Publications

@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}

}

@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}

}