Neural Networks Best-Paper Award
11/22/2024

Neural Networks, the official journal of the International Neural Network Society, selects one paper each year for the Best-Paper Award: for 2022, that paper is Bingham and Miikkulainen's Discovering parametric activation functions. The paper was part of Garrett's dissertation; it shows how activation functions can be customized for deep learning architectures and tasks through a combination of evolution and gradient descent. The award will be presented at the International Joint Conference on Neural Networks (IJCNN2025) in July 2025.

Risto Elected to INNS College of Fellows
8/13/2024

International Neural Network Society (INNS) has been the premier scientific society in the field since 1987. The Fellows of the Society are recognized both for their scientific accomplishments and service to the Society. The College of Fellows includes many of the founders and long-time leaders of the field---to be part of it is a humbling honor!

Best Dissertation Honorable Mention to Garrett Bingham
7/18/2024

Garrett Bingham's dissertation Optimizing Neural Networks through Activation Function Discovery and Automatic Weight Initialization was selected as a "honourable mention" of the 2024 ACM SIGEVO Best Dissertation Award, with the citation "This dissertation advances evolutionary machine learning by introducing methods for automating activation function discovery and optimizing weight initialization strategies for arbitrary neural networks. These contributions bring us closer to being able to evolve an agent capable of recursive self-improvement, thus taking a step towards AGI." The award was announced at the GECCO'2024 closing ceremony in Melbourne. Garrett has open-sourced much of his research, including AQuaSurF code and Act-Bench benchmark dataset for activation function search, and AutoInit for intelligent network initialization. He is currently a research scientist at Google DeepMind. Congratulations Garrett!

Best-paper Honorable Mention at ICDL
5/23/2024

The paper on Using context to adapt to sensor drift, by Jamie Warner, Ashwin Devaraj, and Risto won the "Best-Paper Honorable Mention" at the International Conference on Development and Learning (ICDL-2024, Austin, TX). The idea is to model the context as a separate neural network module, and use it to modulate the outputs of the recognition network. This is a version of the context+skill approach originally proposed by Xun Li for opponent modeling in poker, and used by Cem Tutum and Suhaib Abdulquddos in various control tasks. The code for the sensor drift application as well as the control applications is available at our GitHub repository.

Climate Change AI Award
1/16/2024

The paper on Discovering Effective Policies for Land-Use Planning, by Risto and two former UT students Elliot Meyerson and Daniel Young, won the "Best Pathway to Impact Award" at the NeurIPS Workshop on Tackling Climate Change with Machine Learning. The idea is to use data on past land-use, and a simulator data for carbon emissions, to recommend how land should be best used to minimize change and minimize climate impact. To get a concrete idea of how it works, try out the interactive demo; there's also a prerecorded talk, slides, poster, and a short version of the paper at the workshop site. The land-use planning project is the first use case of Project Resilience, a non-profit group sponsored by the ITU agency of the United Nations, and was first presented at their AI For Good Summit in July 2023.

Two Projects on Language Rehabilitation Started
9/1/2023

The two projects continue our collaboration with Swathi Kiran's lab at Boston University. The first is a new 5-year NIH grant where the the BiLex model of bilingual lexical naming will be extended to slowing down decline in dementia, and to language control in aphasia and dementia. A related project with Constant Therapy looks into recommending exercises in rehabilitation in a mobile app. Uli Grasemann and Chloe Chen will be the key contributors to these projects at UT. A recent Austin Next podcast described these topics and the role of AI in general.

Risto Named AAAI Fellow
1/20/2023

Risto Miikkulainen was elected Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) in the 2023 cohort. The award was given "For significant contribution to neuroevolution techniques and applications." It is nice to see the work, and the area in general, recognized by the broader AI community!

