Ken's Home Page

Kenneth O. Stanley

Associate Professor

University of Central Florida Dept. of Electrical Engineering and Computer Science

Evolutionary Complexity Research Group (EPlex)

kstanley@eecs.ucf.edu
Office: Harris 332

Vita: PDF

Interested in experimental games based on cutting-edge AI? Try AIGameResearch.org, the one-stop Internet hub for research-grade AI in games

New Evolutionary Content-Generating Game Now In Beta: Petalz

Videos of Invited Talks
New: The Case for Evolution in Engineering Brains (2013 MSU Symposium on New Frontiers in Cognitive, Evolutionary, and Computational Models of the Mind)

Discovery Without Objectives (Joint ACM and NICTA-sponsored 2012 talk at RMIT)

Searching Without Objectives (SPLASH 2010 Keynote)

Users Pages: NEAT Users | HyperNEAT Users | ES-HyperNEAT Users | Novelty Search Users

Quick Links: Meeting | Teaching | Research | Software/Source Code | Animated Demos | Publications (journal / conf.) |

Evolutionary Games and Entertainment: Picbreeder | NERO Video Game | Dance Evolution | Galactic Arms Race (GAR) | Petalz

Research

I am the director of the Evolutionary Complexity (EPlex) Research Group at UCF. Our research focuses on abstracting the essential properties of natural evolution that made it possible to discover astronomically complex structures such as the human brain. Our work is in part an approach to artificial intelligence.
I developed a method, called NEAT (NeuroEvolution of Augmenting Topologies), that begins evolution with a population of very simple networks and complexifies the networks over generations by adding new neurons and connections.

We recently developed an extension to NEAT called HyperNEAT that can evolve neural networks with millions of connections and exploit geometric regularities in the task domain. Here is a page on fracture in CPPNs and HyperNEAT.
Another new approach that we recently introduced is called novelty search. Unlike most evolutionary algorithms, novelty search has no defined objective; instead it simply searches for novel behaviors. Nevertheless, it finds surprisingly robust solutions, raising questions about fundamental assumptions on why search works.
I discuss some of my research interests in several interviews that are available online: This audio interview (9/30/06) conducted by Tom Barbalet for biota.org discusses some of my general interests. In this text interview (12/11/08) with AIGameDev.com, I discuss Galactic Arms Race and my thoughts on automatic content generation for video games through evolution. A TV interview (on G4TV) from February 2010 also discusses GAR. In yet another text interview, I discuss GAR with Game Developer Magazine in April 2010.
Before joining UCF, I was a member of the UTCS Neural Networks Research Group.
Günter Bachelier created a gallery of computerized portraits of myself , generated through an evolutionary process, as part of our recognition for winning the Best Paper Award at EvoMUSART 2008. Gunter added another set here
Teaching

New: Fall 2012: NeuroEvolution and Generative and Developmental Systems (CAP 6616): Syllabus | Lectures and Assignments
Old: Spring 2012: AI for Game Programming (CAP 4053): Syllabus | Lectures and Assignments
Old: Spring 2011: AI for Game Programming (CAP 4053): Syllabus | Lectures and Assignments
Old: Fall 2010: NeuroEvolution and Generative and Developmental Systems (CAP 6616): Syllabus | Lectures and Assignments
Old: Spring 2010: AI for Game Programming (CAP 4053): Syllabus | Lectures and Assignments
Old: Fall 2009: NeuroEvolution and Generative and Developmental Systems (CAP 6616): Syllabus | Lectures and Assignments

Old: Spring 2009: AI for Game Programming (CAP 4053): Syllabus | Lectures and Assignments
Old: Fall 2008: NeuroEvolution and Generative and Developmental Systems (CAP 6616): Syllabus | Lectures and Assignments

Old: Spring 2008: AI for Game Programming (CAP 4932): Syllabus | Lectures and Assignments
Old: Fall 2007: NeuroEvolution and Generative and Developmental Systems (CAP 6616): Syllabus | Lectures and Assignments

Old: Spring 2007: Machine Learning (CAP 5810): Syllabus | Lectures and Assignments

Old: Fall 2006: Topics in NeuroEvolution and Developmental Encoding (CAP 6938): Syllabus | Lectures and Assignments

Machine Learning I (EEL 4818; Undergraduate Honors) Class Homepage (Co-taught with Drs. R. DeMara, M. Georgiopoulos, M. Mollaghasemi, and I. Garibay)

Old: Spring 2006: Topics in NeuroEvolution (CAP 6938)
NEAT and HyperNEAT Users
Derek James runs a NEAT Users Group on Yahoo. Please feel free to join to discuss NEAT or HyperNEAT-related issues.
If you are a NEAT user, or interested in working with NEAT, please see the NEAT Users Page , which includes a helpful FAQ.
New! There is now also a HyperNEAT Users Page
Schedule Meeting
You can schedule a meeting with me here: Online Meeting Schedule (please follow the instructions there)
Note that you must be logged into the EPlex website in order to use this feature. If you see the message, "You are not authorized to view this resource," then you need to log in first and the page will appear. If you do not have a login, please send me an email to schedule a meeting.
Evolutionary Games and Entertainment

Galactic Arms Race
Multiplayer online space combat with evolving weapons.

