Screaming racers: Competitive autonomous drivers for racing games

被引：0
|
作者：
Gallego, Francisco [1 ]
Llorens, Faraon [1 ]
Satorre, Rosana [1 ]
机构：
[1] Univ Alicante, Dept Ciencia Computac & Inteligencia Artificial, Apdo Correos 99, Alicante 03080, Spain
来源：
APPLIED ARTIFICIAL INTELLIGENCE | 2006年
关键词：
D O I：
10.1142/9789812774118_0113
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Online videogames are not just entertainment products but also can be used as environments for Multi-agent Systems (MAS) where agents can reach multiple sources of knowledge from which to learn. In particular, videogames are especially well suited for learning Human-Level Artificial Intelligence, because they strengthen human-agent interaction. In this paper we present Screaming Racers, a simple car-racing online videogame designed to experiment with MAS which learn to drive racing cars along competition tracks. We also present our car-driving learning results with several Neuroevolution techniques, including Neuroevolution of Augmenting Topologies (NEAT).
引用
收藏
页码：805 / +
页数：2
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