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.
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{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.
2013
Greco, Luca; Presti, Liliana Lo; Augello, Agnese; Re, Giuseppe Lo; Cascia, Marco La; Gaglio, Salvatore
A Decisional Multi-Agent Framework for Automatic Supply Chain Arrangement Journal Article
In: Studies in Computational Intelligence, vol. 439, pp. 215–232, 2013, ISSN: 1860949X.
Abstract | Links | BibTeX | Tags: Decision Support Systems
@article{grecoDecisionalMultiagentFramework2013,
title = {A Decisional Multi-Agent Framework for Automatic Supply Chain Arrangement},
author = { Luca Greco and Liliana Lo Presti and Agnese Augello and Giuseppe Lo Re and Marco La Cascia and Salvatore Gaglio},
doi = {10.1007/978-3-642-31546-6_13},
issn = {1860949X},
year = {2013},
date = {2013-01-01},
journal = {Studies in Computational Intelligence},
volume = {439},
pages = {215--232},
abstract = {In this work, a multi-agent system (MAS) for supply chain dynamic configuration is proposed. The brain of each agent is composed of a Bayesian Decision Network (BDN); this choice allows the agent for taking the best decisions estimating benefits and potential risks of different strategies, analyzing and managing uncertain information about the collaborating companies. Each agent collects information about customer's orders and current market prices, and analyzes previous experiences of collaborations with trading partners. The agent therefore performs a probabilistic inferential reasoning to filter information modeled in its knowledge base in order to achieve the best performance in the supply chain organization.},
keywords = {Decision Support Systems},
pubstate = {published},
tppubtype = {article}
}
In this work, a multi-agent system (MAS) for supply chain dynamic configuration is proposed. The brain of each agent is composed of a Bayesian Decision Network (BDN); this choice allows the agent for taking the best decisions estimating benefits and potential risks of different strategies, analyzing and managing uncertain information about the collaborating companies. Each agent collects information about customer's orders and current market prices, and analyzes previous experiences of collaborations with trading partners. The agent therefore performs a probabilistic inferential reasoning to filter information modeled in its knowledge base in order to achieve the best performance in the supply chain organization.
2011
Greco, Luca; Presti, Liliana Lo; Augello, Agnese; Re, Giuseppe Lo; Cascia, Marco La; Gaglio, Salvatore
A Multi-Agent Decision Support System for Dynamic Supply Chain Organization Proceedings Article
In: CEUR Workshop Proceedings, CEUR-WS, 2011.
Abstract | BibTeX | Tags: Decision Networks, Decision Support Systems, Dynamic Supply Chains, Information Filtering, Knowledge Representation, Multi-agent systems
@inproceedings{grecoMultiagentDecisionSupport2011,
title = {A Multi-Agent Decision Support System for Dynamic Supply Chain Organization},
author = { Luca Greco and Liliana Lo Presti and Agnese Augello and Giuseppe Lo Re and Marco La Cascia and Salvatore Gaglio},
year = {2011},
date = {2011-01-01},
booktitle = {CEUR Workshop Proceedings},
volume = {771},
publisher = {CEUR-WS},
abstract = {In this work, a multi-agent system (MAS) for supply chain dynamic configuration is proposed. The brain of each agent is composed of a Bayesian Decision Network (BDN); this choice allows the agent for taking the best decisions estimating benefits and potential risks of different strategies, analyzing and managing uncertain information about the collaborating companies. Each agent collects information about customer's orders and current market prices, and analyzes previous experiences of collaborations with trading partners. The agent therefore performs a probabilistic inferential reasoning to filter information modeled in its knowledge base in order to achieve the best performance in the supply chain organization.},
keywords = {Decision Networks, Decision Support Systems, Dynamic Supply Chains, Information Filtering, Knowledge Representation, Multi-agent systems},
pubstate = {published},
tppubtype = {inproceedings}
}
In this work, a multi-agent system (MAS) for supply chain dynamic configuration is proposed. The brain of each agent is composed of a Bayesian Decision Network (BDN); this choice allows the agent for taking the best decisions estimating benefits and potential risks of different strategies, analyzing and managing uncertain information about the collaborating companies. Each agent collects information about customer's orders and current market prices, and analyzes previous experiences of collaborations with trading partners. The agent therefore performs a probabilistic inferential reasoning to filter information modeled in its knowledge base in order to achieve the best performance in the supply chain organization.