Meyerson wins GECCO Awards
7/13/2022

Elliot Meyerson (NNRG PhD 2018) and Risto Miikkulainen received two awards at the Genetic and Evolutionary Computation Conference (GECCO): First, a Best-Paper award in Genetic Algorithms for Simple Genetic Operators are Universal Approximators of Probability Distributions (and other Advantages of Expressive Encodings) (together with Xin Qiu). This paper shows empirically and theoretically that solution representations can be as important as search operators in improving performance. Second, they won a Silver Award in the Human Competitive Results Competition for Evaluating Medical Aesthetics Treatments through Evolved Age-Estimation Models (together with Xin Qiu, Ujjayant Sinha, Raghav Kumar, Karen Hofmann, Matt Yan, Michael Ye, Jingyuan Yang, Damon Caiazza, and Stephanie Manson Brown). This paper improves the state-of-the art in age estimation from face images (with about half the error of human estimation), but also shows that evolutionary metalearning methods can discover more accurate models than those designed by human data scientists.

Podcasts!
10/12/2021

Science podcasts have become popular during the pandemic, and we have done a number of them. On top of the list is Risto's 2-hr interview in the Lex Fridman podcast. He also discussed the XPRIZE Pandemic Response Challenge in The Pulse of AI podcast with winners Nuria Oliver and Mitja Lustrek, and co-organized a series of five podcasts with Stephanie Forrest, Joydeep Ghosh, Babak Hodjat, Quoc Le, and Jordan Pollack. Padmini Rajagopalan discussed her work on emergence of cooperation in the College of Natural Sciences podcast, and Risto earlier appeared in the Biotech Podcast, Futucast, and This Week in Machine Learning. Podcasts can make science topics more live and personal while we wait for return to in-person talks.

XPRIZE Pandemic Response Challenge Concludes
3/13/2021

The XPRIZE Pandemic Response Challenge concluded with the announcement of two winners: a first-place team from Spain and a second-place team from Slovenia, splitting the prize purse of $500K. Eight other teams received an honorable mention. The teams employed a variety of techniques from standard epidemiological modeling to evolutionary optimization. Significant new technology was also developed (by the Cognizant's Evolutionary AI research team) to evaluate the predictors and prescriptors in the competition. Of particular note is a method that allows evaluating how much each prescriptor contributes to a collaborative prescriptor, i.e. one built by bringing all the submissions together. Publicity for the competition achieved over a billion media impressions, thereby drawing attention to science in dealing with the pandemic. Similar collaborative opportunities as well as deployments informing real-world policies will be pursued in the follow-up to the competition.

XPRIZE Pandemic Response Challenge Starts
12/8/2020

The XPRIZE Pandemic Response Challenge focuses on building better predictors and better prescriptors for non-pharmaceutical interventions (such as restrictions on schools, workplaces, gatherings, transportation) in the COVID-19 pandemic. Cognizant's Evolutionary AI research team (which includes current and former NNRG people Elliot Meyerson, Jason Liang, and Garrett Bingham) built the platform on it, based on the interactive demo using Evolutionary Surrogate-assisted Prescription. With support from Cognizant, the top teams will share a $500,000 prize purse. The idea is to develop technology that will make it possible to manage the end of this pandemic better, including interventions through vaccination, as well as helping cope with future pandemics and other similar decision-making challenges.

Best-Paper Awards at GECCO and CEC 2020
7/22/2020

Olivier Francon, Santiago Gonzalez (current NNRG PhD student), Babak Hodjat, Elliot Meyerson (NNRG PhD 2018), Risto Miikkulainen, Xin Qiu, and Hormoz Shahrzad won a Best-Paper Award at the Genetic and Evolutionary Computation Conference (GECCO GECH track) for Effective Reinforcement Learning through Evolutionary Surrogate-Assisted Prescription. This method is the core of e.g. their COVID-19 non-pharmaceutical intervention recommendation system (see interactive demo).

