Diversity Preservation in Minimal Criterion Coevolution through Resource Limitation.
Jonathan C. Brant, Kenneth O. Stanley
Dept. of Computer Science, University of Central Florida, Orlando, FL

Benchmarking Open-Endedness in Minimal Criterion Coevolution
Jonathan C. Brant, Kenneth O. Stanley
Dept. of Computer Science, University of Central Florida, Orlando, FL

Evolving neural networks to follow trajectories of arbitrary complexity
Benjamin Inden¹, Jürgen Jost^2,3;
(1) Department of Computing and Technology, Nottingham Trent University, United Kingdom,
(2) Max Planck Institute for Mathematics in the Sciences, Leipzig Germany,
(3) Santa Fe Institute, Santa Fe, New Mexico, USA.

Neuroevolution for Realtime Strategy Game Micromanagement
Aavaas Gajurel
University of Nevada, Reno

Neuroevolution for RTS Micro
Aavaas Gajurel, Sushil J Louis, Daniel J Mendez, Siming Liu; University of Nevada, Reno

Collaborative Interactive Evolution in Minecraft
Pablo González de Prado Salas, Sebastian Risi; IT University of Copenhagen, Denmark

HyperNTM: Evolving Scalable Neural Turing Machines through HyperNEAT
Jakob Merrild, Mikkel Angaju Rasmussen, and Sebastian Risi; IT University of Copenhagen, Denmark

Neuro-evolution behavior transfer for collective behavior tasks (Doctoral Thesis)
Sabre Z. Didi; University of Capetown, South Africa

Applying neuroevolutionary algorithms to video game artificial intelligence agents (Dissertation)
Ashley Knowles; School of Computer Science, University of Lincoln, UK.

The importance of the activation function in NeuroEvolution with FS-NEAT and FD-NEAT
Evgenia Papavasileiou^1,2, Bart Jansen^1,2;
(1) Department of Electronics and Informatics (ETRO), Vrije Universiteit Brussel (VUB), Pleinlaan 2, B-1050, Brussels, Belgium,
(2) imec

Minimal Criterion Coevolution: A New Approach to Open-Ended Search
Jonathan C. Brant, Kenneth O. Stanley; Dept. of Computer Science, University of Central Florida, Orlando, Florida.

How to Best Automate Intersection Management
Aashiq Parker, Geoff Nitschke; Department of Computer Science, University of Cape Town, Cape Town, South Africa.

HyperENTM: Evolving Scalable Neural Turing Machines through HyperNEAT
Jakob Merrild, Mikkel Angaju Rasmussen, Sebastian Risi; IT University of Copenhagen, Denmark.

DLNE: A Hybridization of Deep Learning and Neuroevolution for Visual Control
Andreas Precht Poulsen, Mark Thorhauge, Mikkel Hvilshj Funch, Sebastian Risi; Center for Computer Games Research, IT University of Copenhagen, Denmark

Continual and One-Shot Learning through Neural Networks with Dynamic External Memory
Benno Luders, Mikkel Schläger, Aleksandra Korach, Sebastian Risi; IT University of Copenhagen, Denmark.

Evolving Collective Driving Behaviors
Chien-Lun (Allen) Huang, Geoff Nitschke; Department of Computer Science, University of Cape Town, Cape Town, South Africa.

Interactive Evolution of Complex Behaviours through Skill Encapsulation
Pablo Gonz´alez de Prado Salas and Sebastian Risi; IT University of Copenhagen, Denmark.

Primal-Improv: Towards Co-Evolutionary Musical Improvisation
Marco Scirea, Peter Eklund, Julian Togelius, Sebastian Risi1; Center for Computer Games Research, Robotics, Evolution and Art Lab, IT University of Copenhagen, Denmark; Department of Computer Science and Engineering, New York University, NY, USA

Evolving Transferable Artificial Neural Networks for Gameplay Tasks via NEAT with Phased Searching
Will Hardwick-Smith, Yiming Peng, Gang Chen, Yi Mei, Mengjie Zhang; School of Engineering and Computer Science, Victoria University of Wellington, Wellington, New Zealand

Evolving novelty strategies for the Iterated Prisoner’s Dilemma in deceptive tournaments
C.R. Noordman; Department of Information and Computing Sciences, Faculty of Science, Utrecht University.

Learning Crowd Behaviour with Neuroevolution
Pascal Widmer, Distributed Computing Group, Computer Engineering and Networks Laboratory, ETH Zürich.

