Investigations in meta-GAs: panaceas or pipe dreams? - Jeff Clune; Sherri Goings; Bill Punch 001; Eric Goodman (GECCO Workshops, 2005)

Investigating the Emergence of Phenotypic Plasticity in Evolving Digital Organisms. - Jeff Clune; Charles Ofria; Robert T. Pennock (ECAL, 2007)

How generative encodings fare on less regular problems. - Jeff Clune; Charles Ofria; Robert T. Pennock (GECCO, 2008)

How a Generative Encoding Fares as Problem-Regularity Decreases. - Jeff Clune; Charles Ofria; Robert T. Pennock (PPSN, 2008)

Natural Selection Fails to Optimize Mutation Rates for Long-Term Adaptation on Rugged Fitness Landscapes. - Jeff Clune; Dusan Misevic; Charles Ofria; Richard E. Lenski; Santiago F. Elena; Rafael Sanjuán (PLoS Comput. Biol., 2008)

Evolving coordinated quadruped gaits with the HyperNEAT generative encoding. - Jeff Clune; Benjamin E. Beckmann; Charles Ofria; Robert T. Pennock (IEEE Congress on Evolutionary Computation, 2009)

HybrID: A Hybridization of Indirect and Direct Encodings for Evolutionary Computation. - Jeff Clune; Benjamin E. Beckmann; Robert T. Pennock; Charles Ofria (ECAL (2), 2009)

The Evolution of Division of Labor. - Heather Goldsby; David B. Knoester; Jeff Clune; Philip K. McKinley; Charles Ofria (ECAL (2), 2009)

The sensitivity of HyperNEAT to different geometric representations of a problem. - Jeff Clune; Charles Ofria; Robert T. Pennock (GECCO, 2009)

Problem decomposition using indirect reciprocity in evolved populations. - Heather Goldsby; Sherri Goings; Jeff Clune; Charles Ofria (GECCO, 2009)

Digital evolution with avida. - Benjamin E. Beckmann; Jeff Clune; Charles Ofria (GECCO (Companion), 2010)

Investigating whether hyperNEAT produces modular neural networks. - Jeff Clune; Benjamin E. Beckmann; Philip K. McKinley; Charles Ofria (GECCO, 2010)

Selective pressures for accurate altruism targeting: evidence from digital evolution for difficult-to-test aspects of inclusive fitness theory. - Jeff Clune; Heather J. Goldsby; Charles Ofria; Robert T. Pennock (ECAL, 2011)

Evolving three-dimensional objects with a generative encoding inspired by developmental biology. - Jeff Clune; Hod Lipson (ECAL, 2011)

Evolving robot gaits in hardware: the HyperNEAT generative encoding vs. parameter optimization. - Jason Yosinski; Jeff Clune; Diana Hidalgo; Sarah Nguyen; Juan Cristóbal Zagal; Hod Lipson (ECAL, 2011)

A novel generative encoding for evolving modular, regular and scalable networks. - Marcin Suchorzewski; Jeff Clune (GECCO, 2011)

Generating gaits for physical quadruped robots: evolved neural networks vs. local parameterized search. - Jason Yosinski; Jeff Clune; Diana Hidalgo; Sarah Nguyen; Juan Cristóbal Zagal; Hod Lipson (GECCO (Companion), 2011)

On the Performance of Indirect Encoding Across the Continuum of Regularity. - Jeff Clune; Kenneth O. Stanley; Robert T. Pennock; Charles Ofria (IEEE Trans. Evol. Comput., 2011)

Aracna: An Open-Source Quadruped Platform for Evolutionary Robotics. - Sara Lohmann; Jason Yosinski; Eric Gold; Jeff Clune; Jeremy Blum; Hod Lipson (ALIFE, 2012)

The evolutionary origins of modularity - Jeff Clune; Jean-Baptiste Mouret; Hod Lipson (CoRR, 2012)

Organizing Committee. - Sebastian Risi; Joel Lehman; Jeff Clune (AAAI Fall Symposia, 2013)

Preface. - Sebastian Risi; Joel Lehman; Jeff Clune (AAAI Fall Symposia, 2013)

Upload any object and evolve it: Injecting complex geometric patterns into CPPNS for further evolution. - Jeff Clune; Anthony Chen; Hod Lipson (IEEE Congress on Evolutionary Computation, 2013)