Padmini Rajagopalan (NNRG PhD 2016), Kay Holekamp (MSU), and Risto Miikkulainen won the Best-Paper Award at the 2020 IEEE Congress on Evolutionary Computation for their paper on Evolution of Complex Coordinated Behavior. This work was based on an interdisciplinary collaboration in the NSF-funded BEACON-Center, demonstrating computationally how hyenas in Serengeti-Mara may have evolved a coordinated attack that allows them to steal a kill from lions. See a video of this behavior, and CNS Podcast for a summary of this research.

Evolutionary AI for Optimizing COVID-19 Interventions
7/3/2020

Cognizant's Evolutionary AI research team (which includes current and former NNRG people Elliot Meyerson, Jason Liang, Santiago Gonzalez, Garrett Bingham, and Kaitlin Maile) recently published a website on evolutionary optimization on decision making. A major part of this research is an application in optimizing non-pharmaceutical interventions in the COVID-19 pandemic (such as restrictions on schools, workplaces, gatherings, transportation). The site features an interactive demo that allows you to explore prescriptors, i.e. decision policies from the Pareto front between minimizing the number of cases and minimizing the stringency of the interventions, predicting how the pandemic is likely to unfold for different countries in the future.

Heidelberg Laureate Forum
9/28/2019

Kaitlin Maile attended the 7th Heidelberg Laureate Forum in Heidelberg, Germany, as an invited young researcher from September 22–27, 2019. Each year, the recipients of the most prestigious awards in mathematics and computer science, the Abel Prize, ACM A.M. Turing Award, ACM Prize in Computing, Fields Medal, and Nevanlinna Prize, meet 200 selected young researchers in computer science and mathematics from all over the world. Participants spent a week interacting and networking in a relaxed atmosphere designed to encourage scientific exchange.

Evolutionary Computation Pioneer Award
8/1/2019

Risto is the recipient of the 2020 IEEE CIS Evolutionary Computation Pioneer Award that "recognizes significant contributions to early concepts and sustained developments in the field of evolutionary computation." It is given by the IEEE Computational Intelligence Society, i.e. the part of IEEE that focuses on Neural Networks, Fuzzy Systems, and Evolutionary Computation (i.e., modern AI). The award will be given at one of the IEEE conferences in 2020, most likely World Congress on Computational Intelligence (WCCI) in July 2020.

Nature Article on Neuroevolution Published
1/7/2019

A review article on Neuroevolution was featured in the inaugural issue of Nature Machine Intelligence. The article was co-authored by Ken Stanley, Jeff Clune, Joel Lehman, and Risto Miikkulainen. This is perhaps the most visible article to date in this field!

Two Lifelong Learning Machines Projects Started
8/1/2018

We have two new projects under DARPA's Lifelong Learning Machines program: "STELLAR: Super Turing Evolving Lifelong Learning ARchitecture" is a multi-institutional project led by HRL Laboratories where the goal is to use neuroevolution in conjunction with reinforcement learning, memory, neuromodulation, and supervised learning to build a complex adaptive control system; "Context-Dependent Reconfiguration of an Intelligent Neural System," with University of Chicago (lead) and Cornell University focusing on lifelong learning in the olfactory system. Both projects build on the opponent modeling framework in Xun Li's dissertation where evolution is operating in two different timescales. Cem Tutum is our lead investigator in both projects.

Evolution is the New Deep Learning
3/14/2018

Working with colleagues at Sentient Technologies, Jason Liang, Elliot Meyerson, and Aditya Rawal have been building a case for why evolution is the technology of the future. In short: the same way deep learning has benefited from big compute, modern evolutionary computation can too, and thereby can advance machine creativity. Our website with this theme went live this morning! (See also a blog post introducing this site.) We are showcasing five new papers, but the fun part is the 11 animated demos and three interactive demos illustrating evolutionary computation. The goal is to get the word out, i.e. to get people thinking and talking about evolutionary computation. Spread the word!

