Name
Abstract | ||
|---|---|---|
In order to ensure simulations reproducibility, particular attention must be payed to the specification of its model. This requires adequate design methodologies, that enlightens modelers on possible implementation ambiguities - and biases - their model might have. Yet, because of not adapted knowledge representation. current reactive simulation design methodologies lack specifications concerning interaction selection, especially in stochastic behaviors. Thanks to the interaction-oriented methodology IODA - which knowledge representation is fit to handle such problems - this paper provides simple guidelines to describe interaction selection. These guidelines use a subsumption like-structure, and focus the design of interaction selection on two points : how the selection takes place - for instance first select the interaction, and then select the partner of the interaction, or first a partner and then an interaction - and the nature of each selection - for instance at random, or with a utility function. This provides a valuable communication support between modelers and computer scientists, that makes the interpretation of the model and its implementation clearer, and the identification of ambiguities and biases easier. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-3-642-00487-2_11 | 7TH INTERNATIONAL CONFERENCE ON PRACTICAL APPLICATIONS OF AGENTS AND MULTI-AGENT SYSTEMS (PAAMS 2009) |
Keywords | Field | DocType |
knowledge representation,design methodology | Data mining,Knowledge representation and reasoning,Simulation design,Computer science,Artificial intelligence,Machine learning | Conference |
Volume | ISSN | Citations |
55 | 1867-5662 | 5 |
PageRank | References | Authors |
0.67 | 8 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yoann Kubera | 1 | 92 | 11.23 |
| Philippe Mathieu | 2 | 65 | 11.34 |
| Sébastien Picault | 3 | 136 | 24.50 |