Affective Music Generation and its effect on player experience
Marco Scirea; Center for Computer Games Research, Digital Design Department, IT University of Copenhagen.

ПРОГНОЗ ПОТРЕБЛЕНИЯ ГАЗА ПРЕДПРИЯТИЯМИ С ИСПОЛЬЗОВАНИЕМ НЕЙРОННЫХ СЕТЕЙ (Google translation: Forecast of gas consumption by enterprises with the use of neural networks)
Окунева Александра Олеговича.

Continual Learning through Evolvable Neural Turing Machines
Benno Luders, Mikkel Schlager, Sebastian Risi; IT University of Copenhagen, Denmark

The Eyes Have It: Gaze-based Detection of Mind Wandering during Learning with an Intelligent Tutoring System
Stephen Hutt, Caitlin Mills, Shelby White, Patrick J. Donnelly, Sidney K. D’Mello; University of Notre Dame, Indiana, USA.

Quality Diversity: a new Frontier for evolutionary computation
Justin K. Pugh, Lisa B. Soros and Kenneth O. Stanley; Evolutionary Complexity Research Group, Department of Computer Science, University of Central Florida, Orlando, FL, USA.

Accelerating the Evolution of Cognitive Behaviors Through Human-Computer Collaboration
Mathias Löwe, Sebastian Risi; Robotics, Evolution, and Art Lab, IT University of Copenhagen, Denmark

EvoCommander: A Novel Game Based on Evolving and Switching Between Artificial Brains
Daniel Jallov, Sebastian Risi - Center for Computer Games Research IT University of Copenhagen; Julian Togelius, Tandon School of Engineering, New York University.

Searching for Quality Diversity When Diversity is Unaligned with Quality
Justin K. Pugh, L. B. Soros, Kenneth O. Stanley; Department of Computer Science, University of Central Florida, Orlando, USA

Confronting the Challenge of Quality Diversity
Justin K. Pugh, L. B. Soros, Paul A. Szerlip, and Kenneth O. Stanley (2015); Department of EECS, Computer Science Division University of Central Florida.
In: Proc. of the 17th Annual Conference on Genetic and Evolutionary Computation (GECCO 2015). New York, NY: ACM

Unsupervised Feature Learning through Divergent Discriminative Feature Accumulation
Paul A. Szerlip, Gregory Morse, Justin K. Pugh, and Kenneth O. Stanley (2015)
In: Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI-2015). Palo Alto, CA: AAAI Press, 2015.

A new and fast image feature selection method for developing an optimal mammographic mass detection scheme
Maxine Tan, Jiantao Pu, Bin Zheng (2014).
In: Medical Physics 41, 081906 (2014)

Optimization of Network Topology in Computer-Aided Detection Schemes Using Phased Searching with NEAT in a Time-Scaled Framework
Maxine Tan, Jiantao Pu, Bin Zheng (2014).
In: Cancer Informatics; 2014; 13(Suppl 1): 17–27.
Link2

Composing Video Game Levels with Music Metaphors through Functional Scaffolding
Amy K. Hoover, Julian Togelius, Georgios N. Yannakis (2015).

Evolving Flappy Bird game agents with sharpNEAT
Trond Glomnes, Vinicius Pinton, Till Riemer, Adan Silva; IT University of Copenhagen (2014).

Directional Communication in Evolved Multiagent Teams
Justin K. Pugh, Skyler Goodell, and Kenneth O. Stanley (2014)
In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2014). New York, NY: ACM, 2014.
This paper is accompanied with a set of video demos at http://tinyurl.com/DirComVideo

Identifying Necessary Conditions for Open-Ended Evolution through the Artificial Life World of Chromaria
L. B. Soros and Kenneth O. Stanley (2014)
In: Proceedings of the Fourteenth International Conference on the Synthesis and Simulation of Living Systems (ALIFE 14). Cambridge, MA: MIT Press, 2014.

Winner of the Best Poster Award at ALIFE 14

This paper is accompanied with a set of video demos and source code http://eplex.cs.ucf.edu/chromaria/home.

