. This solution provides intelligent conversational agents with a dynamic and flexible behavior. The modularity of the architecture allows a concurrent and synergic use of different techniques, making it possible to use the most adequate methodology for the management of a specific characteristic of the domain, of the dialogue, or of the user behavior. We show the implementation of a proof-of-concept prototype: a set of modules exploiting different knowledge representation techniques and capable to differently manage conversation features has been developed. Each module is automatically triggered through a component, named corpus callosum, whose task is to choose, time by time, the most adequate chatbot knowledge section to activate. © 2011 IEEE.