Conceptual structures: information processing in mind and machine
Conceptual structures: information processing in mind and machine
Principles of artificial intelligence
Principles of artificial intelligence
Tutorial on agent-based modeling and simulation part 2: how to model with agents
Proceedings of the 38th conference on Winter simulation
Graph-based Knowledge Representation: Computational Foundations of Conceptual Graphs
Graph-based Knowledge Representation: Computational Foundations of Conceptual Graphs
Handbook of Knowledge Representation
Handbook of Knowledge Representation
Image-scenarization: from conceptual models to executable simulation
Proceedings of the Winter Simulation Conference
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Agent-based modeling has been of interest to researchers for some time now. Some research has focused on the analysis and design of such software, but none has truly addressed the need for automated assistance in creating agent-based simulators from initial problem comprehension. This paper proposes an approach addressing the gap and supporting the spiral process of generating an agent-based simulator. In particular, this approach enables the incremental and iterative representation of a problem and its translation into an executable model. Initially using an unconstrained ontology, the designer draws conceptual graphs representing the problem. Progressively, graph elements are linked hierarchically under concepts that are part of a predefined generic Scenarization Vocabulary (i.e., agent, patient, behaviour, attribute, parameter, variable...). This Scenarization semantic defines roles in the simulation. This approach is part of a broader research effort known as IMAGE that develops a toolset concept supporting collaborative understanding of complex situations.