Outstanding Paper of the Decade Award
9/6/2017

The International Society for Artificial Life awarded Ken Stanley and Risto Miikkulainen the 2017 Outstanding Paper of the Decade (2001-2012) award for their paper on Evolving Neural Networks Through Augmenting Topologies, Evolutionary Computation 10:99--127, 2002. This paper described the NEAT method for evolving neural networks, a method that is often used in modeling adaptive behavior. And it is still going strong!

GECCO Best Paper Award
7/20/2017

Eric A. Yu, Jin Yeom, Cem Tutum, Etienne Vouga, and Risto Miikkulainen won the Best-Paper Award in the Real-World Applications track at the GECCO 2017 Conference for their paper on Evolutionary Decomposition for 3D Printing. Eric and Jin were students in the FRI program as freshmen, and did this work while serving as mentors in the FRI stream taught by Cem Tutum. College of Natural Sciences did a nice news story on their work.

DISLEX Model tested in a Clinical Trial
5/27/2017

A new NIH grant, Predicting Rehabilitation Outcomes In Bilingual Aphasia Using Computational Modeling started in July 2016 with familiar personnel: Uli Grasemann returned to UT to lead the computational modeling work, and Swathi Kiran at Boston University leads the clinical work. Building on our prior grant, the goal is to use self-organizing maps with associative connections, i.e. the DISLEX model, to understand damage and recovery of the lexical system in bilinguals. However in this new grant (starting this summer), the model is put into an actual clinical trial, predicting optimal treatment for actual patients. To our knowledge, this is the first time a computational cognitive model has served in this role! See our earlier paper for a background on this project.

Evolutionary Computation in the Real World
9/13/2016

Sentient Technologies, Inc. (where Risto currently is on a leave) just launched a novel application of evolutionary computation on e-commerce. Their Ascend is a system for designing web pages automatically in order to maximize conversions (i.e. user actions such as purchases or sign-ups). Evolution generates web page candidates that are then tested on real users in real time. This blog post describes the technology in more detail.

Risto Elevated to IEEE Fellow
1/6/2016

Risto Miikkulainen was elevated to Fellow of the IEEE in the 2016 cohort of the Computational Intelligence Society. The award was given "for contributions to neural and evolutionary computation." Less than 0.1\% of voting members are selected annual as Fellows, so this is an excellent recognition of our work!

INNS Gabor Award
12/7/2015

Risto received the Dennis Gabor Award of the International Neural Network Society. This award recognizes "outstanding contributions to engineering applications of neural networks;" in this case, neuroevolution.

NNRG in the media
8/22/2015 (updated 3/15/2016)

The work of NNRG and its alumni has recently been featured in a number of media outlets. For instance, UT's press release on Joel Lehman and Risto Miikkulainen's PLOS ONE article on how extinctions can accelerate evolution was picked up by a number of sites, including the National Science Foundation, Science Daily, phys.org, and even the Daily Mail. It generated much discussion e.g. on Twitter and io9, and a hilarious interview/skit with TexasExes. Ken Stanley and Joel Lehman's new book on novelty search was the focus of an article on FiveThirtyEight and Ken's radio interview. Dan Lessin's research was featured in the Robohub robotics news site. Risto was recently interviewed about game AI by the KXAN TV channel and about strong AI by the Austin American Statesman newspaper, and about evolutionary computation by David Beyer for O'Reilly Radar Podcast. Also, a well-known gamer Seth Bling used NEAT to create a Mario-playing agent---a YouTube video of it has over 2 million views. The word is getting out!

Schrum wins GECCO Best Paper Award---again!
7/15/2015

Jacob Schrum and Risto Miikkulainen won the Best Paper Award in the Digital Entertainment and Arts track at the GECCO 2015 Conference for their paper on Solving Interleaved and Blended Sequential Decision-Making Problems through Modular Neuroevolution. Jacob received his PhD in Spring 2014 and is currently an Assistant Professor at Southwestern University. This is his second such award, following the one from GECCO-2014. In addition he has won two best paper awards from the IEEE Conference on Computational Intelligence and Games, in 2011 and 2009. Way to go Jacob!