Picbreeder
Evolve pictures online.

Dance Evolution
Train 3D animated characters to dance to any MIDI song using interactive evolution.

The NERO Video Game
Evolve robots in real time to train for battle.

Software / Source Code

Novelty Search
Novelty Search C++ by Joel Lehman implements the novelty search algorithm introduced by Lehman and Stanley in Exploiting Open-Endedness to Solve Problems Through the Search for Novelty . Experiments in the paper are included in the software release.
MultiNEAT C++ by Peter Chervenski also includes an implementation of novelty search.
HyperNEAT Versions
HyperNEAT is Hypercube-based NeuroEvolution of Augmenting Topologies, a new algorithm for evolving very large neural networks with geometric regularities. More information is available under publications.

HyperSharpNEAT C# by David D'Ambrosio. This package extends Colin Green's original SharpNEAT to run as HyperNEAT. A scalable robot food gathering domain is included.

HyperSharpNEAT-compatible multiagent robotics simulator and experimental platform Includes room-clearing experiment, visualization tools, sample genomes, and a nice GUI. Other multiagent experiments can be implemented with it as well.

HyperNEAT C++ by Jason Gauci. Includes the scalable big box/little box visual discrimination task and a convenient GUI for exploring the substrate.

SharpNEAT 2 HyperNEAT by Colin Green. Colin Green's new SharpNEAT version 2 also includes a complete implementation of HyperNEAT. The boxes experiment is included.

Keepaway HyperNEAT C# by Phillip Verbancsics. This version of HyperNEAT is also in C# but it is coded entirely separate from the other C# versions. It comes with RoboCup Keepaway and a clone of the original RoboCup server entirely rewritten in C# for much faster speed.

Another HyperNEAT Implementation (AHNI) [Java] by Oliver Coleman. This Java-based version of HyperNEAT was produced by Oliver Coleman at The University of New South Wales by extending the pre-existing ANJI version of NEAT (which is written by Derek James and Philip Tucker). It includes visual processing experiments and vision-based RL experiments. Oliver also published an undergraduate thesis that explains these experiments in detail.

New! MultiNEAT C++ with Python Bindings by Peter Chervenski. This package includes Python bindings with pickleable Genomes available through Boost.Python and is heavily commented. Peter explains how to use the HyperNEAT component: "The user only has to supply all the coordinates (through Python or C++) of inputs, hidden and outputs for the substrate and use the substrate each time with Genome.BuildHyperNEATPhenotype(). The Substrate class returns the number of inputs/outputs of the required CPPN and this data should be used when creating the CPPN seed genome." Also includes novelty search.

NEAT Versions

NEAT C++ Software Package for Linux. My own C++ source code, intended for Linux.

Real-time NEAT C++ Software Package. A public version of the rtNEAT source code used in NERO. Provided with a public noncommercial research license. Examples of real-time main loops are provided.

NEAT JAVA (See some screenshots ). Ugo Vierucci wrote this version of NEAT based on my original C++ source code. Includes a nice GUI.

Microsoft Windows NEAT C++ (See a screenshot ). Mat Buckland wrote this version of NEAT for Windows. It comes with an animated minesweepers experiment.

Delphi NEAT (including source code and demos) Mattias Fagerlund wrote this version of NEAT in Delphi. It includes a number of nice graphical demos of evolved behavior. Mattias' coolest demos depict NEAT evolving various mobility strategies for 3D artificial creatures.

Matlab NEAT . Christian Mayr wrote this version of NEAT for Matlab. Includes the XOR experiment.

SharpNEAT. Colin Green wrote this version of NEAT in C#. Includes the XOR, predator/prey, and pole balancing experiments.

Another NEAT Java Implementation (ANJI) Derek James and Philip Tucker wrote this alternate version NEAT in Java. It includes XOR and Tic Tac Toe.

NEAT 4J. Matt Simmerson produced this Java-based version of NEAT, which comes with XOR and supports distributed evolution over multiple processes.

NEAT Python. Cesar G. Miguel and Carolina Feher da Silva maintain this project to bring NEAT to Python. XOR is included and the project continues to be developed. It can be checked out from the SVN repository and requires Python 2.5.

Encog NEAT is part of a larger Neural Network Framework by Heaton Research. It is licensed under the LGPL and is available C#, Java and Silverlight.

New! ObjectiveNEAT is an implementation of NEAT by Ben Trewhella in Objective C, supporting applications on Mac / iOS devices. It comes with an implementation of XOR. Documentation is here.

New! XNET NEAT is part of the XNet simulation and evolution library by Michael Roberts that is included in this package.

