Evolution and The Knightian Blindspot of Machine Learning. - Lehman, Joel; Meyerson, Elliot; El-Gaaly, Tarek; Stanley, Kenneth O.; Ziyaee, Tarin (CoRR, 2025)

Multi-Agent Risks from Advanced AI. - Hammond, Lewis; Chan, Alan; Clifton, Jesse; Hoelscher-Obermaier, Jason; Khan, Akbir; McLean, Euan; Smith, Chandler; Barfuss, Wolfram; Foerster, Jakob N.; Gavenciak, Tomas; Han, The Anh; Hughes, Edward; et al. (CoRR, 2025)

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

Language Model Crossover: Variation through Few-Shot Prompting. - Meyerson, Elliot; Nelson, Mark J.; Bradley, Herbie; Gaier, Adam; Karkaj, Arash Moradi; Hoover, Amy K.; Lehman, Joel (ACM Trans. Evol. Learn. Optim., 2024)

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

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

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

The Ethics of Advanced AI Assistants. - Gabriel, Iason; Manzini, Arianna; Keeling, Geoff; Hendricks, Lisa Anne; Rieser, Verena; Iqbal, Hasan; Tomasev, Nenad; Ktena, Ira; Kenton, Zachary; Rodriguez, Mikel; El-Sayed, Seliem; Brown, Sasha; et al. (CoRR, 2024)

Simulating Tabular Datasets through LLMs to Rapidly Explore Hypotheses about Real-World Entities. - Zabaleta, Miguel; Lehman, Joel (CoRR, 2024)

The OpenELM Library: Leveraging Progress in Language Models for Novel Evolutionary Algorithms. - Bradley, Herbie; Fan, Honglu; Galanos, Theodoros; Zhou, Ryan; Scott, Daniel; Lehman, Joel (2023)

Machine Love. - Lehman, Joel (CoRR, 2023)

Language Model Crossover: Variation through Few-Shot Prompting. - Meyerson, Elliot; Nelson, Mark J.; Bradley, Herbie; Gaier, Adam; Karkaj, Arash Moradi; Hoover, Amy K.; Lehman, Joel (CoRR, 2023)

OMNI: Open-endedness via Models of human Notions of Interestingness. - Zhang, Jenny; Lehman, Joel; Stanley, Kenneth O.; Clune, Jeff (CoRR, 2023)

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

Quality-Diversity through AI Feedback. - Bradley, Herbie; Dai, Andrew; Teufel, Hannah; Zhang, Jenny; Oostermeijer, Koen; Bellagente, Marco; Clune, Jeff; Stanley, Kenneth O.; Schott, Grégory; Lehman, Joel (CoRR, 2023)

Evolution through Large Models. - Lehman, Joel; Gordon, Jonathan; Jain, Shawn; Ndousse, Kamal; Yeh, Cathy; Stanley, Kenneth O. (CoRR, 2022)

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

Reinforcement Learning Under Moral Uncertainty. - Ecoffet, Adrien; Lehman, Joel (2021)

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

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

Antimander: open source detection of gerrymandering though multi-objective evolutionary algorithms. - Simon, Joel; Lehman, Joel (2020)

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

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

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

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

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

First return then explore. - Ecoffet, Adrien; Huizinga, Joost; Lehman, Joel; Stanley, Kenneth O.; Clune, Jeff (CoRR, 2020)

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

Reinforcement Learning Under Moral Uncertainty. - Ecoffet, Adrien; Lehman, Joel (CoRR, 2020)

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

Ideas for Improving the Field of Machine Learning: Summarizing Discussion from the NeurIPS 2019 Retrospectives Workshop. - Sodhani, Shagun; Jaiswal, Mayoore S.; Baker, Lauren; Sinha, Koustuv; Shneider, Carl; Henderson, Peter; Lehman, Joel; Lowe, Ryan (CoRR, 2020)

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

Tradeoffs in Neuroevolutionary Learning-Based Real-Time Robotic Task Design in the Imprecise Computation Framework. - Huang, Pei-Chi; Sentis, Luis; Lehman, Joel; Fok, Chien-Liang; Mok, Aloysius K.; Miikkulainen, Risto (ACM Trans. Cyber Phys. Syst., 2019)

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

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

Evolutionary Computation and AI Safety - Research Problems Impeding Routine and Safe Real-World Application of Evolution. - Lehman, Joel (2019)

Towards Empathic Deep Q-Learning. - Bussmann, Bart; Heinerman, Jacqueline; Lehman, Joel (2019)

