The development of accurate models for cyber-physical systems (CPSs) is hampered by the complexity of these systems, fundamental differences in the operation of cyber and physical components, and significant interdependencies among these components. Agent-based modeling shows promise in overcoming these challenges, due to the flexibility of software agents as autonomous and intelligent decision-making components. Semantic agent systems are even more capable, as the structure they provide facilitates the extraction of meaningful content from the data provided to the software agents. In this book chapter, we present a multi-agent model for a CPS, where the semantic capabilities are underpinned by sensor networks that provide information about the physical operation to the cyber infrastructure. As a specific example of the semantic interpretation of raw sensor data streams, we present a failure detection ontology for an intelligent water distribution network as a model CPS. The ontology represents physical entities in the CPS, as well as the information extraction, analysis and processing that takes place in relation to these entities. The chapter concludes with introduction of a semantic agent framework for CPS, and presentation of a sample implementation of the framework using C++.


Electrical and Computer Engineering


This is a post-peer-review, pre-copyedit version of an article published in Semantic Agent Systems: Foundations and Applicationsy. The final authenticated version is available online at: http://dx.doi.org/10.1007/978-3-642-18308-9_9

Keywords and Phrases

Agent-Based Modeling; Cyber-Physical Systems; Fault Detection; Intelligent Water Distribution; Multi-Agent System; Semantic Capabilities; Sensor Networks

International Standard Book Number (ISBN)

978-3642183072; 978-3642183089

International Standard Serial Number (ISSN)

1860-949X; 1860-9503

Document Type

Book - Chapter

Document Version

Accepted Manuscript

File Type





© 2011 Springer Verlag, All rights reserved.

Publication Date

01 Jan 2011