New! MultiNEAT C++ with Python Bindings by Peter Chervenski. This package includes Python bindings with pickleable Genomes available through Boost.Python and is heavily commented. Also includes HyperNEAT and novelty search implementations.

New! NEAT Visualizer SFML C++ by Eric Laukien. Variant of NEAT with implicit speciation instead of the usual explicit speciation, which means that organisms are not explcitly grouped into species, but they can only reproduce with other genes that are similar enough and fitness is modified according to compatibility. Includes a special visualization system and XOR.

NEAT-based Genetic Art (CPPN Explorer) Programs and Other CPPN Applications
For an introduction to the theory behind Compositional Pattern Producing Networks (CPPNs), which explains how the patterns produced by these programs are possible to evolve, please refer to our paper Exploiting Regularity Without Development.

DelphiNEAT-based Genetic Art Tool. Mattias Fagerlund released this tool first, which allows you to explore evolved images generated through NEAT-evolved CPPNs. The interface makes it a great neural network learning tool, and other developers followed suit.

SharpNEAT-based Genetic Art Tool. Inspired by the DelphiNEAT Genetic Art tool, Holger Ferstl created this newer genetic art tool with SharpNEAT. It includes some novel schemes for evolving pictures with color. The files are also available with permission from Holger from my local server: Executable (requires .NET 2.0); Full Source

JCPPN. William Monti created this Java-based CPPN explorer, including the version of NEAT that powers it. It includes HSL color and the ability to input texture files into the CPPN and manipulate them.

djNEAT. This program by Wade Spires and Brendon Moore (started as a project in my neuroevolution class) implements interactive evolution of audio effects. It is like the image explorer programs except it produces sounds instead of images.

Evolving a 2D Model of an Eye using CPPNs: This document is a Masters Thesis by Anders Storsveen completed at the Norwegian University of Science and Technology Department of Computer and Information Science, under the supervision of Professor Keith Downing. It is interesting because it is a unique application of CPPNs outside the usual domains. Some of the work was completed while Anders visited the Evolutionary Complexity Research Group at UCF in 2008.

Animated Demos
Animations of evolved NEAT neural network behavior: Robot Duel, hall navigation, function approximation, NEAT Hopper, and Peons. Demo formats include GIF animations, .avi movies, and a Windows executable.
The Evolution of a Spaceship
Watch how NEAT neural networks evolved to draw a multi-featured spaceship out of scratch. A fascinating exhibition of complexification and the evolution of form.

Selected Publications Journal Conference
(For a full list of my publications please see my vita)
Paperback Book Available with Chapter on NEAT
This book by Mat Buckland provides a nice overview of NEAT intended for general (i.e. non-academic) audiences: AI Techniques for Game Programming. NEAT is covered in the final chapter and the book comes with source code from Mat.
Dissertation
Ph.D. Dissertation: EFFICIENT EVOLUTION OF NEURAL NETWORKS THROUGH COMPLEXIFICATION
Kenneth O. Stanley
Department of Computer Sciences, The University of Texas at Austin
Technical Report~AI-TR-04-39, August 2004.
Journal Articles
Scalable Multiagent Learning through Indirect Encoding of Policy Geometry
David B. D'Ambrosio and Kenneth O. Stanley
Dept. of Electrical Engineering and Computer Science, University of Central Florida
To appear in: Evolutionary Intelligence . New York, NY: Springer-Verlag, 2013. Manuscript 30 pages.

From Modulated Hebbian Plasticity to Simple Behavior Learning through Noise and Weight Saturation
Andrea Soltoggio and Kenneth O. Stanley
Research Institute for Cognition and Robotics . CoR-Lab, Bielefeld, Germany and Dept. of Electrical Engineering and Computer Science, University of Central Florida
To appear in: Neural Networks journal, Vol. 34, October 2012, pp. 28.41. New York, NY: Elsevier, 2012. Manuscript 17 pages.

An Enhanced Hypercube-Based Encoding for Evolving the Placement, Density and Connectivity of Neurons
Sebastian Risi and Kenneth O. Stanley
Dept. of Electrical Engineering and Computer Science, University of Central Florida
To appear in: Artificial Life journal. Cambridge: MIT Press, 2012. Manuscript 54 pages.

Picbreeder: A Case Study in Collaborative Evolutionary Exploration of Design Space
Jimmy Secretan, Nicholas Beato, David B. D.Ambrosio, Adelein Rodriguez, Adam Campbell, Jeremiah T. Folsom-Kovarik, and Kenneth O. Stanley
Dept. of Electrical Engineering and Computer Science, University of Central Florida
To appear in: Evolutionary Computation journal. Cambridge: MIT Press, 2011. Manuscript 33 pages.

On the Performance of Indirect Encoding Across the Continuum of Regularity
Jeff Clune, Kenneth O. Stanley, Robert T. Pennock, and Charles Ofria
Digital Evolution Lab at Michigan State University (Clune, Pennock, and Ofria) and School of Electrical Engineering and Computer Science, University of Central Florida (Stanley)
To appear in: IEEE Transactions on Evolutionary Computation journal. New York: IEEE Press, 2011. Manuscript 23 pages.