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

Learning Belief Representations for Imitation Learning in POMDPs. - Gangwani, Tanmay; Lehman, Joel; Liu, Qiang; Peng, Jian (2019)

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

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

Learning Belief Representations for Imitation Learning in POMDPs. - Gangwani, Tanmay; Lehman, Joel; Liu, Qiang; Peng, Jian (CoRR, 2019)

Evolutionary Computation and AI Safety: Research Problems Impeding Routine and Safe Real-world Application of Evolution. - Lehman, Joel (CoRR, 2019)

Towards Empathic Deep Q-Learning. - Bussmann, Bart; Heinerman, Jacqueline; Lehman, Joel (CoRR, 2019)

Evolvability ES: Scalable and Direct Optimization of Evolvability. - Gajewski, Alexander; Clune, Jeff; Stanley, Kenneth O.; Lehman, Joel (CoRR, 2019)

Generative Teaching Networks: Accelerating Neural Architecture Search by Learning to Generate Synthetic Training Data. - Such, Felipe Petroski; Rawal, Aditya; Lehman, Joel; Stanley, Kenneth O.; Clune, Jeff (CoRR, 2019)

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

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

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

On the Potential Benefits of Knowing Everything. - Lehman, Joel; Stanley, Kenneth O. (2018)

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

An intriguing failing of convolutional neural networks and the CoordConv solution. - Liu, Rosanne; Lehman, Joel; Molino, Piero; Such, Felipe Petroski; Frank, Eric; Sergeev, Alex; Yosinski, Jason (2018)

The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities. - Lehman, Joel; Clune, Jeff; Misevic, Dusan; Adami, Christoph; Altenberg, Lee; Beaulieu, Julie; Bentley, Peter J.; Bernard, Samuel; Beslon, Guillaume; Bryson, David M.; Chrabaszcz, Patryk; Cheney, Nick; et al. (CoRR, 2018)

An Intriguing Failing of Convolutional Neural Networks and the CoordConv Solution. - Liu, Rosanne; Lehman, Joel; Molino, Piero; Such, Felipe Petroski; Frank, Eric; Sergeev, Alex; Yosinski, Jason (CoRR, 2018)

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

Precomputation for rapid hypothesis generation in evolutionary robotics. - Lehman, Joel (2017)

Analyzing deception, evolvability, and behavioral rarity in evolutionary robotics. - Lehman, Joel (2017)

Improving Exploration in Evolution Strategies for Deep Reinforcement Learning via a Population of Novelty-Seeking Agents. - Conti, Edoardo; Madhavan, Vashisht; Such, Felipe Petroski; Lehman, Joel; Stanley, Kenneth O.; Clune, Jeff (CoRR, 2017)

Safe Mutations for Deep and Recurrent Neural Networks through Output Gradients. - Lehman, Joel; Chen, Jay; Clune, Jeff; Stanley, Kenneth O. (CoRR, 2017)

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

ES Is More Than Just a Traditional Finite-Difference Approximator. - Lehman, Joel; Chen, Jay; Clune, Jeff; Stanley, Kenneth O. (CoRR, 2017)

On the Critical Role of Divergent Selection in Evolvability. - Lehman, Joel; Wilder, Bryan; Stanley, Kenneth O. (Frontiers Robotics AI, 2016)

Petalz: Search-Based Procedural Content Generation for the Casual Gamer. - Risi, Sebastian; Lehman, Joel; D'Ambrosio, David B.; Hall, Ryan; Stanley, Kenneth O. (IEEE Trans. Comput. Intell. AI Games, 2016)

Orthogonally Evolved AI to Improve Difficulty Adjustment in Video Games. - Hintze, Arend; Olson, Randal S.; Lehman, Joel (2016)

Automatic Evolution of Multimodal Behavior with Multi-Brain HyperNEAT. - Schrum, Jacob; Lehman, Joel; Risi, Sebastian (2016)

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

Learning Behavior Characterizations for Novelty Search. - Meyerson, Elliot; Lehman, Joel; Miikkulainen, Risto (2016)

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

Using Indirect Encoding of Multiple Brains to Produce Multimodal Behavior. - Schrum, Jacob; Lehman, Joel; Risi, Sebastian (CoRR, 2016)

Why Greatness Cannot Be Planned - The Myth of the Objective - Stanley, Kenneth O.; Lehman, Joel (Springer, 2015)

Investigating Biological Assumptions through Radical Reimplementation. - Lehman, Joel; Stanley, Kenneth O. (Artif. Life, 2015)