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},
doi = {10.1142/S1793351X11001158},
issn = {1793351X},
year = {2011},
date = {2011-01-01},
journal = {International Journal of Semantic Computing},
volume = {5},
number = {1},
pages = {33--53},
abstract = {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.},
keywords = {Chatbots, Context awareness, Conversational Agents, Decision Support Systems, Knowledge Representation, Semantic Computing},
pubstate = {published},
tppubtype = {article}
}
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.
Ribino, Patrizia; Augello, Agnese; Re, Giuseppe Lo; Gaglio, Salvatore
A Knowledge Management and Decision Support Model for Enterprises Journal Article
In: Advances in Decision Sciences, vol. 2011, 2011, ISSN: 20903359.
Abstract | Links | BibTeX | Tags: Decision Support Systems, Knowledge Representation
@article{ribinoKnowledgeManagementDecision2011,
title = {A Knowledge Management and Decision Support Model for Enterprises},
author = { Patrizia Ribino and Agnese Augello and Giuseppe Lo Re and Salvatore Gaglio},
doi = {10.1155/2011/425820},
issn = {20903359},
year = {2011},
date = {2011-01-01},
journal = {Advances in Decision Sciences},
volume = {2011},
abstract = {We propose a novel knowledge management system (KMS) for enterprises. Our system exploits two different approaches for knowledge representation and reasoning: a document-based approach based on data-driven creation of a semantic space and an ontology-based model. Furthermore, we provide an expert system capable of supporting the enterprise decisional processes and a semantic engine which performs intelligent search on the enterprise knowledge bases. The decision support process exploits the Bayesian networks model to improve business planning process when performed under uncertainty. Copyright textcopyright 2011 Patrizia Ribino et al.},
keywords = {Decision Support Systems, Knowledge Representation},
pubstate = {published},
tppubtype = {article}
}
We propose a novel knowledge management system (KMS) for enterprises. Our system exploits two different approaches for knowledge representation and reasoning: a document-based approach based on data-driven creation of a semantic space and an ontology-based model. Furthermore, we provide an expert system capable of supporting the enterprise decisional processes and a semantic engine which performs intelligent search on the enterprise knowledge bases. The decision support process exploits the Bayesian networks model to improve business planning process when performed under uncertainty. Copyright textcopyright 2011 Patrizia Ribino et al.
2010
Augello, Agnese; Pilato, Giovanni; Gaglio, Salvatore
Intelligent Advisor Agents in Distributed Environments Journal Article
In: Studies in Computational Intelligence, vol. 324, pp. 109–124, 2010, ISSN: 1860949X.
Abstract | Links | BibTeX | Tags: Chatbots, Decision Support Systems, Intelligent Advisors Systems
@article{augelloIntelligentAdvisorAgents2010,
title = {Intelligent Advisor Agents in Distributed Environments},
author = { Agnese Augello and Giovanni Pilato and Salvatore Gaglio},
editor = { Soro A},
doi = {10.1007/978-3-642-16089-9_7},
issn = {1860949X},
year = {2010},
date = {2010-01-01},
journal = {Studies in Computational Intelligence},
volume = {324},
pages = {109--124},
abstract = {The chapter presents a Distributed Expert System based on a multi-agent-architecture. The system is composed of a community of intelligent conversational agents playing the role of specialized advisors for the government of a virtual town, inspired to the SimCity game. The agents are capable to handle strategic decision under uncertainty conditions. They interact in natural language with their owners, obtain information on the current status of the town and give suggestions about the best strategies to apply in order to govern the town. textcopyright 2010 Springer-Verlag Berlin Heidelberg.},
keywords = {Chatbots, Decision Support Systems, Intelligent Advisors Systems},
pubstate = {published},
tppubtype = {article}
}
The chapter presents a Distributed Expert System based on a multi-agent-architecture. The system is composed of a community of intelligent conversational agents playing the role of specialized advisors for the government of a virtual town, inspired to the SimCity game. The agents are capable to handle strategic decision under uncertainty conditions. They interact in natural language with their owners, obtain information on the current status of the town and give suggestions about the best strategies to apply in order to govern the town. textcopyright 2010 Springer-Verlag Berlin Heidelberg.
