Name
Abstract | ||
|---|---|---|
The computational cost of large-scale multi-agent based simulations (MABS) can be extremely important, especially if simulations have to be monitored for validation purposes. In this paper, two methods, based on self-observation and statistical survey theory, are introduced in order to optimize the computation of observations in MABS. An empirical comparison of the computational cost of these methods is performed on a toy problem. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1007/978-3-642-28400-7_8 | MABS'11 Proceedings of the 12th international conference on Multi-Agent-Based Simulation |
Keywords | DocType | Volume |
empirical comparison,validation purpose,computational cost,toy problem,statistical survey theory,large-scale multi-agent,scalability,observation methods | Journal | abs/1311.0758 |
ISSN | Citations | PageRank |
Multi-Agent-Based Simulation XII, LNCS 7124, 2012, pp 103-112 | 0 | 0.34 |
References | Authors | |
8 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gildas Morvan | 1 | 31 | 7.10 |
| Alexandre Veremme | 2 | 9 | 1.52 |
| Daniel Dupont | 3 | 23 | 2.56 |