Evolving Gaits for Physical Robots with the HyperNEAT Generative Encoding: The Benefits of Simulation. - Suchan Lee; Jason Yosinski; Kyrre Glette; Hod Lipson; Jeff Clune (EvoApplications, 2013)

Unshackling evolution: evolving soft robots with multiple materials and a powerful generative encoding. - Nick Cheney; Robert MacCurdy; Jeff Clune; Hod Lipson (GECCO, 2013)

Hands-free Evolution of 3D-printable Objects via Eye Tracking - Nick Cheney; Jeff Clune; Jason Yosinski; Hod Lipson (CoRR, 2013)

Evolved Electrophysiological Soft Robots. - Nicholas Cheney; Jeff Clune; Hod Lipson (ALIFE, 2014)

Summary of "The Evolutionary Origins of Modularity". - Jeff Clune; Jean-Baptiste Mouret; Hod Lipson (ALIFE, 2014)

Automated generation of environments to test the general learning capabilities of AI agents. - Oliver J. Coleman; Alan D. Blair; Jeff Clune (GECCO, 2014)

Evolving neural networks that are both modular and regular: HyperNEAT plus the connection cost technique. - Joost Huizinga; Jeff Clune; Jean-Baptiste Mouret (GECCO, 2014)

Encouraging creative thinking in robots improves their ability to solve challenging problems. - Jingyu Li; Jed Storie; Jeff Clune (GECCO, 2014)

Novelty search creates robots with general skills for exploration. - Roby Velez; Jeff Clune (GECCO, 2014)

How transferable are features in deep neural networks? - Jason Yosinski; Jeff Clune; Yoshua Bengio; Hod Lipson (NIPS, 2014)

Reports on the 2013 AAAI Fall Symposium Series. - Gully Burns; Yolanda Gil; Yan Liu 002; Natalia Villanueva-Rosales; Sebastian Risi; Joel Lehman; Jeff Clune; Christian Lebiere; Paul S. Rosenbloom; Frank van Harmelen; James A. Hendler; Pascal Hitzler; et al. (AI Mag., 2014)

Robots that can adapt like natural animals. - Antoine Cully; Jeff Clune; Jean-Baptiste Mouret (CoRR, 2014)

An Anarchy of Methods: Current Trends in How Intelligence Is Abstracted in AI. - Joel Lehman; Jeff Clune; Sebastian Risi (IEEE Intell. Syst., 2014)

Deep neural networks are easily fooled: High confidence predictions for unrecognizable images. - Anh Mai Nguyen; Jason Yosinski; Jeff Clune (CVPR, 2015)

Innovation Engines: Automated Creativity and Improved Stochastic Optimization via Deep Learning. - Anh Mai Nguyen; Jason Yosinski; Jeff Clune (GECCO, 2015)

A method to improve signal quality in wireless ad-hoc networks with limited mobility. - Nicholas J. Gurbhoo; Robert F. Kubichek; Suresh Muknahallipatna; Jeff Clune (ICNC, 2015)

Illuminating search spaces by mapping elites. - Jean-Baptiste Mouret; Jeff Clune (CoRR, 2015)

Understanding Neural Networks Through Deep Visualization. - Jason Yosinski; Jeff Clune; Anh Mai Nguyen; Thomas J. Fuchs; Hod Lipson (CoRR, 2015)

Robots that can adapt like animals. - Antoine Cully; Jeff Clune; Danesh Tarapore; Jean-Baptiste Mouret (Nat., 2015)

Neural Modularity Helps Organisms Evolve to Learn New Skills without Forgetting Old Skills. - Kai Olav Ellefsen; Jean-Baptiste Mouret; Jeff Clune (PLoS Comput. Biol., 2015)

Does Aligning Phenotypic and Genotypic Modularity Improve the Evolution of Neural Networks? - Joost Huizinga; Jean-Baptiste Mouret; Jeff Clune (GECCO, 2016)

Evolvability Search: Directly Selecting for Evolvability in order to Study and Produce It. - Henok Mengistu; Joel Lehman; Jeff Clune (GECCO, 2016)

Neuromodulation Improves the Evolution of Forward Models. - Mohammad Sadegh Norouzzadeh; Jeff Clune (GECCO, 2016)