An Integrated Approach to Personalized Procedural Map Generation using Evolutionary Algorithms
William L. Raffe, Fabio Zambetta, Xiaodong Li, and Kenneth O. Stanley (2014)
DOI 10.1109/TCIAIG.2014.2341665, IEEE Transactions on Computational Intelligence and AI in Games

Phased searching with NEAT in a Time-Scaled Framework: Experiments on a computer-aided detection system for lung nodules
Maxine Tan, Rudi Deklerck, Jan Cornelis, Bart Jansen

CPPNs Effectively Encode Fracture: A Response to Critical Factors in the Performance of HyperNEAT
Kenneth O. Stanley, Jeff Clune, David B. D'Ambrosio, Colin D. Green, Joel Lehman, Gregory Morse, Justin K. Pugh, Sebastian Risi, and Paul Szerlip (2013)
University of Central Florida Dept. of EECS Technical Report CS-TR-13-05.

Evolving Multimodal Controllers with HyperNEAT
Justin K. Pugh, Kenneth O. Stanley (2013); Department of EECS, University of Central Florida
In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2013). New York, NY: ACM

Neuroevolution of Content Layout in the PCG: Angry Bots Video Game
William L. Raffe, Fabio Zambetta, Xiaodong Li (2013); School of Computer Science and Information Technology, RMIT University, Melbourne 3001, Australia.
2013 IEEE Congress on Evolutionary Computation, June 20-23, Cancún, México

A Compiler for CPPNs: Transforming Phenotypic Descriptions Into Genotypic Representations
Sebastian Risi (2013); Center for Computer Games Research, IT University of Copenhagen, Copenhagen, Denmark 2300
AAAI Technical Report FS-13-02

Neuroevolution of a multi-agent system for the dynamic pickup and delivery problem
Jonathan Merlevede, Rinde R.S. van Lon, Tom Holvoet; iMinds-DistriNet, KU Leuven, 3001 Leuven, Belgium.

Encouraging Reactivity to Create Robust Machines
Joel Lehman, Sebastian Risi, David B. D'Ambrosio and Kenneth O. Stanley (2013)
In: Adaptive Behavior journal. London: SAGE, 2013 (Maunscript 31 pages).

This paper is accompanied with a set of video demos at http://goo.gl/Qn9nz

Scalable Multiagent Learning through Indirect Encoding of Policy Geometry
Joel Lehman, Sebastian Risi, David B. D'Ambrosio and Kenneth O. Stanley (2013)
In: Evolutionary Intelligence Journal. New York, NY: Springer-Verlag, 2013 (Maunscript 30 pages).

Evolving neural fields for problems with large input and output spaces
Benjamin Inden(a,d), Yaochu Jinb(b), Robert Haschkec(c), Helge Ritterc(c)
(a) Research Institute for Cognition and Robotics, Bielefeld University, Bielefeld, Germany
(b) Department of Computing, University of Surrey, United Kingdom
(c) Neuroinformatics Group, Bielefeld University, Germany
(d) Artificial Intelligence Group, Bielefeld University, Germany

Multirobot Behavior Synchronization through Direct Neural Network Communication
David B. D'Ambrosio, Skyler Goodell, Joel Lehman, Sebastian Risi, and Kenneth O. Stanley (2012).
In: Proceedings of the 5th International Conference on Intelligent Robotics and Applications (ICIRA-2012). New York, NY: Springer-Verlang, 2012.

An Enhanced Hypercube-Based Encoding for Evolving the Placement, Density and Connectivity of Neurons
Sebastian Risi and Kenneth O. Stanley (2012).
To appear in: Artificial Life journal. Cambridge, MA: MIT Press, 2012

A Unified Approach to Evolving Plasticity and Neural Geometry
Sebastian Risi and Kenneth O. Stanley (2012).
In: Proceedings of the International Joint Conference on Neural Networks (IJCNN 2012). Piscataway, NJ: IEEE, 2012.

Winner of the Best Student Paper Award at IJCNN-2012

Rewarding Reactivity to Evolve Robust Controllers without Multiple Trials or Noise
Joel Lehman, Sebastian Risi, David B. D'Ambrosio, and Kenneth O. Stanley (2012).
In: Proceedings of the Thirteenth International Conference on Artificial Life (ALIFE 13). Cambridge, MA: MIT Press, 2012.

Modularity as a Solution to Spatial Interference in Neural Networks
Kim Verner Soldal (2012); Computer and Information Science, Norwegian University of Science and Technology.

