OpenNERO
Released 2010
OpenNERO is a general research and education platform for artificial intelligence. The platform is based on a simulation and graphical display of a 3-D physical world that includes multiple agents with embedded sensors and effectors and multiple objects. The software also includes tools for defining and manipulating the environment, the task, and the agent algorithms. The OpenNERO software environment allows developing and testing new AI methods as well as demonstrating existing methods in a sophisticated and concrete simulation of the physical world.

An abstract of the OpenNERO demo presented at AIIDE-08 is here. The current version of the environment is maintained at Googlecode. An example machine learning game that serves as inspiration for OpenNERO is described the NERO page.

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Adam C. Dziuk Undergraduate Alumni
Igor V. Karpov Ph.D. Student ikarpov [at] gmail com
Dan Lessin Ph.D. Student dlessin [at] cs utexas edu
Risto Miikkulainen Faculty risto [at] cs utexas edu
Kenneth Stanley Postdoctoral Alumni kstanley [at] cs ucf edu
IJCNN-2013 Tutorial on Evolution of Neural Networks Risto Miikkulainen To Appear In 2013. Tutorial slides.. 2013

Creating Intelligent Agents through Shaping of Coevolution Adam Dziuk and Risto Miikkulainen In Proceedings of the Congress on Evolutionary Computation, New Orleans, LA, 2011. IEEE. 2011

Neuroevolution Risto Miikkulainen In Encyclopedia of Machine Learning, New York, 2010. Springer. 2010

The Necessity of Separating Control and Logic When Grounding Language Using Neuroevolution Yonatan Bisk Technical Report HR-09-05, Department of Computer Sciences, The University of Texas at Austin, 2009. 2009

Real-time Neuroevolution in the NERO Video Game Kenneth O. Stanley, Bobby D. Bryant, and Risto Miikkulainen IEEE Transactions on Evolutionary Computation:653-668, 2005. IEEE. 2005