Schrum wins GECCO Best Paper Award
7/16/2014

Jacob Schrum and Risto Miikkulainen won the Best Paper Award in the Digital Entertainment and Arts track at the GECCO 2014 Conference for their paper on Evolving Multimodal Behavior With Modular Neural Networks in Ms. Pac-Man. Jacob received his PhD in Spring 2014 and will be an Assistant Professor at Southwestern University in Fall 2014.

NIH and IARPA projects started
11/15/2013

In the Role of Emotion and Communication in Cooperative Behavior project the goal is to understand how these cognitive facilities contribute to mobbing behavior, as observed in hyenas and in a computational model. The project is funded by the Modeling Social Behavior of the NIH. In the Knowledge Representation as Embodied Abstractionsproject a team of researchers (led by Teledyne Scientific, Inc., and including the NNRG at UT) is aiming to model how representations of concepts in the brain are shaped by context. This project is funded by the Knowledge Representation in Neural Systems program of IARPA.

Lockett and Waters win awards
8/5/2013

Alan Lockett received a runner-up award for the Best Overall Paper at the 2013 IEEE Congress on Evolutionary Computation for his paper on Measure-Theoretic Analysis of Performance in Evolutionary Algorithms. Alan received his PhD with the NNRG last year and is currently a postdoctoral researcher at IDSIA, Switzerland.

Austin Waters and Risto Miikkulainen received an IAAI Deployed Application Award at the 2013 AAAI Conference for their paper on GRADE: Machine Learning Support for Graduate Admissions. GRADE is used in the UTCS Department to evaluate applicants to the PhD program, reducing the workload of the admissions committee by 74%.

Neuroevolution Scholarpedia Article Published
6/7/2013

Lehman and Miikkulainen recently authored an article on Neuroevolution in Scholarpedia, the peer-reviewed open-access encyclopedia. This article reviews more than two decades of research on evolution of neural networks, a technique that has proven to be a practical engineering methodology as well as a novel tool for exploring biological hypotheses. This article is the the latest step in our effort to educate people in this area, following several tutorials since 2005 at GECCO, IJCNN, WCCI, and Alife, and the development of OpenNERO software platform for AI education.

The UT^2 Bot wins BotPrize
9/15/2012

For the first time in the five-year history of the BotPrize Competition (i.e. the "Turing test for game bots" in the Unreal 2004 video game), the best bots were judged as human more than 50% of the time, resulting in the awarding of the actual BotPrize sponsored by 2K Games. Two bots achieved this feat; one of them was the UT^2 bot created by Igor Karpov, Jacob Schrum, and Risto Miikkulainen, based on neuroevolution of combat behavior and navigation based on human traces. For more details, see our BotPrize project page and the official BotPrize Competition page, and listen to/watch interviews on Digital Nibbles and aigamedev.org.

The UT^2 Bot wins Humanlike-Bot Competition
6/13/2012

As part of the IEEE World Congress on Computational Intelligence (WCCI 2012) in Brisbane, Australia, a competition was held in a "Turing test for game bots", i.e. for the most humanlike game agents in the Unreal 2004 video game. The UT^2 bot, created by Igor Karpov, Jacob Schrum, and Risto Miikkulainen won the competition with a 21% humanness rating, which for the first time was better than half the human players. See this year's results and general description of the BotPrize Competition for more details.

Online OpenNERO Tournament Demonstrates a "Machine Learning Game"
1/31/2012

The tournament was run in the NERO machine learning game of the OpenNERO software system in Dec 2012. Most of the 159 participants came from the Stanford Online AI course, and some from the cs343 and cs394n courses at UT Austin. Most teams were trained with neuroevolution and some with Q-learning. The results showed that surprisingly diverse strategies can be successful, and no single strategy dominates all others---which indeed makes the game an interesting challenge for humans and machine learning alike. See the tournament results page for details.

