AI*IA 2017 Advances in Artificial Intelligence

In this work we present a platform shaping citizens’ behavior in case of critical hydrogeological phenomena that can be manipulated in order to realize many possible scenarios. Here the citizens (modeled through cognitive agents) need to identify the risk of a possible critical events, relying of their information sources and of the trustworthiness attributed to them. Thanks to a training phase, the agents will be able to make a rational use of their different information sources: (a) their own evaluation about what could happen in the near future; (b) the information communicated by an authority; (c) the crowd behavior, as an evidence for evaluating the level of danger of the coming hydrogeological event. These weather forecasts are essential for the agents to deal with different meteorological events requiring adequate behaviors. In particular we consider that the authority can be more or less trustworthy and more or less able to deliver its own forecasts to the agents: due to the nature itself of the problem, these two parameters are correlated with each other. The main results of this work are: (1) it is necessary to optimize together both the authority communicativeness and trustworthiness, as optimizing just one aspect will not lead to the best solution; (2) once the authority can reach much of the population it is better to focus on its trustworthiness, since trying to give the information to a larger population could have no effect at all or even a negative effect; (3) the social source is essential to compensate the lack of information that some agents have.

[1]  Michael E. Bratman,et al.  Intention, Plans, and Practical Reason , 1991 .

[2]  Lin Padgham,et al.  Hierarchical planning in BDI agent programming languages: a formal approach , 2006, AAMAS '06.

[3]  Mehul Bhatt,et al.  Modular Ontologies for Architectural Design , 2009, FOMI.

[4]  Giancarlo Guizzardi,et al.  Grounding Software Domain Ontologies in the Unified Foundational Ontology (UFO): The case of the ODE Software Process Ontology , 2008, CIbSE.

[5]  Giancarlo Guizzardi,et al.  Ontological foundations for structural conceptual models , 2005 .

[6]  Ian Horrocks,et al.  Ontology Integration Using Mappings: Towards Getting the Right Logical Consequences , 2009, ESWC.

[7]  G. Guizzardi,et al.  The role of foundational ontologies for conceptual modeling and domain ontology representation , 2006, 2006 7th International Baltic Conference on Databases and Information Systems.

[8]  George A. Miller,et al.  WordNet: A Lexical Database for English , 1995, HLT.

[9]  Helena Sofia Pinto,et al.  Ontology Integration: How to perform the Process , 2001, OIS@IJCAI.

[10]  Giancarlo Guizzardi,et al.  OntoUML Lightweight Editor: A Model-Based Environment to Build, Evaluate and Implement Reference Ontologies , 2015, 2015 IEEE 19th International Enterprise Distributed Object Computing Workshop.

[11]  Mohamad Khalil,et al.  Ontology Learning Process as a Bottom-up Strategy for Building Domain-specific Ontology from Legal Texts , 2017, ICAART.

[12]  Giancarlo Guizzardi,et al.  Towards Ontological Foundations for Agent Modelling Concepts Using the Unified Fundational Ontology (UFO) , 2004, AOIS.

[13]  André Valente,et al.  Legal modeling and automated reasoning with ON-LINE , 1999, Int. J. Hum. Comput. Stud..

[14]  Giorgio Terracina,et al.  Experimenting with recursive queries in database and logic programming systems , 2007, Theory and Practice of Logic Programming.

[15]  Anilton Salles Garcia,et al.  An Automated Transformation from OntoUML to OWL and SWRL , 2013, ONTOBRAS.

[16]  Werner Ceusters,et al.  Aboutness: towards foundations for the Information Artifact Ontology , 2015, ICBO.

[17]  Emiliano Lorini,et al.  BDI Logics for BDI Architectures: Old Problems, New Perspectives , 2016, KI - Künstliche Intelligenz.

[18]  Rinke Hoekstra,et al.  The LKIF Core Ontology of Basic Legal Concepts , 2007, LOAIT.

[19]  Andreas Herzig,et al.  On Hierarchical Task Networks , 2016, JELIA.

[20]  Sudarsan Rachuri,et al.  An Analysis of Description Logic Augmented with Domain Rules for the Development of Product Models , 2010, J. Comput. Inf. Sci. Eng..