Abandoning Objectives: Evolution Through the Search for Novelty Alone
Joel Lehman and Kenneth O. Stanley
School of Electrical Engineering and Computer Science, University of Central Florida
To appear in: Evolutionary Computation journal. Cambridge, MA: MIT Press, 2011. Manuscript 39 pages.

Evolving Plastic Neural Networks with Novelty Search
Sebastian Risi, Charles E. Hughes, and Kenneth O. Stanley
School of Electrical Engineering and Computer Science, University of Central Florida
To appear in: Adaptive Behavior journal 18(6), pages 470-491. London: SAGE, 2010. Manuscript 41 pages.

Evolving Static Representations for Task Transfer
Phillip Verbancsics and Kenneth O. Stanley
School of Electrical Engineering and Computer Science, University of Central Florida
In: Journal of Machine Learning Research (JMLR). 11: pages 1737-1769. Brookline, MA: Microtome Publishing, 2010. 33 pages.

Autonomous Evolution of Topographic Regularities in Artificial Neural Networks
Jason Gauci and Kenneth O. Stanley
School of Electrical Engineering and Computer Science, University of Central Florida
In: Neural Computation journal 22(7), pages 1860-1898. Cambridge, MA: MIT Press, 2010. Manuscript 38 pages.

Automatic Content Generation in the Galactic Arms Race Video Game
Erin J. Hastings, Ratan K. Guha, and Kenneth O. Stanley
School of Electrical Engineering and Computer Science, University of Central Florida
In: IEEE Transactions on Computational Intelligence and AI in Games, volume 4, number 1, New York: IEEE Press, 2009. Manuscript 19 pages

Interactive Evolution of Particle Systems for Computer Graphics and Animation
Erin J. Hastings, Ratan K. Guha, and Kenneth O. Stanley
School of Electrical Engineering and Computer Science, University of Central Florida
In: IEEE Transactions on Evolutionary Computation, New York: IEEE Press, 2009. Manuscript 15 pages

Exploiting Functional Relationships in Musical Composition
Amy K. Hoover and Kenneth O. Stanley
School of Electrical Engineering and Computer Science, University of Central Florida
In: Connection Science Special Issue on Music, Brain, & Cognition. Abington, UK: Taylor & Francis, 2009. Manuscript 33 pages

A Hypercube-Based Encoding for Evolving Large-Scale Neural Networks
Kenneth O. Stanley, David B. D'Ambrosio, and Jason Gauci
School of Electrical Engineering and Computer Science, University of Central Florida
In: Artificial Life journal. Cambridge, MA: MIT Press, 2009. Manuscript 39 pages

Picbreeder: Collaborative Interactive Evolution of Images
Jimmy Secretan, Nicholas Beato, David B. D'Ambrosio, Adelein Rodriguez, Adam Campbell, and Kenneth O. Stanley
School of Electrical Engineering and Computer Science, University of Central Florida
In: Leonardo (Transactions Section) 41(1), 2007. 2 pages (This article is a short notice written for the transaction section of the journal)

Compositional Pattern Producing Networks: A Novel Abstraction of Development
Kenneth O. Stanley
School of Electrical Engineering and Computer Science, University of Central Florida
In: Genetic Programming and Evolvable Machines Special Issue on Developmental Systems New York, NY: Springer, 2007. 36 pages.

REAL-TIME NEUROEVOLUTION IN THE NERO VIDEO GAME
Kenneth O. Stanley, Bobby D. Bryant, and Risto Miikkulainen
Department of Computer Sciences, The University of Texas at Austin
IEEE Transactions on Evolutionary Computation 9(6): 653-668, December 2005.

COMPETITIVE COEVOLUTION THROUGH EVOLUTIONARY COMPLEXIFICATION
Kenneth O. Stanley and Risto Miikkulainen
Department of Computer Sciences, The University of Texas at Austin
Journal of Artificial Intelligence Research 21: 63-100, 2004.

A TAXONOMY FOR ARTIFICIAL EMBRYOGENY
Kenneth O. Stanley and Risto Miikkulainen
Department of Computer Sciences, The University of Texas at Austin
Artificial Life journal 9(2):93-130, 2003.

EVOLVING NEURAL NETWORKS THROUGH AUGMENTING TOPOLOGIES
Kenneth O. Stanley and Risto Miikkulainen
Department of Computer Sciences, The University of Texas at Austin
Evolutionary Computation 10(2):99-127, 2002.

