| id | title | desc | updated | created |
|---|---|---|---|---|
73kcj3ohj07u985kspptsjx |
An Ontology for Agent Based Modeling and Simulation |
1720932297673 |
1720291330115 |
- https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=7db660023a2734b826b6dde61f8c18e8ce146da8
- authors: @scott-christley, @xiaorong-xiang, @greg-madey
- keywords: [[t.cs.agents.agent-based-modeling]], [[t.cs.agents.agent-based-simulation]], [[t.cs.ai.automated-reasoning]], [[t.km.ontology]], [[t.cs.simulation.discrete-event]]
Ontologies are a formal methodology for establishing a common vocabulary, for defining the concepts and relationships between those concepts of a particular domain, and for reasoning about the objects, behaviors, and knowledge that comprises the domain. In this paper, we present an ontology for agent-based modeling and simulation. Agent-based modeling and simulation has become an important and popular paradigm for the computational social and natural sciences; however, the application of this paradigm tends to be performed in an ad-hoc fashion leading to questions about underlying assumptions in an agent-based model, verification of the software implementation as a representation of that model, and validation of hypothesized conclusions inferred from data produced by computer simulation experiments. An ontology provides a formal, logical knowledge representation that supports automated reasoning. Such reasoning capability provides for consistency checking of the concepts and relationships in an agent-based model, can infer the assumptions inherent in a model, can infer the assumptions and the parameters inherent in a simulation or software representation of a model, and can enforce adherence to formal methods or best practices for verification and validation testing. These reasoning tasks direct, or at least inform, the modeler about relevant techniques and methods in the agent-based paradigm. The reasoning capability also provides a framework for automated generation of software code, automated design and execution of simulation experiments as well as automated generation and execution of validation tests for those experiments. Using the standard Ontology Web Language (OWL), we provide a complete, detailed ontology of agent-based modeling and simulation, and we show how the ontology is used as part of the modeling and simulation process.
ABDESO, a foundational ontology for agent-based discrete event simulation