Augello, Agnese; Pilato, Giovanni; Gaglio, Salvatore
An Intelligent Advisor to Suggest Strategies in Economic Policy Decisions Proceedings Article
In: CISIS 2010 - The 4th International Conference on Complex, Intelligent and Software Intensive Systems, pp. 734–739, 2010, ISBN: 978-0-7695-3967-6.
Abstract | Links | BibTeX | Tags: Artificial intelligence, Conversational Agents, Decision Networks, Decision Support Systems, Knowledge Representation, Ontologies
@inproceedings{augelloIntelligentAdvisorSuggest2010,
title = {An Intelligent Advisor to Suggest Strategies in Economic Policy Decisions},
author = { Agnese Augello and Giovanni Pilato and Salvatore Gaglio},
doi = {10.1109/CISIS.2010.75},
isbn = {978-0-7695-3967-6},
year = {2010},
date = {2010-01-01},
booktitle = {CISIS 2010 - The 4th International Conference on Complex, Intelligent and Software Intensive Systems},
pages = {734--739},
abstract = {In this paper we illustrate the architecture of an agent that plays the role of an "intelligent advisor". The advisor is aimed at suggesting the best managing strategies for a model of a virtual town. A Decision Support System (DSS) embedded on a conversational agent constitutes the intelligent advisor architecture. Two interacting knowledge representation areas characterize the DSS. The first one deals with the description of the domain and the deterministic events through the use of ontologies. The second one deals with the management of situations characterized by uncertainty. The intelligent advisor tries to prospect the future evolutions of particular choices taken by the user, and as a consequence, suggests the player-user the best strategy given the current status of the game. textcopyright 2010 IEEE.},
keywords = {Artificial intelligence, Conversational Agents, Decision Networks, Decision Support Systems, Knowledge Representation, Ontologies},
pubstate = {published},
tppubtype = {inproceedings}
}
In this paper we illustrate the architecture of an agent that plays the role of an "intelligent advisor". The advisor is aimed at suggesting the best managing strategies for a model of a virtual town. A Decision Support System (DSS) embedded on a conversational agent constitutes the intelligent advisor architecture. Two interacting knowledge representation areas characterize the DSS. The first one deals with the description of the domain and the deterministic events through the use of ontologies. The second one deals with the management of situations characterized by uncertainty. The intelligent advisor tries to prospect the future evolutions of particular choices taken by the user, and as a consequence, suggests the player-user the best strategy given the current status of the game. textcopyright 2010 IEEE.
2009
Augello, Agnese; Pilato, Giovanni; Gaglio, Salvatore
A Conversational Agent to Support Decisions in SimCity like Games Proceedings Article
In: ICSC 2009 - 2009 IEEE International Conference on Semantic Computing, pp. 367–372, 2009, ISBN: 978-0-7695-3800-6.
Abstract | Links | BibTeX | Tags: Artificial intelligence, Conversational Agents, Decision Support Systems, Human computer interaction, Semantic Computing
@inproceedings{augelloConversationalAgentSupport2009,
title = {A Conversational Agent to Support Decisions in SimCity like Games},
author = { Agnese Augello and Giovanni Pilato and Salvatore Gaglio},
doi = {10.1109/ICSC.2009.74},
isbn = {978-0-7695-3800-6},
year = {2009},
date = {2009-01-01},
booktitle = {ICSC 2009 - 2009 IEEE International Conference on Semantic Computing},
pages = {367--372},
abstract = {Computational intelligent techniques applied to economics have played an important role in the last years. In this paper we propose a framework based on an intelligent conversational agent embedded with a decision support system, aimed at suggesting the best managing strategies for a game-based model of a virtual town. The agent tries to prospect the future evolutions of particular choices taken by the user. Interaction is conducted through a natural language interface built as an Alice-based conversational agent. textcopyright 2009 IEEE.},
keywords = {Artificial intelligence, Conversational Agents, Decision Support Systems, Human computer interaction, Semantic Computing},
pubstate = {published},
tppubtype = {inproceedings}
}
Computational intelligent techniques applied to economics have played an important role in the last years. In this paper we propose a framework based on an intelligent conversational agent embedded with a decision support system, aimed at suggesting the best managing strategies for a game-based model of a virtual town. The agent tries to prospect the future evolutions of particular choices taken by the user. Interaction is conducted through a natural language interface built as an Alice-based conversational agent. textcopyright 2009 IEEE.