ONLINE INTERACTIVE NEURO-EVOLUTION
Adrian Agogino(1), Kenneth Stanley(2), and Risto Miikkulainen(2)
(1) Dept. of Electrical and Computer Engineering, The University of Texas at Austin
(2) Department of Computer Sciences, The University of Texas at Austin
Neural Processing Letters 11(1):29-37, 2000.
Conference and Symposium Papers
Combining Search-based Procedural Content Generation and Social Gaming in the Petalz Video Game
Sebastian Risi, Joel Lehman, David B. D'Ambrosio, Ryan Hall and Kenneth O. Stanley
Department of Electrical Engineering and Computer Science, University of Central Florida
To appear in: Proceedings of the Artificial Intelligence and Interactive Digital Entertainment Conference (AIIDE 2012). Menlo Park, CA:AAAI, 2012. 6 pages.

Multirobot Behavior Synchronization through Direct Neural Network Communication
David B. D'Ambrosio, Skyler Goodell, Joel Lehman, Sebastian Risi, and Kenneth O. Stanley
Department of Electrical Engineering and Computer Science, University of Central Florida
To appear in: Proceedings of the 5th International Conference on Intelligent Robotics and Applications (ICIRA-2012). New York, NY: Springer-Verlang, 2012. 12 pages.

A Unified Approach to Evolving Plasticity and Neural Geometry
Sebastian Risi and Kenneth O. Stanley
Department of Electrical Engineering and Computer Science, University of Central Florida
To appear in: Proceedings of the International Joint Conference on Neural Networks (IJCNN 2012). Piscataway, NJ: IEEE, 2012. 8 pages.
Winner of the Best Student Paper Award at IJCNN-2012

On the Benefits of Divergent Search for Evolved Representations
Joel Lehman and Kenneth O. Stanley
Department of Electrical Engineering and Computer Science, University of Central Florida
To appear in: Proceedings of EvoNet 2012 Workshop at the Thirteenth International Conference on Artificial Life (ALIFE XIII). 2012. 4 pages.

Beyond Open-endedness: Quantifying Impressiveness
Joel Lehman and Kenneth O. Stanley
Department of Electrical Engineering and Computer Science, University of Central Florida
To appear in: Proceedings of the Thirteenth International Conference on Artificial Life (ALIFE XIII). Cambridge, MA: MIT Press, 2012. 8 pages.

Rewarding Reactivity to Evolve Robust Controllers without Multiple Trials or Noise
Joel Lehman, Sebastian Risi, David B. D'Ambrosio, and Kenneth O. Stanley
Department of Electrical Engineering and Computer Science, University of Central Florida
To appear in: Proceedings of the Thirteenth International Conference on Artificial Life (ALIFE XIII). Cambridge, MA: MIT Press, 2012. 8 pages.

Generating a Complete Multipart Musical Composition from a Single Monophonic Melody with Functional Scaffolding
Amy K. Hoover, Paul A. Szerlip, Marie E. Norton, Trevor A. Brindle, Zachary Merritt, and Kenneth O. Stanley
Department of Electrical Engineering and Computer Science, University of Central Florida
To appear in: Proceedings of the Third International Conference on Computational Creativity (ICCC-2012, Dublin, Ireland). 2012. 8 pages.

Task Switching in Multiagent Learning through Indirect Encoding
David B. D'Ambrosio, Joel Lehman, Sebastian Risi, and Kenneth O. Stanley
Department of Electrical Engineering and Computer Science, University of Central Florida
To appear in: Proceedings of the International Conference on Intelligent Robots and Systems (IROS 2011, San Fransisco, CA). Piscataway, NJ: IEEE, 2011. 8 pages.

Generating Musical Accompaniment through Functional Scaffolding
Amy K. Hoover, Paul A. Szerlip, and Kenneth O. Stanley
Department of Electrical Engineering and Computer Science, University of Central Florida
To appear in: Proceedings of the 8th Sound and Music Computing Conference (SMC-2011, Padova, Italy). . 8 pages.

Enhancing ES-HyperNEAT to Evolve More Complex Regular Neural Networks
Sebastian Risi and Kenneth O. Stanley
Department of Electrical Engineering and Computer Science, University of Central Florida
To appear in: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2011). New York, NY: ACM, 2011. 8 pages.

Interactively Evolving Harmonies through Functional Scaffolding
Amy K. Hoover, Paul A. Szerlip, and Kenneth O. Stanley
Department of Electrical Engineering and Computer Science, University of Central Florida
To appear in: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2011). New York, NY: ACM, 2011. 8 pages.
Winner of the Best Paper Award in the Digital Entertainment Technologies and Arts Track at GECCO-2011

Evolving a Diversity of Virtual Creatures through Novelty Search with Local Competition
Joel Lehman and Kenneth O. Stanley
Department of Electrical Engineering and Computer Science, University of Central Florida
To appear in: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2011). New York, NY: ACM, 2011. 8 pages.

Improving Evolvability through Novelty Search and Self-Adaptation
Joel Lehman and Kenneth O. Stanley
Department of Electrical Engineering and Computer Science, University of Central Florida
To appear in: Proceedings of the 2011 IEEE Congress on Evolutionary Computation (CEC 2011). Piscataway, NJ: IEEE, 2011. 8 pages.