How do Different Encodings Influence the Performance of the MAP-Elites Algorithm? - Danesh Tarapore; Jeff Clune; Antoine Cully; Jean-Baptiste Mouret (GECCO, 2016)

Identifying Core Functional Networks and Functional Modules within Artificial Neural Networks via Subsets Regression. - Roby Velez; Jeff Clune (GECCO, 2016)

Creative Generation of 3D Objects with Deep Learning and Innovation Engines. - Joel Lehman; Sebastian Risi; Jeff Clune (ICCC, 2016)

Synthesizing the preferred inputs for neurons in neural networks via deep generator networks. - Anh Mai Nguyen; Alexey Dosovitskiy; Jason Yosinski; Thomas Brox; Jeff Clune (NIPS, 2016)

WebAL Comes of Age: A Review of the First 21 Years of Artificial Life on the Web. - Tim Taylor 001; Joshua Evan Auerbach; Josh C. Bongard; Jeff Clune; Simon J. Hickinbotham; Charles Ofria; Mizuki Oka; Sebastian Risi; Kenneth O. Stanley; Jason Yosinski (Artif. Life, 2016)

Convergent Learning: Do different neural networks learn the same representations? - Yixuan Li 001; Jason Yosinski; Jeff Clune; Hod Lipson; John E. Hopcroft (ICLR, 2016)

Multifaceted Feature Visualization: Uncovering the Different Types of Features Learned By Each Neuron in Deep Neural Networks. - Anh Mai Nguyen; Jason Yosinski; Jeff Clune (CoRR, 2016)

Understanding Innovation Engines: Automated Creativity and Improved Stochastic Optimization via Deep Learning. - Anh Nguyen 002; Jason Yosinski; Jeff Clune (Evol. Comput., 2016)

The Evolutionary Origins of Hierarchy. - Henok Mengistu; Joost Huizinga; Jean-Baptiste Mouret; Jeff Clune (PLoS Comput. Biol., 2016)

Plug & Play Generative Networks: Conditional Iterative Generation of Images in Latent Space. - Anh Nguyen 002; Jeff Clune; Yoshua Bengio; Alexey Dosovitskiy; Jason Yosinski (CVPR, 2017)

Automatically identifying wild animals in camera trap images with deep learning. - Mohammad Sadegh Norouzzadeh; Anh Nguyen 002; Margaret Kosmala; Ali Swanson; Craig Packer; Jeff Clune (CoRR, 2017)

Diffusion-based neuromodulation can eliminate catastrophic forgetting in simple neural networks. - Roby Velez; Jeff Clune (CoRR, 2017)

On the Relationship Between the OpenAI Evolution Strategy and Stochastic Gradient Descent. - Xingwen Zhang; Jeff Clune; Kenneth O. Stanley (CoRR, 2017)

Deep Neuroevolution: Genetic Algorithms Are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning. - Felipe Petroski Such; Vashisht Madhavan; Edoardo Conti; Joel Lehman; Kenneth O. Stanley; Jeff Clune (CoRR, 2017)

How evolution learns to generalise: Using the principles of learning theory to understand the evolution of developmental organisation. - Kostas Kouvaris; Jeff Clune; Loizos Kounios; Markus Brede; Richard A. Watson (PLoS Comput. Biol., 2017)

Safe mutations for deep and recurrent neural networks through output gradients. - Joel Lehman; Jay Chen; Jeff Clune; Kenneth O. Stanley (GECCO, 2018)

ES is more than just a traditional finite-difference approximator. - Joel Lehman; Jay Chen; Jeff Clune; Kenneth O. Stanley (GECCO, 2018)

VINE: an open source interactive data visualization tool for neuroevolution. - Rui Wang 052; Jeff Clune; Kenneth O. Stanley (GECCO (Companion), 2018)

Differentiable plasticity: training plastic neural networks with backpropagation. - Thomas Miconi; Kenneth O. Stanley; Jeff Clune (ICML, 2018)

The Surprising Creativity of Digital Evolution. - Joel Lehman; Jeff Clune; Dusan Misevic (ALIFE, 2018)

Improving Exploration in Evolution Strategies for Deep Reinforcement Learning via a Population of Novelty-Seeking Agents. - Edoardo Conti; Vashisht Madhavan; Felipe Petroski Such; Joel Lehman; Kenneth O. Stanley; Jeff Clune (NeurIPS, 2018)