Task Switching in Multirobot Learning through Indirect Encoding
David B. D'Ambrosio, Joel Lehman, Sebastian Risi, and Kenneth O. Stanley (2011).
In: Proceedings of the International Conference on Intelligent Robots and Systems (IROS 2011 San Fransisco, CA)

Enhancing ES-HyperNEAT to Evolve More Complex Regular Neural Networks
Sebastian Risi and Kenneth O. Stanley (2011)
In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2011). New York, NY:ACM

Comparison of NEAT and HyperNEAT on a Strategic Decision-Making Problem
Jessica Lowell, Kir Birger, and Sergey Grabkovsky (2011).
CS 6140 Final Project

Indirectly Encoding Neural Plasticity as a Pattern of Local Rules
Sebastian Risi and Kenneth O. Stanley (2010).
In: Proceedings of the 11th International Conference on Simulation of Adaptive Behavior (SAB 2010). New York, NY: Springer

Evolving the Placement and Density of Neurons in the HyperNEAT Substrate
Sebastian Risi, Joel Lehman, and Kenneth O. Stanley (2010).
In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2010). New York, NY: ACM

Winner of the Best Paper Award in the Generative and Developmental Systems (GDS) Track

Evolving Policy Geometry for Scalable Multiagent Learning
David B. D'Ambrosio, Joel Lehman, Sebastian Risi, and Kenneth O. Stanley (2010).
In: Proceedings of the Ninth International Conference on Autonomous Agents and Multiagent Systems (AAMAS-2010).
Note:
This paper is accompanied with a set of videos at http://eplex.cs.ucf.edu/mahnaamas2010.html

Using Neural Networks for Strategy Selection in Real-Time Strategy Games
Thomas Randall, Peter Cowling, Roderick Baker and Ping Jiang (2009).
School of Computing, Informatics and Media, Univ. of Bradford.

A Hypercube-Based Indirect Encoding for Evolving Large-Scale Neural Networks
Kenneth O. Stanley, David B. D'Ambrosio, and Jason Gauci (2009).
In: Artificial Life journal 15(2), Cambridge, MA: MIT Press, 2009.

HyperNEAT Controlled Robots Learn How to Drive on Roads inSimulated Environment
Jan Drchal, Jan Koutník, Miroslav Snorek (2009).
Computational Intelligence Group, Department of Computer Science and Engineering, Faculty of Electrical Engineering, Czech Technical University, Prague

Generative Encoding for Multiagent Learning
David B. D'Ambrosio and Kenneth O. Stanley
In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2008). New York, NY: ACM, 2008.

Winner of the Best Paper Award in Generative and Developmental Systems at GECCO-2008

Can Opponent Models Aid Poker Player Evolution?
R.J.S.Baker, Member, IEEE, P.I.Cowling, Member, IEEE, T.W.G.Randall, Member, IEEE, and P.Jiang, Member, IEEE.

Interactively Evolved Modular Neural Networks for Game Agent Control
John Reeder, Roberto Miguez, Jessica Sparks, Michael Georgiopoulos, and Georgios Anagnostopoulos.

Neuroevolution and complexifying genetic architectures for memory and control tasks
Benjamin Inden, Max Planck Institute for Mathematics in the Sciences, Leipzig, Germany.

A Novel Generative Encoding for Exploiting Neural Network Sensor and Output Geometry
David B. D'Ambrosio and Kenneth O. Stanley
In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2007). New York, NY: ACM, 2007

Nominated for Best Paper Award in Generative and Developmental Systems, GECCO 2007

David D'Ambrosio and Kenneth Stanley at the University of Central Florida used their extended version of SharpNEAT - HyperSharpNEAT - in this paper presented at GECCO 2007. This was one of two papers introducing HyperNEAT, a powerful new indirect encoding.

Their HyperSharpNEAT releases are available from the UCF EPLEX software download page.

Evolving Explicit Opponent Models in Game Playing
Alan J. Lockett, Charles L. Chen, and Risto Miikkulainen, The University of Texas at Austin.

Wesley Tansey extended SharpNEAT to allow parallel processing across multiple CPUs while at Virginia Tech. This work is hosted on Codeplex as ParaSharpNEAT.

Compositional Pattern Producing Networks: A Novel Abstraction of Development
Kenneth O. Stanley (2007)
In: Genetic Programming and Evolvable Machines Special Issue on Developmental Systems 8(2): 131-162. New York, NY: Springer, 2007.

The Art of Artificial Evolution: A Handbook on Evolutionary Art and Music
Juan J Romero, Penousal Machado
Springer-Verlag Berlin Heidelberg 2007

Exploiting Regularity Without Development
Kenneth O. Stanley, School of Electrical Engineering and Computer Science, The University of Central Florida