Constraining Connectivity to Encourage Modularity in HyperNEAT
Phillip Verbancsics and Kenneth O. Stanley
Department of Electrical Engineering and Computer Science, University of Central Florida
To appear in: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2011). New York, NY: ACM, 2011. 8 pages.

On the Deleterious Effects of A Priori Objectives on Evolution and Representation
Brian G. Woolley and Kenneth O. Stanley
Department of Electrical Engineering and Computer Science, University of Central Florida
To appear in: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2011). New York, NY: ACM, 2011. 8 pages.

Indirect Encoding of Neural Networks for Scalable Go
Jason Gauci and Kenneth O. Stanley
School of Electrical Engineering and Computer Science, University of Central Florida
To appear in: Proceedings of the 11th International Conference on Parallel Problem Solving From Nature (PPSN-2010). New York, NY: Springer, 2010. 10 pages.

Evolving a Single Scalable Controller for an Octopus Arm with a Variable Number of Segments
Brian G. Woolley and Kenneth O. Stanley
School of Electrical Engineering and Computer Science, University of Central Florida
To appear in: Proceedings of the 11th International Conference on Parallel Problem Solving From Nature (PPSN-2010). New York, NY: Springer, 2010. 10 pages.

Interactive Genetic Engineering of Evolved Video Game Content
Erin J. Hastings and Kenneth O. Stanley
School of Electrical Engineering and Computer Science, University of Central Florida
To appear in: Proceedings of the Workshop on Procedural Content Generation in Games (PCG) at the 5th International Conference on the Foundations of Digital Games (FDG-2010). New York, NY: ACM, 2010. 4 pages.

Indirectly Encoding Neural Plasticity as a Pattern of Local Rules
Sebastian Risi and Kenneth O. Stanley
School of Electrical Engineering and Computer Science, University of Central Florida
To appear in: Proceedings of the 11th International Conference on Simulation of Adaptive Behavior (SAB 2010). New York, NY: Springer, 2010. 11 pages.

Revising the Evolutionary Computation Abstraction: Minimal Criteria Novelty Search
Joel Lehman and Kenneth O. Stanley
School of Electrical Engineering and Computer Science, University of Central Florida
To appear in: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2010). New York, NY: ACM, 2010. 8 pages.

Efficiently Evolving Programs through the Search for Novelty
Joel Lehman and Kenneth O. Stanley
School of Electrical Engineering and Computer Science, University of Central Florida
To appear in: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2010). New York, NY: ACM, 2010. 8 pages.

Evolving the Placement and Density of Neurons in the HyperNEAT Substrate
Sebastian Risi, Joel Lehman, and Kenneth O. Stanley
School of Electrical Engineering and Computer Science, University of Central Florida
To appear in: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2010). New York, NY: ACM, 2010. 8 pages.
Winner of the Best Paper Award in the Generative and Developmental Systems track at GECCO-2010

Transfer Learning through Indirect Encoding
Phillip Verbancsics and Kenneth O. Stanley
School of Electrical Engineering and Computer Science, University of Central Florida
To appear in: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2010). New York, NY: ACM, 2010. 8 pages.
Nominated for Best Paper Award in the Generative and Developmental Systems track at GECCO-2010

Evolving Policy Geometry for Scalable Multiagent Learning
David B. D.Ambrosio, Joel Lehman, Sebastian Risi, and Kenneth O. Stanley
School of Electrical Engineering and Computer Science, University of Central Florida
To appear in: Proceedings of the Ninth International Conference on Autonomous Agents and Multiagent Systems (AAMAS-2010). 8 pages.

Search-based Procedural Content Generation
Julian Togelius, Georgios N. Yannakakis, Kenneth O. Stanley, and Cameron Browne
To appear in: Proceedings of 2nd European event on Bio-inspired Algorithms in Games (EvoGAMES 2010). New York, NY: Springer, 2010. 10 pages.

Learning to Dance through Interactive Evolution
Greg Dubbin and Kenneth O. Stanley
School of Electrical Engineering and Computer Science, University of Central Florida
To appear in: Proceedings of the Eighth European Event on Evolutionary and Biologically Inspired Music, Sound, Art and Design (EvoMUSART 2010). New York, NY: Springer, 2010. 10 pages.

Evolving Content in the Galactic Arms Race Video Game
Erin Hastings, Ratan Guha, and Kenneth O. Stanley
School of Electrical Engineering and Computer Science, University of Central Florida
To appear in: Proceedings of the IEEE Symposium on Computational Intelligence and Games (CIG'09). Piscataway, NJ: IEEE, 2009. 8 pages.
Winner of the Best Paper Award at 2009 IEEE Symposium on Computational Intelligence and Games

Demonstrating Automatic Content Generation in the Galactic Arms Race Video Game
Erin Hastings, Ratan Guha, and Kenneth O. Stanley
School of Electrical Engineering and Computer Science, University of Central Florida
To appear in: Proceedings of the Artificial Intelligence and Interactive Digital Entertainment Conference Demonstration Program (AIIDE.09). Menlo Park, CA:AAAI, 2009. 2 pages.
Note: This paper is a short 2-page synopsis that accompanied a live demonstration booth. See other GAR papers for more complete treatments.

