Name
Abstract | ||
|---|---|---|
Imitation learning is a powerful mechanism applied by primates and humans. It allows for a straightforward acquisition of behaviours that, through observation, are known to solve everyday tasks. Recently, a Bayesian formulation has been proposed that provides a mathematical model of imitation learning. In this paper, we apply this framework to the problem of programming believable computer games characters. We will present experiments in imitation learning from the network traffic of multi-player online games. Our results underline that this indeed produces agents that behave more human-like than characters controlled by common game AI techniques. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1504/IJISTA.2007.012489 | International Journal of Intelligent Systems Technologies and Applications |
Keywords | DocType | Volume |
game character,multi-player online game,mathematical model,common game ai technique,programming believable computer game,network traffic,imitation learning,powerful mechanism,straightforward acquisition,bayesian formulation,bayesian imitation,everyday task | Conference | 2 |
Issue | Citations | PageRank |
2/3 | 4 | 1.09 |
References | Authors | |
5 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Christian Thurau | 1 | 478 | 34.19 |
| T Paczian | 2 | 221 | 21.05 |
| Gerhard Sagerer | 3 | 830 | 108.85 |
| Christian Bauckhage | 4 | 1979 | 195.86 |