[21]  Hector J. Levesque,et al.  Intention is Choice with Commitment , 1990, Artif. Intell..

[22]  Ergina Kavallieratou,et al.  Unified layout analysis and text localization framework , 2017, J. Electronic Imaging.

[23]  Antonio Picariello,et al.  An approach to ontology integration for ontology reuse in knowledge based digital ecosystems , 2015, MEDES.

[24]  E. Allen Emerson,et al.  Temporal and Modal Logic , 1991, Handbook of Theoretical Computer Science, Volume B: Formal Models and Sematics.

[25]  David J. Israel,et al.  Plans and resource‐bounded practical reasoning , 1988, Comput. Intell..

[26]  Ian Horrocks,et al.  A Logical Framework for Modularity of Ontologies , 2007, IJCAI.

[27]  Trevor J. M. Bench-Capon,et al.  OWL ontology of basic legal concepts (LKIF-Core) , 2007 .

[28]  Robert Tolksdorf,et al.  Case Studies on Ontology Reuse , 2005 .

[29]  Chitta Baral,et al.  Reasoning about Intended Actions , 2005, AAAI.

[30]  Boris Motik,et al.  OWL 2: The next step for OWL , 2008, J. Web Semant..

[31]  C. Maria Keet The Use of Foundational Ontologies in Ontology Development: An Empirical Assessment , 2011, ESWC.

[32]  Denis Poitrenaud,et al.  SPOT: an extensible model checking library using transition-based generalized Bu/spl uml/chi automata , 2004, The IEEE Computer Society's 12th Annual International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunications Systems, 2004. (MASCOTS 2004). Proceedings..

[33]  Guido Governatori,et al.  Logic of Violations: A gentzen systems for reasoning with contrary-to-duty obligations , 2006 .

[34]  Daniel Alami,et al.  Process Modeling Using Event-Driven Process Chains , 2016 .

[35]  N. Shilov Designing tableau-like axiomatization for Propositional Linear Temporal Logic at home of Arthur Prior , 2006 .

[36]  Yoav Shoham,et al.  Logical Theories of Intention and the Database Perspective , 2009, J. Philos. Log..

[37]  Weiru Liu,et al.  A Concept Hierarchy Based Ontology Mapping Approach , 2010, KSEM.

[38]  Jérôme Euzenat,et al.  Semantic Precision and Recall for Ontology Alignment Evaluation , 2007, IJCAI.

[39]  Vojtech Rehák,et al.  LTL to Büchi Automata Translation: Fast and More Deterministic , 2012, TACAS.

[40]  Eva Söderström,et al.  Towards a Framework for Comparing Process Modelling Languages , 2002, CAiSE.

[41]  Tom Bylander,et al.  The Computational Complexity of Propositional STRIPS Planning , 1994, Artif. Intell..

[42]  E. Clarke,et al.  Symbolic model checking using SAT procedures instead of BDDs , 1999, Proceedings 1999 Design Automation Conference (Cat. No. 99CH36361).

[43]  Gerd Wagner,et al.  Towards Ontological Foundations for the Conceptual Modeling of Events , 2013, ER.

[44]  Benjamin N. Grosof,et al.  Combining Rules and Ontologies . A survey . , 2005 .

[45]  Luciano Serafini,et al.  Distributed Description Logics: Assimilating Information from Peer Sources , 2003, J. Data Semant..

[46]  Gerd Wagner,et al.  Using the Unified Foundational Ontology (UFO) as a Foundation for General Conceptual Modeling Languages , 2010 .

[47]  Antonino Rotolo,et al.  An OWL Ontology of Fundamental Legal Concepts , 2006, JURIX.

[48]  Dongmo Zhang,et al.  Refinement of Intentions , 2016, JELIA.

[49]  Edmund M. Clarke,et al.  Symbolic Model Checking: 10^20 States and Beyond , 1990, Inf. Comput..

[50]  Friedrich M. Wahl,et al.  Document Analysis System , 1982, IBM J. Res. Dev..

[51]  Ivo Düntsch,et al.  A note on proximity spaces and connection based mereology , 2001, FOIS.