The Emergence of Canalization and Evolvability in an Open-Ended, Interactive Evolutionary System. - Joost Huizinga; Kenneth O. Stanley; Jeff Clune (Artif. Life, 2018)

Deep Curiosity Search: Intra-Life Exploration Improves Performance on Challenging Deep Reinforcement Learning Problems. - Christopher Stanton; Jeff Clune (CoRR, 2018)

Evolving Multimodal Robot Behavior via Many Stepping Stones with the Combinatorial Multi-Objective Evolutionary Algorithm. - Joost Huizinga; Jeff Clune (CoRR, 2018)

An Atari Model Zoo for Analyzing, Visualizing, and Comparing Deep Reinforcement Learning Agents. - Felipe Petroski Such; Vashisht Madhavan; Rosanne Liu; Rui Wang 052; Pablo Samuel Castro; Yulun Li; Ludwig Schubert; Marc G. Bellemare; Jeff Clune; Joel Lehman (CoRR, 2018)

Automatically identifying, counting, and describing wild animals in camera-trap images with deep learning. - Mohammad Sadegh Norouzzadeh; Anh Nguyen 002; Margaret Kosmala; Alexandra Swanson; Meredith S. Palmer; Craig Packer; Jeff Clune (Proc. Natl. Acad. Sci. USA, 2018)

Evolvability ES: scalable and direct optimization of evolvability. - Alexander Gajewski; Jeff Clune; Kenneth O. Stanley; Joel Lehman (GECCO, 2019)

POET: open-ended coevolution of environments and their optimized solutions. - Rui Wang 052; Joel Lehman; Jeff Clune; Kenneth O. Stanley (GECCO, 2019)

Backpropamine: training self-modifying neural networks with differentiable neuromodulated plasticity. - Thomas Miconi; Aditya Rawal; Jeff Clune; Kenneth O. Stanley (ICLR (Poster), 2019)

Robustness to Out-of-Distribution Inputs via Task-Aware Generative Uncertainty. - Rowan McAllister; Gregory Kahn; Jeff Clune; Sergey Levine (ICRA, 2019)

An Atari Model Zoo for Analyzing, Visualizing, and Comparing Deep Reinforcement Learning Agents. - Felipe Petroski Such; Vashisht Madhavan; Rosanne Liu; Rui Wang 052; Pablo Samuel Castro; Yulun Li; Jiale Zhi; Ludwig Schubert; Marc G. Bellemare; Jeff Clune; Joel Lehman (IJCAI, 2019)

Commonsense and Semantic-Guided Navigation through Language in Embodied Environment. - Dian Yu 002; Chandra Khatri; Alexandros Papangelis; Andrea Madotto; Mahdi Namazifar; Joost Huizinga; Adrien Ecoffet; Huaixiu Zheng; Piero Molino; Jeff Clune; Zhou Yu 005; Kenji Sagae; et al. (ViGIL@NeurIPS, 2019)

Paired Open-Ended Trailblazer (POET): Endlessly Generating Increasingly Complex and Diverse Learning Environments and Their Solutions. - Rui Wang 052; Joel Lehman; Jeff Clune; Kenneth O. Stanley (CoRR, 2019)

Go-Explore: a New Approach for Hard-Exploration Problems. - Adrien Ecoffet; Joost Huizinga; Joel Lehman; Kenneth O. Stanley; Jeff Clune (CoRR, 2019)

Understanding Neural Networks via Feature Visualization: A survey. - Anh Nguyen 002; Jason Yosinski; Jeff Clune (CoRR, 2019)

AI-GAs: AI-generating algorithms, an alternate paradigm for producing general artificial intelligence. - Jeff Clune (CoRR, 2019)

A deep active learning system for species identification and counting in camera trap images. - Mohammad Sadegh Norouzzadeh; Dan Morris 001; Sara Beery; Neel Joshi; Nebojsa Jojic; Jeff Clune (CoRR, 2019)

Designing neural networks through neuroevolution. - Kenneth O. Stanley; Jeff Clune; Joel Lehman; Risto Miikkulainen (Nat. Mach. Intell., 2019)

Understanding Neural Networks via Feature Visualization: A Survey. - Anh Nguyen 002; Jason Yosinski; Jeff Clune (Explainable AI, 2019)

