Neuroevolution for Adaptive Teams Bobby D. Bryant and Risto Miikkulainen Department of Computer Sciences The University of Texas at Austin Austin, TXUSA {bdbryant,risto}@cs.utexas.edu

Source URL: www.cse.unr.edu

Real-Time Neuroevolution in the NERO Video Game Kenneth O. Stanley () Bobby D. Bryant () Risto Miikkulainen () Department of Computer Sciences University of

Source URL: www.cse.unr.edu

Scaling-up Behaviours in EvoTanks: Applying Subsumption Principles to Artificial Neural Networks Thomas Thompson and John Levine Abstract— Applying evolution to generate simple agent behaviours has become a successful

Source URL: www.csse.uwa.edu.au

• Artificial intelligence
• Computational neuroscience
• Cybernetics
• Multi-agent systems
• Computational statistics
• Subsumption architecture
• Artificial neural network
• Evolutionary robotics
• Agent-based model
• Computational intelligence
• Genetic algorithm
• Neuroevolution

Acquiring Visibly Intelligent Behavior with Example-Guided Neuroevolution Bobby D. Bryant Risto Miikkulainen

Source URL: www.cse.unr.edu

Journal of Machine Learning Research Submitted 8/07; Revised 2/08; Published 5/08 Accelerated Neural Evolution through Cooperatively Coevolved Synapses

Source URL: people.idsia.ch

• Artificial neural networks
• Applied mathematics
• Artificial intelligence
• Evolutionary algorithms
• Machine learning
• Evolutionary computation
• Cybernetics
• Computational statistics
• Neuroevolution
• Coevolution
• Cooperative coevolution
• Genetic algorithm

Virtual Bagging for an Evolved Agent Controller Bobby D. Bryant, Member, IEEE is, if the optimal action in a given environment is to move to the left, then the optimal action in a mirror image of that environment would b

Source URL: game.itu.dk

• Computational statistics
• Machine learning
• Applied mathematics
• Ensemble learning
• Statistics
• Computational neuroscience
• Bootstrap aggregating
• Agent-based model
• Artificial neural network
• Simulation
• Neuroevolution

Backpropagation without Human Supervision for Visual Control in Quake II Matt Parker and Bobby D. Bryant Abstract— Backpropagation and neuroevolution are used in a Lamarckian evolution process to train a neural network

Source URL: www.cse.unr.edu

Lamarckian Neuroevolution for Visual Control in the Quake II Environment Matt Parker and Bobby D. Bryant Abstract— A combination of backpropagation and neuroevolution is used to train a neural network visual controller

Source URL: www.cse.unr.edu

1 Neuroevolution in Games: State of the Art and Open Challenges Sebastian Risi and Julian Togelius

Source URL: julian.togelius.com

• Artificial neural networks
• Evolutionary algorithms
• Evolutionary computation
• Genetic algorithms
• Computational neuroscience
• Neuroevolution
• HyperNEAT
• Compositional pattern-producing network
• Blondie24
• Multilayer perceptron
• Galactic Arms Race
• Artificial intelligence

Single-Unit Pattern Generators for Quadruped Locomotion In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCONew York, NY: ACM Gregory Morse Sebastian Risi

Source URL: eplex.cs.ucf.edu

• Artificial neural networks
• Neuroscience
• Terrestrial locomotion
• Evolutionary algorithms
• Applied mathematics
• Cognitive science
• Evolutionary computation
• Genetic algorithms
• HyperNEAT
• Neuroevolution
• Hexapod
• Gait