Schrum wins CIG-11 Best Paper Award
9/8/2011

Jacob Schrum won the Best Paper Award at the 2011 IEEE Conference on Computational Intelligence and Games for his paper with Risto Miikkulainen on Evolving Multimodal Networks for Multitask Games. Multitask games are domains in which separate tasks within the domain each have their own dynamics and objectives. The methods described in the paper allow evolved neural networks to use multiple output modes to better learn multiple modes of behavior in multitask games. Videos of evolved behavior can be seen here.

Silverthorn again wins solver competition
8/1/2011

The Borg algorithm portfolio, developed by Bryan Silverthorn, has placed first in the main category of the annual pseudo-Boolean solver competition for the second year in a row. The competition tests a program's ability to solve difficult computational problems, such as finding bugs in software and hardware, expressed in "pseudo-Boolean" mathematical form. Borg succeeds by using multiple algorithms and automatically choosing which to apply to each problem. Its recent improvements include better predictions of whether an algorithm will succeed, and better schedules of when an algorithm should be executed. Borg's continued success demonstrates the promise of its portfolio approach: solving larger sets of more challenging problems, more quickly.

Computational Modeling of Schizophrenia
5/13/2011

Uli Grasemann's work (with Ralph Hoffman and Risto Miikkulainen) on computational modeling of schizophrenia has reached an unusually wide audience. After UT did a press release on it, the story was Slashdotted, and then spread to several venues from the Chronicle of Higher Education and NPR's Science Friday to somewhat unexpected venues such as IEEE Spectrum, Business Week and Popular Mechanics. Some of the most interesting headlines include "Computer takes responsibility for terrorist bombing" and "Boffins develop method of driving computers insane." Nevertheless, the interest demonstrates that connectionist modeling has perhaps become mature enough so that it can be now a topic of public discussion.

BEACON Center started
8/1/2010

BEACON is an NSF Science and Technology Center, focusing on "Evolution in Action", i.e. interdisciplinary approaches to understanding biological and computational evolution. It is a consortium of Michigan State University (the lead institution), University of Idaho, University of Texas, University of Washington, and North Carolina A&T University, with a total funding of $25M over five years. Several people in the NNRG participate in BEACON's activities, and Risto is the lead for the UT subcontract. For more details, see the BEACON website.

Silverthorn wins solver competition
7/24/10

Bryan Silverthorn's Borg program won the main category of the Fifth Annual Competition of Pseudo-Boolean Solvers at the Thirteenth International Conference on Theory and Applications of Satisfiability Testing. This international competition compared systems for solving pseudo-Boolean expressions, which are used to address problems such as the correctness of electronic circuit designs. Bryan's program succeeded by applying multiple solution methods, executing them according to statistical patterns that it automatically discovered from experience. For more details see the Borg project page.

Three projects started, with funding from NSF and Google
12/1/09

In the NSF Robust Intelligence project, our work on evolving neural networks in control tasks will be extended to sequential decision making at the strategic level. It makes use of the OpenNERO project, funded by Google, Inc., where we are extending the NERO machine learning game into a general AI research and education platform. In the interdisciplinary NSF SciSIP project, the goal is to understand competitive multiagent search, and apply it to organizational theory on how high-technology firms can best innovate.

Schrum wins CIG-09 Best Student Paper Award
09/09/09

Jacob Schrum won the Best Student Paper Award at the 2009 IEEE Symposium on Computational Intelligence and Games for his paper with Risto Miikkulainen on Evolving Multi-modal Behavior in NPCs. See also videos of evolved behaviors.

New NSF, NIH, and ARP projects started
12/1/08

In the NSF-supported "CreativeIT" project, the goal is to leverage human intuition with neuroevolution discovery of complex behavior. In the ARP project, we are utilizing simulated environments like OpenNERO to learn complex high-level behaviors. Both of these projects build on our prior work on evolving neural networks. The NIH project, in turn, continues our cognitive science research stream: A model of bilingual lexicon is being built in order to study how it breaks down in aphasia, and how the performance can be best regained through rehabilitation.