Learning to Continually Learn. - Shawn Beaulieu; Lapo Frati; Thomas Miconi; Joel Lehman; Kenneth O. Stanley; Jeff Clune; Nick Cheney (ECAI, 2020)

Scaling MAP-Elites to deep neuroevolution. - Cédric Colas; Vashisht Madhavan; Joost Huizinga; Jeff Clune (GECCO, 2020)

Enhanced POET: Open-ended Reinforcement Learning through Unbounded Invention of Learning Challenges and their Solutions. - Rui Wang 052; Joel Lehman; Aditya Rawal; Jiale Zhi; Yulun Li; Jeffrey Clune; Kenneth O. Stanley (ICML, 2020)

Generative Teaching Networks: Accelerating Neural Architecture Search by Learning to Generate Synthetic Training Data. - Felipe Petroski Such; Aditya Rawal; Joel Lehman; Kenneth O. Stanley; Jeffrey Clune (ICML, 2020)

Open Questions in Creating Safe Open-ended AI: Tensions Between Control and Creativity. - Adrien Ecoffet; Jeff Clune; Joel Lehman (ALIFE, 2020)

The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities. - Joel Lehman; Jeff Clune; Dusan Misevic; Christoph Adami; Lee Altenberg; Julie Beaulieu; Peter J. Bentley; Samuel Bernard; Guillaume Beslon; David M. Bryson; Nick Cheney; Patryk Chrabaszcz; et al. (Artif. Life, 2020)

Fiber: A Platform for Efficient Development and Distributed Training for Reinforcement Learning and Population-Based Methods. - Jiale Zhi; Rui Wang 052; Jeff Clune; Kenneth O. Stanley (CoRR, 2020)

Synthetic Petri Dish: A Novel Surrogate Model for Rapid Architecture Search. - Aditya Rawal; Joel Lehman; Felipe Petroski Such; Jeff Clune; Kenneth O. Stanley (CoRR, 2020)

Multi-task curriculum learning in a complex, visual, hard-exploration domain: Minecraft. - Ingmar Kanitscheider; Joost Huizinga; David Farhi; William Hebgen Guss; Brandon Houghton; Raul Sampedro; Peter Zhokhov; Bowen Baker; Adrien Ecoffet; Jie Tang; Oleg Klimov; Jeff Clune (CoRR, 2021)

Continual learning under domain transfer with sparse synaptic bursting. - Shawn L. Beaulieu; Jeff Clune; Nick Cheney (CoRR, 2021)

First return, then explore. - Adrien Ecoffet; Joost Huizinga; Joel Lehman; Kenneth O. Stanley; Jeff Clune (Nat., 2021)

Video PreTraining (VPT): Learning to Act by Watching Unlabeled Online Videos. - Bowen Baker; Ilge Akkaya; Peter Zhokhov; Joost Huizinga; Jie Tang; Adrien Ecoffet; Brandon Houghton; Raul Sampedro; Jeff Clune (NeurIPS, 2022)

Evolving Multimodal Robot Behavior via Many Stepping Stones with the Combinatorial Multiobjective Evolutionary Algorithm. - Joost Huizinga; Jeff Clune (Evol. Comput., 2022)

Biological underpinnings for lifelong learning machines. - Dhireesha Kudithipudi; Mario Aguilar-Simon; Jonathan Babb; Maxim Bazhenov; Douglas Blackiston; Josh C. Bongard; Andrew P. Brna; Suraj Chakravarthi Raja; Nick Cheney; Jeff Clune; Anurag Reddy Daram; Stefano Fusi; et al. (Nat. Mach. Intell., 2022)

Thought Cloning: Learning to Think while Acting by Imitating Human Thinking. - Shengran Hu; Jeff Clune (NeurIPS, 2023)

First-Explore, then Exploit: Meta-Learning Intelligent Exploration. - Ben Norman; Jeff Clune (CoRR, 2023)

Quality Diversity through Human Feedback. - Li Ding 010; Jenny Zhang; Jeff Clune; Lee Spector; Joel Lehman (CoRR, 2023)

Managing AI Risks in an Era of Rapid Progress. - Yoshua Bengio; Geoffrey E. Hinton; Andrew Yao; Dawn Song; Pieter Abbeel; Yuval Noah Harari; Ya-Qin Zhang; Lan Xue; Shai Shalev-Shwartz; Gillian K. Hadfield; Jeff Clune; Tegan Maharaj; et al. (CoRR, 2023)