How Novelty Search Escapes the Deceptive Trap of Learning to Learn
Sebastian Risi, Sandy D. Vanderbleek, Charles E. Hughes and Kenneth O. Stanley
School of Electrical Engineering and Computer Science, University of Central Florida
To appear in: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2009). New York, NY: ACM, 2009. 8 pages.
Winner of the Best Paper Award in the Artificial Life, Evolutionary Robotics, Adaptive Behavior, Evolvable Hardware Track at GECCO-2009

Exploiting Open-Endedness to Solve Problems Through the Search for Novelty
Joel Lehman and Kenneth O. Stanley
School of Electrical Engineering and Computer Science, University of Central Florida
To appear in: Proceedings of the Eleventh International Conference on Artificial Life (ALIFE XI). Cambridge MA: MIT Press, 2008. 8 pages.

Generative Encoding for Multiagent Learning
David B. D'Ambrosio and Kenneth O. Stanley
School of Electrical Engineering and Computer Science, University of Central Florida
To appear in: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2008). New York, NY: ACM, 2008. 8 pages.
Accompanied by videos of evolved multiagent behavior.
Winner of the Best Paper Award in Generative and Developmental Systems at GECCO 2008

A Case Study on the Critical Role of Geometric Regularity in Machine Learning
Jason J. Gauci and Kenneth O. Stanley
School of Electrical Engineering and Computer Science, University of Central Florida
To appear in: Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence (AAAI-2008). Menlo Park, CA: AAAI Press, 2008 (6 pages)

Picbreeder: Evolving Pictures Collaboratively Online
Jimmy Secretan, Nicholas Beato, David B. D'Ambrosio, Adelein Rodriguez, Adam Campbell and Kenneth O. Stanley
School of Electrical Engineering and Computer Science, University of Central Florida
To appear in: Proceedings of Computer Human Interaction Conference (CHI 2008). New York, NY: ACM, 2008 (10 pages)

Scaffolding for Interactively Evolving Novel Drum Tracks for Existing Songs
Amy K. Hoover, Michael P. Rosario, and Kenneth O. Stanley
School of Electrical Engineering and Computer Science, University of Central Florida
In: Proceedings of the Sixth European Workshop on Evolutionary and Biologically Inspired Music, Sound, Art and Design (EvoMUSART 2008). New York, NY: Springer, 2008. 10 pages.
Winner of the Best Paper Award at EvoMUSART 2008

Generating Large-Scale Neural Networks Through Discovering Geometric Regularities
Jason J. Gauci and Kenneth O. Stanley
School of Electrical Engineering and Computer Science, University of Central Florida
To appear in: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2007). New York, NY: ACM, 2007. 8 pages.

A Novel Generative Encoding for Exploiting Neural Network Sensor and Output Geometry
David B. D'Ambrosio and Kenneth O. Stanley
School of Electrical Engineering and Computer Science, University of Central Florida
To appear in: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2007). New York, NY: ACM, 2007. 8 pages.
Nominated for Best Paper Award in the Generative and Developmental Systems track at GECCO-2007

NEAT Particles: Design, Representation, and Animation of Particle System Effects
Erin Hastings, Ratan Guha, and Kenneth O. Stanley
School of Electrical Engineering and Computer Science, University of Central Florida
To appear in: Proceedings of the IEEE Symposium on Computational Intelligence and Games (CIG'07). Piscataway, NJ: IEEE, 2007. 7 pages.

Exploiting Regularity Without Development
Kenneth O. Stanley
School of Electrical Engineering and Computer Science, University of Central Florida
To appear in: Proceedings of the AAAI Fall Symposium on Developmental Systems. Meno Park, CA: AAAI Press, 2006. 8 pages.

EVOLVING NEURAL NETWORK AGENTS IN THE NERO VIDEO GAME
Kenneth O. Stanley, Bobby D. Bryant, and Risto Miikkulainen
Department of Computer Sciences, The University of Texas at Austin
Proceedings of the IEEE 2005 Symposium on Computational Intelligence and Games (CIG'05). Piscataway, NJ: IEEE, 2005.
Winner of the Best Paper Award at CIG'05

RETAINING LEARNED BEHAVIOR DURING REAL-TIME NEUROEVOLUTION
Thomas D'Silva, Roy Janik, Michael Chrien, Kenneth O. Stanley, and Risto Miikkulainen
Department of Computer Sciences, The University of Texas at Austin
In:Proceedings of the Artificial Intelligence and Interactive Digital Entertainment Conference (AIIDE 2005).