Valsalam and Miikkulainen win a GECCO Best Paper Award
7/16/08

Vinod Valsalam and Risto Miikkulainen won the Best Paper Award in the "Artificial Life, Evolutionary Robotics, Adaptive Behavior, Evolvable Hardware" track of GECCO-2008 for their paper Modular Neuroevolution for Multilegged Locomotion. See also videos of walking behaviors.

New NNRG website launched
1/1/2008

The site has moved to a departmental server, it has a new look and feel (under the same design), and now includes a "demos" area that will be populated over the next few months. Please bear with us as we complete the transition and add the content.

NERO 2.0 released
09-06-2007

A new, significantly extended version of the NERO Machine Learning Game, based on rtNEAT neuroevolution, was released in Fall 2007. This version includes an interactive game mode, a new user interface, and more extensive training tools.

Reisinger and Miikkulainen win a Best Paper Award
07-11-2007

Joe Reisinger and Risto Miikkulainen won the Best Paper award in the Generative and Developmental Systems track at GECCO 2007, for their paper "Acquiring Evolvability through Adaptive Representations."

Computational Maps in the Visual Cortex published
12-15-2005

This book, co-authored by Risto Miikkulainen, James A. Bednar, Yoonsuck Choe, and Joseph Sirosh, and published by Springer, reviews 18 years of research by the UTCS Neural Networks Research Group on modeling the visual cortex. The book is accompanied by the Topographica software package for general modeling of computational maps.

Bednar, Grasemann, Miikkulainen, Sit, and Valsalam win awards at GECCO 2005
07-11-2005

Valsalam, Bednar, and Miikkulainen's Constructing Good Learners using Evolved Pattern Generators won the Best Paper Award in the Evolutionary Robotics, A-life, and Adaptive Behavior track, and Sit and Miikkulainen's Learning Basic Navigation for Personal Satellite Assistant using Neuroevolution in the Real World Applications track; Grasemann and Miikkulainen's Effective Image Compression using Evolved Wavelets won a Bronze Medal in the Human-Competitive Results Competition and was featured in NSF Discoveries.

Stanley, Bryant, and Miikkulainen win Best Paper Award
04-06-2005

Ken Stanley, Bobby Bryant, and Risto Miikkulainen won the Best Paper Award at the IEEE 2005 Symposium on Computational Intelligence and Games, for Evolving Neural Network Agents in the NERO Video Game. Risto gave a keynote talk and NERO producer Aliza Gold presented a paper on transfering academic AI to game applications.

NERO: A Pioneering Neuroevolution-based Video Game
06-20-2004

NERO demonstrates how neuroevolution can be used to adapt behaviors of autonomous agents in a complex real-time video game. Together with a team at UT Digital Media Collaboratory, Ken Stanley and Bobby Bryant have now completed the first prototype of NERO.

Neuroevolution Researchers Address Game Development Workshop
09-16-2003

Members of our neuroevolution group join stars from the world of computer game design in the second annual Game Development Workshop organized by the UT Digital Media Collaboratory, in an effort toward establlishing an ongoing technology transfer between academic AI research and the real-world considerations of commercial game development.

Gomez & Miikkulainen Win Best Paper Award
09-17-2003

Faustino Gomez and Risto Miikkulainen won the "Best of GECCO" award in the Real World Applications track at GECCO 2003, for their paper "Active Guidance for a Finless Rocket Using Neuroevolution"

UT Neural Networks Research Group Web Site Goes Live
06-03-2003

The Neural Networks Research Group at the University of Texas at Austin has redesigned and reprogrammed their website... and you're looking at it.

Stanley & Miikkulainen Win Best Paper Award
09-13-2001

Ken Stanley and Risto Miikkulainen's paper, Efficient Reinforcement Learning Through Evolving Neural Network Topologies," is the winner of the 2002 Best Paper Award in Genetic Algorithms.