An ontological framework for knowledge modeling and decision support in cyber-physical systems

Our work is concerned with the development of knowledge structures to support correct-by-design cyber-physical systems (CPS). This class of systems is defined by a tight integration of software and physical processes, the need to satisfy stringent constraints on performance and safety, and a reliance on automation for the management of system functionality and decision making. To assure correctness of functionality with respect to requirements, there is a strong need for system models to account for semantics of the domains involved. This paper introduces a new ontological-based knowledge and reasoning framework for decision support for CPS. It enables the development of determinate, provable and executable CPS models supported by sound semantics strengthening the model-driven approach to CPS design. An investigation into the structure of basic description logics (DL) has identified the needed semantic extensions to enable the web ontology language (OWL) as the ontological language for our framework. The SROIQ DL has been found to be the most appropriate logic-based knowledge formalism as it maps to OWL 2 and ensures its decidability. Thus, correct, stable, complete and terminating reasoning algorithms are guaranteed with this SROIQ -backed language. The framework takes advantage of the commonality of data and information processing in the different domains involved to overcome the barrier of heterogeneity of domains and physics in CPS. Rules-based reasoning processes are employed. The framework provides interfaces for semantic extensions and computational support, including the ability to handle quantities for which dimensions and units are semantic parameters in the physical world. Together, these capabilities enable the conversion of data to knowledge and their effective use for efficient decision making and the study of system-level properties, especially safety. We exercise these concepts in a traffic light time-based reasoning system.

[1]  R. Firoozian.  Feedback Control Theory , 2009 .

[2]  Pavel Klinov,et al.  Practical Reasoning in Probabilistic Description Logic , 2011 .

[3]  A. Turing.  On Computable Numbers, with an Application to the Entscheidungsproblem. , 1937 .

[4]  Edward A. Lee.  The problem with threads , 2006, Computer.

[5]  Edward A. Lee,et al.  A model-based design methodology for cyber-physical systems , 2011, 2011 7th International Wireless Communications and Mobile Computing Conference.

[6]  Nancy G. Leveson,et al.  A systems-theoretic approach to safety in software-intensive systems , 2004, IEEE Transactions on Dependable and Secure Computing.

[7]  C. Lutz.  The Complexity of Reasoning with Concrete Domains , 1999 .

[8]  Edward A. Lee.  CPS foundations , 2010, Design Automation Conference.

[9]  Jae-Hyun Lee,et al.  Ontological product modeling for collaborative design , 2009, Adv. Eng. Informatics.

[10]  Simon Cox,et al.  Time Ontology in OWL , 2017 .

[11]  Hector J. Levesque,et al.  The Tractability of Subsumption in Frame-Based Description Languages , 1984, AAAI.

[12]  Gerd Folkers,et al.  On computable numbers , 2016 .

[13]  James F. Allen,et al.  What's in a Semantic Network? , 1982, ACL.

[14]  Ian Horrocks,et al.  The Even More Irresistible SROIQ , 2006, KR.

[15]  Zohar Manna,et al.  The Temporal Logic of Reactive and Concurrent Systems , 1991, Springer New York.

[16]  Mark Austin,et al.  Ontologies of Time and Time-based Reasoning for MBSE of Cyber-Physical Systems , 2013, CSER.

[17]  Yarden Katz,et al.  Pellet: A practical OWL-DL reasoner , 2007, J. Web Semant..

[18]  Franz Baader,et al.  A Scheme for Integrating Concrete Domains into Concept Languages , 1991, IJCAI.

[19]  Maurizio Lenzerini,et al.  Concept Language with Number Restrictions and Fixpoints, and its Relationship with Mu-calculus , 1994, ECAI.

[20]  Ian Horrocks,et al.  Description Logics as Ontology Languages for the Semantic Web , 2005, Mechanizing Mathematical Reasoning.

[21]  Butler W. Lampson.  Getting computers to understand , 2003, JACM.

[22]  L Burkholder,et al.  The halting problem , 1987, SIGA.

[23]  Hideaki Takeda,et al.  Physical concept ontology for the knowledge intensive engineering framework , 2004, Adv. Eng. Informatics.

[24]  John F. Sowa,et al.  Conceptual Structures: Information Processing in Mind and Machine , 1983 .

[25]  Gianfranco La Rocca,et al.  Knowledge based engineering: Between AI and CAD. Review of a language based technology to support engineering design , 2012, Adv. Eng. Informatics.

[26]  Peter Marwedel,et al.  Embedded system design , 2021, Embedded Systems.

[27]  Joseph Y. Halpern.  Reasoning about uncertainty , 2003 .