REAL-TIME LEARNING IN THE NERO VIDEO GAME
Kenneth O. Stanley, Ryan Cornelius, Risto Miikkulainen, Thomas D'Silva, and Aliza Gold
Department of Computer Sciences, The University of Texas at Austin
In:Proceedings of the Artificial Intelligence and Interactive Digital Entertainment Conference Demonstration Program (AIIDE 2005).
Note: This paper is a short synopsis that accompanied a live demonstration booth

NEUROEVOLUTION OF AN AUTOMOBILE CRASH WARNING SYSTEM
Kenneth O. Stanley, Nate Kohl, Rini Sherony, and Risto Miikkulainen
Department of Computer Sciences, The University of Texas at Austin
In:Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2005).

AUTOMATIC FEATURE SELECTION IN NEUROEVOLUTION
Shimon Whiteson, Peter Stone, Kenneth O. Stanley, Risto Miikkulainenn and Nate Kohl
Department of Computer Sciences, The University of Texas at Austin
In:Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2005).

TOWARDS AN EMPIRICAL MEASURE OF EVOLVABILITY
Joseph Reisinger, Kenneth O. Stanley, and Risto Miikkulainenn
Department of Computer Sciences, The University of Texas at Austin
In:Proceedings of the Genetic and Evolutionary Computation Conference Workshop Program (GECCO-2005).

EVOLVING A ROVING EYE FOR GO
Kenneth O. Stanley and Risto Miikkulainen
Department of Computer Sciences, The University of Texas at Austin
Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2004). New York, NY: Springer-Verlag, 2004.

EXPLOITING MORPHOLOGICAL CONVENTIONS FOR GENETIC REUSE
Kenneth O. Stanley, Joseph Reisinger, and Risto Miikkulainen
Department of Computer Sciences, The University of Texas at Austin
Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2004) Workshop Program. New York, NY: Springer-Verlag, 2004
GECCO Workshop on Modularity, Regularity, and Hierarchy in Evolutionary Computation

EVOLVING REUSABLE NEURAL MODULES
Joseph Reisinger, Kenneth O. Stanley, and Risto Miikkulainen
Department of Computer Sciences, The University of Texas at Austin
Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2004). New York, NY: Springer-Verlag, 2004.

AUTOMATIC FEATURE SELECTION IN NEUROEVOLUTION (older workshop version)
Shimon Whiteson, Kenneth O. Stanley, and Risto Miikkulainen
Department of Computer Sciences, The University of Texas at Austin
Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2004) Workshop Program. New York, NY: Springer-Verlag, 2004
GECCO Workshop on Self-organization in Representations for Evolutionary Algorithms

EVOLVING ADAPTIVE NEURAL NETWORKS WITH AND WITHOUT ADAPTIVE SYNAPSES
Kenneth O. Stanley, Bobby D. Bryant, and Risto Miikkulainen
Department of Computer Sciences, The University of Texas at Austin
Proceedings of the 2003 IEEE Congress on Evolutionary Computation (CEC-2003). Canberra, Australia: IEEE Press, 2003.

ACHIEVING HIGH-LEVEL FUNCTIONALITY THROUGH COMPLEXIFICATION
Kenneth O. Stanley and Risto Miikkulainen
Department of Computer Sciences, The University of Texas at Austin
Proceedings of the AAAI-2003 Spring Symposium on Computational Synthesis. Stanford, CA: AAAI Press, 2003.

EFFICIENT REINFORCEMENT LEARNING THROUGH EVOLVING NEURAL NETWORK TOPOLOGIES
Kenneth O. Stanley and Risto Miikkulainen
Department of Computer Sciences, The University of Texas at Austin
Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2002). San Francisco, CA: Morgan Kaufmann, 2002.
Winner of the Best Paper Award in Genetic Algorithms

CONTINUAL COEVOLUTION THROUGH COMPLEXIFICATION
Kenneth O. Stanley and Risto Miikkulainen
Department of Computer Sciences, The University of Texas at Austin
Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2002). San Francisco, CA: Morgan Kaufmann, 2002.

THE DOMINANCE TOURNAMENT METHOD FOR MONITORING PROGRESS IN COEVOLUTION
Kenneth O. Stanley and Risto Miikkulainen
Department of Computer Sciences, The University of Texas at Austin
Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2002) Workshop Program. San Francisco, CA: Morgan Kaufmann, 2002.
Analysis of Coevolution Workshop Link

EFFICIENT EVOLUTION OF NEURAL NETWORK TOPOLOGIES
Kenneth O. Stanley and Risto Miikkulainen
Department of Computer Sciences, The University of Texas at Austin
Proceedings of the 2002 Congress on Evolutionary Computation (CEC '02). Piscataway, NJ: IEEE, 2002.

Off-topic
The following tech report describes an algorithm for tracking concept drift that is unrelated to NEAT and my usual research:

LEARNING CONCEPT DRIFT WITH A COMMITTEE OF DECISION TREES
Kenneth O. Stanley
Department of Computer Sciences, The University of Texas at Austin
Technical Report AI-03-302, September 2003.

Contact me here:
kstanley@cs.ucf.edu .