Patricia Vargas, Ezequiel Di Paolo, Inman Harvey, and Phil Husbands (eds), The Horizons of Evolutionary Robotics, The MIT Press, 2014, ISBN: 978-0-262-02676-5, Hardcover book, 302 pages. - Lehman, Joel (Genet. Program. Evolvable Mach., 2015)

Novelty-Driven Particle Swarm Optimization. - Galvao, Diana F.; Lehman, Joel; Urbano, Paulo (2015)

Enhancing Divergent Search through Extinction Events. - Lehman, Joel; Miikkulainen, Risto (2015)

Tradeoffs in Real-Time Robotic Task Design with Neuroevolution Learning for Imprecise Computation. - Huang, Pei-Chi; Sentis, Luis; Lehman, Joel; Fok, Chien-Liang; Mok, Aloysius K.; Miikkulainen, Risto (2015)

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

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

A Neuroevolution Approach to General Atari Game Playing. - Hausknecht, Matthew J.; Lehman, Joel; Miikkulainen, Risto; Stone, Peter (IEEE Trans. Comput. Intell. AI Games, 2014)

Grasping novel objects with a dexterous robotic hand through neuroevolution. - Huang, Pei-Chi; Lehman, Joel; Mok, Aloysius K.; Miikkulainen, Risto; Sentis, Luis (2014)

Overcoming deception in evolution of cognitive behaviors. - Lehman, Joel; Miikkulainen, Risto (2014)

Encouraging reactivity to create robust machines. - Lehman, Joel; Risi, Sebastian; D'Ambrosio, David B.; Stanley, Kenneth O. (Adapt. Behav., 2013)

Neuroevolution. - Lehman, Joel; Miikkulainen, Risto (Scholarpedia, 2013)

Exploring Biological Intelligence through Artificial Intelligence and Radical Reimplementation. - Lehman, Joel; Stanley, Kenneth O. (2013)

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

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

Effective diversity maintenance in deceptive domains. - Lehman, Joel; Stanley, Kenneth O.; Miikkulainen, Risto (2013)

Boosting Interactive Evolution Using Human Computation Markets. - Lehman, Joel; Miikkulainen, Risto (2013)

Evolvability Is Inevitable: Increasing Evolvability Without the Pressure to Adapt - Lehman, Joel; Stanley, Kenneth O. (CoRR, 2013)

Combining Search-Based Procedural Content Generation and Social Gaming in the Petalz Video Game. - Risi, Sebastian; Lehman, Joel; D'Ambrosio, David B.; Hall, Ryan; Stanley, Kenneth O. (2012)

Rewarding Reactivity to Evolve Robust Controllers without Multiple Trials or Noise. - Lehman, Joel; Risi, Sebastian; D'Ambrosio, David B.; Stanley, Kenneth O. (2012)

Beyond Open-endedness: Quantifying Impressiveness. - Lehman, Joel; Stanley, Kenneth O. (2012)

Multirobot Behavior Synchronization through Direct Neural Network Communication. - D'Ambrosio, David B.; Goodell, Skyler; Lehman, Joel; Risi, Sebastian; Stanley, Kenneth O. (2012)

Abandoning Objectives: Evolution Through the Search for Novelty Alone. - Lehman, Joel; Stanley, Kenneth O. (Evol. Comput., 2011)

Improving evolvability through novelty search and self-adaptation. - Lehman, Joel; Stanley, Kenneth O. (2011)

Evolving a diversity of virtual creatures through novelty search and local competition. - Lehman, Joel; Stanley, Kenneth O. (2011)

Task switching in multirobot learning through indirect encoding. - D'Ambrosio, David B.; Lehman, Joel; Risi, Sebastian; Stanley, Kenneth O. (2011)

Evolving policy geometry for scalable multiagent learning. - D'Ambrosio, David B.; Lehman, Joel; Risi, Sebastian; Stanley, Kenneth O. (2010)

Revising the evolutionary computation abstraction: minimal criteria novelty search. - Lehman, Joel; Stanley, Kenneth O. (2010)

Evolving the placement and density of neurons in the hyperneat substrate. - Risi, Sebastian; Lehman, Joel; Stanley, Kenneth O. (2010)

Efficiently evolving programs through the search for novelty. - Lehman, Joel; Stanley, Kenneth O. (2010)

Exploiting Open-Endedness to Solve Problems Through the Search for Novelty. - Lehman, Joel; Stanley, Kenneth O. (2008)