Reset It and Forget It: Relearning Last-Layer Weights Improves Continual and Transfer Learning. - Lapo Frati; Neil Traft; Jeff Clune; Nick Cheney (ECAI, 2024)

Quality-Diversity through AI Feedback. - Herbie Bradley; Andrew Dai 001; Hannah Benita Teufel; Jenny Zhang; Koen Oostermeijer; Marco Bellagente; Jeff Clune; Kenneth O. Stanley; Grégory Schott; Joel Lehman (ICLR, 2024)

OMNI: Open-endedness via Models of human Notions of Interestingness. - Jenny Zhang; Joel Lehman; Kenneth O. Stanley; Jeff Clune (ICLR, 2024)

Quality Diversity through Human Feedback: Towards Open-Ended Diversity-Driven Optimization. - Li Ding 010; Jenny Zhang; Jeff Clune; Lee Spector; Joel Lehman (ICML, 2024)

Genie: Generative Interactive Environments. - Jake Bruce; Michael D. Dennis; Ashley Edwards; Jack Parker-Holder; Yuge Shi; Edward Hughes 001; Matthew Lai; Aditi Mavalankar; Richie Steigerwald; Chris Apps; Yusuf Aytar; Sarah Bechtle; et al. (ICML, 2024)

First-Explore, then Exploit: Meta-Learning to Solve Hard Exploration-Exploitation Trade-Offs. - Ben Norman; Jeff Clune (NeurIPS, 2024)

Scaling Instructable Agents Across Many Simulated Worlds. - SIMA Team; Maria Abi Raad; Arun Ahuja; Catarina Barros; Frederic Besse; Andrew Bolt; Adrian Bolton; Bethanie Brownfield; Gavin Buttimore; Max Cant; Sarah Chakera; Stephanie C. Y. Chan; et al. (CoRR, 2024)

The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery. - Chris Lu 001; Cong Lu; Robert Tjarko Lange; Jakob N. Foerster; Jeff Clune; David Ha (CoRR, 2024)

OMNI-EPIC: Open-endedness via Models of human Notions of Interestingness with Environments Programmed in Code. - Maxence Faldor; Jenny Zhang; Antoine Cully; Jeff Clune (ICLR, 2025)

Automated Design of Agentic Systems. - Shengran Hu; Cong Lu; Jeff Clune (ICLR, 2025)

Intelligent Go-Explore: Standing on the Shoulders of Giant Foundation Models. - Cong Lu; Shengran Hu; Jeff Clune (ICLR, 2025)

Automated Capability Discovery via Model Self-Exploration. - Cong Lu; Shengran Hu; Jeff Clune (CoRR, 2025)

The AI Scientist-v2: Workshop-Level Automated Scientific Discovery via Agentic Tree Search. - Yutaro Yamada; Robert Tjarko Lange; Cong Lu; Shengran Hu; Chris Lu 001; Jakob N. Foerster; Jeff Clune; David Ha (CoRR, 2025)

Questioning Representational Optimism in Deep Learning: The Fractured Entangled Representation Hypothesis. - Akarsh Kumar; Jeff Clune; Joel Lehman; Kenneth O. Stanley (CoRR, 2025)

Darwin Godel Machine: Open-Ended Evolution of Self-Improving Agents. - Jenny Zhang; Shengran Hu; Cong Lu; Robert T. Lange; Jeff Clune (CoRR, 2025)

The Singapore Consensus on Global AI Safety Research Priorities. - Yoshua Bengio; Tegan Maharaj; Luke Ong; Stuart Russell 001; Dawn Song; Max Tegmark; Lan Xue; Ya-Qin Zhang; Stephen Casper; Wan Sie Lee; Sören Mindermann; Vanessa Wilfred; et al. (CoRR, 2025)

How Weight Resampling and Optimizers Shape the Dynamics of Continual Learning and Forgetting in Neural Networks. - Lapo Frati; Neil Traft; Jeff Clune; Nick Cheney (CoRR, 2025)

Foundation Model Self-Play: Open-Ended Strategy Innovation via Foundation Models. - Aaron Dharna; Cong Lu; Jeff Clune (CoRR, 2025)