An Ontology of Environments, Events, and Happenings

The paper presents our intermediate results in ontologizing a refined formal representation of environments, events, and happenings elaborated in PSI project. This ontology is used for agent-based modeling of engineering design systems and processes. Our formal approach is inspired by discrete event calculus (DEC). In difference to DEC based on discrete linear time representation, it uses fuzzy time intervals. Our framework also refines classic event calculi approaches by introducing explicit formal representations for environments and happenings as well as drawing a clear distinction between events and atomic actions. A reduced version of PSI environment, event, and happening ontology based on crisp representation of time intervals has been implemented as an OWL-DL ontology and is used in PSI design process simulation software. Fuzzy time interval based ontology is also implemented in OWL-DL and will be used in the future software versions.

[1]  James A. Hendler,et al.  Agents and the Semantic Web , 2001, IEEE Intell. Syst..

[2]  Richard B. Scherl,et al.  The logic of events , 2000, Annals of Mathematics and Artificial Intelligence.

[3]  Umberto Straccia,et al.  fuzzyDL: An expressive fuzzy description logic reasoner , 2008, 2008 IEEE International Conference on Fuzzy Systems (IEEE World Congress on Computational Intelligence).

[4]  Erik T. Mueller,et al.  Commonsense Reasoning , 2006, Qualitative Representations.

[5]  John McCarthy,et al.  SOME PHILOSOPHICAL PROBLEMS FROM THE STANDPOINT OF ARTI CIAL INTELLIGENCE , 1987 .

[6]  Adam Pease,et al.  Towards a standard upper ontology , 2001, FOIS.

[7]  Nicola Guarino,et al.  Supporting ontological analysis of taxonomic relationships , 2001, Data Knowl. Eng..

[8]  J. McCarthy.  Some Expert Systems Need Common Sense , 1984, Annals of the New York Academy of Sciences.

[9]  Hector J. Levesque,et al.  Knowledge, action, and the frame problem , 2003, Artif. Intell..

[10]  Natalya Keberle,et al.  An Agent-Oriented Model of a Dynamic Engineering Design Process , 2005, AOIS.

[11]  Erik T. Mueller,et al.  Event Calculus Reasoning Through Satisfiability , 2004, J. Log. Comput..

[12]  NICHOLAS R. JENNINGS,et al.  An agent-based approach for building complex software systems , 2001, CACM.

[13]  Vadim Ermolayev,et al.  Towards Industrial Strength Business Performance Management , 2007, HoloMAS.

[14]  James F. Allen,et al.  Actions and Events in Interval Temporal Logic , 1994 .

[15]  Raymond Reiter,et al.  The Frame Problem in the Situation Calculus: A Simple Solution (Sometimes) and a Completeness Result for Goal Regression , 1991, Artificial and Mathematical Theory of Computation.

[16]  Murray Shanahan,et al.  The Event Calculus in Classical Logic - Alternative Axiomatisations , 1999, Electron. Trans. Artif. Intell..

[17]  E. Sandewall.  Features and fluents (vol. 1): the representation of knowledge about dynamical systems , 1995 .

[18]  Natalya Keberle,et al.  Fuzzy Time Intervals for Simulating Actions , 2008, UNISCON.

[19]  Christiane Fellbaum,et al.  Book Reviews: WordNet: An Electronic Lexical Database , 1999, CL.

[20]  Marek J. Sergot,et al.  A logic-based calculus of events , 1989, New Generation Computing.

[21]  Eyck Jentzsch,et al.  Holonic Simulation of a Design System for Performance Analysis , 2007, HoloMAS.