[28]  Nils J. Nilsson,et al.  Artificial Intelligence , 1974, IFIP Congress.

[29]  Marie-Laure Mugnier,et al.  Graph-based Knowledge Representation - Computational Foundations of Conceptual Graphs , 2008, Advanced Information and Knowledge Processing.

[30]  Mark Austin,et al.  Cyber-physical architecture for modeling and enhanced operations of connected-vehicle systems , 2013, 2013 International Conference on Connected Vehicles and Expo (ICCVE).

[31]  Hyoil Han,et al.  A survey on ontology mapping , 2006, SGMD.

[32]  Gregory Zacharewicz,et al.  An ontology-driven framework towards building enterprise semantic information layer , 2013, Adv. Eng. Informatics.

[33]  Weiming Shen,et al.  Systems integration and collaboration in architecture, engineering, construction, and facilities management: A review , 2010, Adv. Eng. Informatics.

[34]  Klaus Schild,et al.  Terminological Cycles and the Propositional µ-Calculus , 1994, KR.

[35]  P. Hayes.  The Logic of Frames , 1981 .

[36]  Diego Calvanese,et al.  The Description Logic Handbook: Theory, Implementation, and Applications , 2003, Description Logic Handbook.

[37]  ShenWeiming,et al.  Systems integration and collaboration in architecture, engineering, construction, and facilities management , 2010 .

[38]  Ajinkya Bhave,et al.  Multi-domain Modeling of Cyber-Physical Systems Using Architectural Views , 2010 .

[39]  Peter Marwedel,et al.  Embedded system design , 2010, Embedded Systems.

[40]  H. Chertkow,et al.  Semantic memory , 2002, Current neurology and neuroscience reports.

[41]  A. Cataldo,et al.  A constructive fixed-point theorem and the feedback semantics of timed systems , 2006, 2006 8th International Workshop on Discrete Event Systems.

[42]  Michel van Tooren,et al.  Knowledge based engineering to support complex product design , 2012, Adv. Eng. Informatics.

[43]  John F. Sowa,et al.  Principles of semantic networks , 1991 .

[44]  Edward A. Lee,et al.  Heterogeneous Concurrent Modeling and Design in Java (Volume 1: Introduction to Ptolemy II) , 2008 .

[45]  Ian Horrocks,et al.  A Description Logic with Transitive and Inverse Roles and Role Hierarchies , 1999, J. Log. Comput..

[46]  Praveen K. Paritosh.  The Heuristic Reasoning Manifesto , 2006 .

[47]  Marvin Minsky,et al.  A framework for representing knowledge , 1974 .

[48]  Klaus Schild,et al.  Terminological Cycles and the Propositional μ-Calculus**This work was supported by a grant from the Deutsche Forschungsgemeinschaft (DFG). , 1994 .

[49]  M. Sheelagh T. Carpendale,et al.  Visualization of Uncertainty and Reasoning , 2007, Smart Graphics.

[50]  Ian Horrocks,et al.  Handbook of Knowledge Representation Edited Description Logics 3.1 Introduction , 2022 .

[51]  Mark Austin,et al.  9.1.1 Semantic Platforms for Cyber‐Physical Systems , 2014 .

[52]  Paul R. Cohen,et al.  A Theory of Heuristic Reasoning About Uncertainty , 1983, AI Mag..

[53]  Janos Sztipanovits,et al.  Model Integration and Cyber Physical Systems: A Semantics Perspective , 2011, FM.

[54]  C. Papadimitriou,et al.  Introduction to the Theory of Computation , 2018 .

[55]  James F. Allen.  Maintaining knowledge about temporal intervals , 1983, CACM.

[56]  Pietro Torasso,et al.  On the Relationship between Abduction and Deduction , 1991, J. Log. Comput..

[57]  Edward A. Lee,et al.  Addressing Modeling Challenges in Cyber-Physical Systems , 2011 .

[58]  Diego Calvanese,et al.  The description logic handbook: theory , 2003 .

[59]  Timothy W. Simpson,et al.  A Methodology for Product Family Ontology Development Using Formal Concept Analysis and Web Ontology Language , 2006, J. Comput. Inf. Sci. Eng..

[60]  Tim Menzies,et al.  Applications of abduction: knowledge-level modelling , 1996, Int. J. Hum. Comput. Stud..

[61]  N. Cutland.  Computability: An Introduction to Recursive Function Theory , 1980 .

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

[63]  Ian Horrocks,et al.  A Description Logic Primer , 2012, ArXiv.

[64]  Ana Meštrović,et al.  Graph-Based Formalisms for Knowledge Representation , 2013 .