Action Grammars: A Cognitive Model for Learning Temporal Abstractions. - Robert Tjarko Lange; Aldo Faisal (CoRR, 2019)

Reinforcement Learning with Structured Hierarchical Grammar Representations of Actions. - Petros Christodoulou; Robert Tjarko Lange; Ali Shafti; A. Aldo Faisal (CoRR, 2019)

Neural surprise in somatosensory Bayesian learning. - Sam Gijsen; Miro Grundei; Robert T. Lange; Dirk Ostwald; Felix Blankenburg (PLoS Comput. Biol., 2021)

Learning Not to Learn: Nature versus Nurture In Silico. - Robert Tjarko Lange; Henning Sprekeler (AAAI, 2022)

On Lottery Tickets and Minimal Task Representations in Deep Reinforcement Learning. - Marc Aurel Vischer; Robert Tjarko Lange; Henning Sprekeler (ICLR, 2022)

evosax: JAX-Based Evolution Strategies. - Robert Tjarko Lange (GECCO Companion, 2023)

Discovering Attention-Based Genetic Algorithms via Meta-Black-Box Optimization. - Robert Tjarko Lange; Tom Schaul; Yutian Chen 001; Chris Lu 001; Tom Zahavy; Valentin Dalibard; Sebastian Flennerhag (GECCO, 2023)

Discovering Evolution Strategies via Meta-Black-Box Optimization. - Robert Tjarko Lange; Tom Schaul; Yutian Chen 001; Tom Zahavy; Valentin Dalibard; Chris Lu 001; Satinder Singh 001; Sebastian Flennerhag (GECCO Companion, 2023)

Lottery Tickets in Evolutionary Optimization: On Sparse Backpropagation-Free Trainability. - Robert Tjarko Lange; Henning Sprekeler (ICML, 2023)

NeuroEvoBench: Benchmarking Evolutionary Optimizers for Deep Learning Applications. - Robert Tjarko Lange; Yujin Tang; Yingtao Tian (NeurIPS, 2023)

JaxMARL: Multi-Agent RL Environments in JAX. - Alexander Rutherford; Benjamin Ellis; Matteo Gallici; Jonathan Cook 004; Andrei Lupu; Garðar Ingvarsson; Timon Willi; Akbir Khan; Christian Schröder de Witt; Alexandra Souly; Saptarashmi Bandyopadhyay; Mikayel Samvelyan; et al. (CoRR, 2023)

JaxMARL: Multi-Agent RL Environments and Algorithms in JAX. - Alexander Rutherford; Benjamin Ellis; Matteo Gallici; Jonathan Cook 004; Andrei Lupu; Garðar Ingvarsson; Timon Willi; Akbir Khan; Christian Schröder de Witt; Alexandra Souly; Saptarashmi Bandyopadhyay; Mikayel Samvelyan; et al. (AAMAS, 2024)

Evolution Transformer: In-Context Evolutionary Optimization. - Robert T. Lange; Yingtao Tian; Yujin Tang (GECCO Companion, 2024)

Large Language Models As Evolution Strategies. - Robert T. Lange; Yingtao Tian; Yujin Tang (GECCO Companion, 2024)

Discovering Temporally-Aware Reinforcement Learning Algorithms. - Matthew Thomas Jackson; Chris Lu 001; Louis Kirsch; Robert Tjarko Lange; Shimon Whiteson; Jakob Nicolaus Foerster (ICLR, 2024)

Behaviour Distillation. - Andrei Lupu; Chris Lu 001; Jarek Liesen; Robert Tjarko Lange; Jakob Nicolaus Foerster (ICLR, 2024)

Position: Leverage Foundational Models for Black-Box Optimization. - Xingyou Song; Yingtao Tian; Robert Tjarko Lange; Chansoo Lee; Yujin Tang; Yutian Chen 001 (ICML, 2024)

Discovering Preference Optimization Algorithms with and for Large Language Models. - Chris Lu 001; Samuel Holt; Claudio Fanconi; Alex J. Chan; Jakob N. Foerster; Mihaela van der Schaar; Robert T. Lange (NeurIPS, 2024)

JaxMARL: Multi-Agent RL Environments and Algorithms in JAX. - Alexander Rutherford; Benjamin Ellis; Matteo Gallici; Jonathan Cook 004; Andrei Lupu; Garðar Ingvarsson; Timon Willi; Ravi Hammond; Akbir Khan; Christian Schröder de Witt; Alexandra Souly; Saptarashmi Bandyopadhyay; et al. (NeurIPS, 2024)

Discovering Minimal Reinforcement Learning Environments. - Jarek Liesen; Chris Lu 001; Andrei Lupu; Jakob N. Foerster; Henning Sprekeler; Robert T. Lange (CoRR, 2024)

NAVIX: Scaling MiniGrid Environments with JAX. - Eduardo Pignatelli; Jarek Liesen; Robert Tjarko Lange; Chris Lu 001; Pablo Samuel Castro; Laura Toni (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)

Competition and Attraction Improve Model Fusion. - João Abrantes; Robert T. Lange; Yujin Tang (GECCO, 2025)

Stein Variational Evolution Strategies. - Cornelius V. Braun; Robert Tjarko Lange; Marc Toussaint (UAI, 2025)

Discovering Quality-Diversity Algorithms via Meta-Black-Box Optimization. - Maxence Faldor; Robert Tjarko Lange; Antoine Cully (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)

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

Text-to-LoRA: Instant Transformer Adaption. - Rujikorn Charakorn; Edoardo Cetin; Yujin Tang; Robert Tjarko Lange (CoRR, 2025)