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Real-Time Evolution of Neural Networks in the NERO Video Game (2006)
Kenneth O. Stanley
,
Bobby D. Bryant
,
Igor Karpov
,
Risto Miikkulainen
A major goal for AI is to allow users to interact with agents that learn in real time, making new kinds of interactive simulations, training applications, and digital entertainment possible. This paper describes such a learning technology, called real-time NeuroEvolution of Augmenting Topologies (rtNEAT), and describes how rtNEAT was used to build the NeuroEvolving Robotic Operatives (NERO) video game. This game represents a new genre of
machine learning games
where the player trains agents in real time to perform challenging tasks in a virtual environment. Providing laymen the capability to effectively train agents in real time with no prior knowledge of AI or machine learning has broad implications, both in promoting the field of AI and making its achievements accessible to the public at large.
View:
PDF
Citation:
In
Proceedings of the Twenty-First National Conference on Artificial Intelligence (AAAI-2006)
, 1671--1674, Boston, MA, 2006. Meno Park, CA: AAAI Press.
Bibtex:
@inproceedings{stanley:aaai06, title={Real-Time Evolution of Neural Networks in the NERO Video Game}, author={Kenneth O. Stanley and Bobby D. Bryant and Igor Karpov and Risto Miikkulainen}, booktitle={Proceedings of the Twenty-First National Conference on Artificial Intelligence (AAAI-2006)}, address={Boston, MA}, publisher={Meno Park, CA: AAAI Press}, pages={1671--1674}, url="http://nn.cs.utexas.edu/?stanley:aaai06", year={2006} }
People
Bobby D. Bryant
Ph.D. Alumni
bdbryant [at] cse unr edu
Igor V. Karpov
Masters Alumni
ikarpov [at] gmail com
Risto Miikkulainen
Faculty
risto [at] cs utexas edu
Kenneth Stanley
Postdoctoral Alumni
kstanley [at] cs ucf edu
Projects
The OpenNERO AI Research and Education Platform
Since 2009
NEAT: Evolving Increasingly Complex Neural Network Topologies
2000 - 2011
NERO: NeuroEvolving Robotic Operatives
2003 - 2009
Demos
Neuro-Evolving Robotic Operatives (NERO)
Kenneth Stanley
2007
Areas of Interest
Neuroevolution