Real-time learning in the NERO video game

Real-time learning in the NERO video game (2005)

Cached

Download Links

[nn.cs.utexas.edu]

Other Repositories/Bibliography

DBLP

by Kenneth O. Stanley , Ryan Cornelius , Risto Miikkulainen , Aliza Gold

Venue:	In Proceedings of the Artificial Intelligence and Interactive Digital Entertainment Conference (AIIDE 2005) Demo Papers
Citations:	3 - 1 self

Versions

Version History

Metadata Version 1

Datum	Value	Source
TITLE	Real-time learning in the NERO video game	INFERENCE
AUTHOR NAME	Kenneth O. Stanley	SVM HeaderParse 0.2
AUTHOR AFFIL	Department of Computer Sciences, The University of Texas at Austin, Austin	SVM HeaderParse 0.2
AUTHOR ADDR	TX 78712-0233 USA	SVM HeaderParse 0.2
AUTHOR NAME	Ryan Cornelius	SVM HeaderParse 0.2
AUTHOR AFFIL	Department of Computer Sciences, The University of Texas at Austin, Austin	SVM HeaderParse 0.2
AUTHOR ADDR	TX 78712-0233 USA	SVM HeaderParse 0.2
AUTHOR NAME	Risto Miikkulainen	SVM HeaderParse 0.2
AUTHOR AFFIL	Department of Computer Sciences, The University of Texas at Austin, Austin	SVM HeaderParse 0.2
AUTHOR ADDR	TX 78712-0233 USA	SVM HeaderParse 0.2
AUTHOR NAME	Aliza Gold	SVM HeaderParse 0.2
AUTHOR AFFIL	Digital Media Collaboratory, IC Institute, The University of Texas at Austin, Austin	SVM HeaderParse 0.2
AUTHOR ADDR	TX 78705 USA	SVM HeaderParse 0.2
ABSTRACT	If game characters could learn through interacting with the player, behavior could improve as the game is played, keeping it interesting. The real-time NeuroEvolution of Augmenting Topologies (rtNEAT) method, which can evolve increasingly complex artificial neural networks in real time as a game is being played, will be presented. The rtNEAT method makes possible an entirely new genre of video games in which the player trains a team of agents through a series of customized exercises. In order to demonstrate this concept, the NeuroEvolving Robotic Operatives (NERO) game was built based on rtNEAT. In NERO, the player trains a team of virtual robots for combat against other players’ teams. The live demo will show how agents in NERO	SVM HeaderParse 0.2
YEAR	2005	INFERENCE
VENUE	In Proceedings of the Artificial Intelligence and Interactive Digital Entertainment Conference (AIIDE 2005) Demo Papers	INFERENCE
VENUE TYPE	CONFERENCE	INFERENCE
CITATIONS	3 found	ParsCit 1.0