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Jakob Foerster

54 papers · 2016–2025 · 9 conferences · across top CS/AI conferences

Achievements

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+17 more ↓ πŸ—ΊοΈ Taxonomy Completionist (24) 🧭 Keyword Pioneer 🌈 Renaissance Researcher (6) πŸŒ‰ Interdisciplinary Bridge 🐣 Hot Topic Early Bird
🌍 Conference Polyglot (9) 🐣 Hot Topic Early Bird πŸ—ΊοΈ Taxonomy Completionist (24) 🌟 Keyword Trendsetter Combo (3) 🏠 Conference Loyalist (26) πŸ† Grand Slam πŸ‘₯ Mega-Team (21) πŸ‘‘ Triple Crown πŸ”¬ Deep Specialist (19) πŸ† Keyword Champion (3) 🧬 Topic Evolution 🀝 Dynamic Duo (17) ⚑ Prolific Year (9) πŸ’Ž Century Club (54) πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (87) πŸ”₯ Unstoppable (10)

Conferences

NIPS (26) ICML (16) AAAI (2) ACL (2) ICLR (2) IJCAI (2) JMLR (2) EMNLP (1) UAI (1)

Papers

Combining Code Generating Large Language Models and Self-Play to Iteratively Refine Strategies in Games IJCAI 2025 Computing Low-Entropy Couplings for Large-Support Distributions UAI 2024 Artificial Generational Intelligence: Cultural Accumulation in Reinforcement Learning NIPS 2024 Rainbow Teaming: Open-Ended Generation of Diverse Adversarial Prompts NIPS 2024 Discovering Preference Optimization Algorithms with and for Large Language Models NIPS 2024 HelloFresh: LLM Evalutions on Streams of Real-World Human Editorial Actions across X Community Notes and Wikipedia edits ACL 2024 Recurrent Reinforcement Learning with Memoroids NIPS 2024 No Regrets: Investigating and Improving Regret Approximations for Curriculum Discovery NIPS 2024 JaxMARL: Multi-Agent RL Environments and Algorithms in JAX NIPS 2024 BAM! Just Like That: Simple and Efficient Parameter Upcycling for Mixture of Experts NIPS 2024 SMACv2: An Improved Benchmark for Cooperative Multi-Agent Reinforcement Learning NIPS 2023 Structured State Space Models for In-Context Reinforcement Learning NIPS 2023 Discovering General Reinforcement Learning Algorithms with Adversarial Environment Design NIPS 2023 Similarity-based cooperative equilibrium NIPS 2023 Generalized Beliefs for Cooperative AI ICML 2022 Mirror Learning: A Unifying Framework of Policy Optimisation ICML 2022 COLA: Consistent Learning with Opponent-Learning Awareness ICML 2022 Communicating via Markov Decision Processes ICML 2022 Nocturne: a scalable driving benchmark for bringing multi-agent learning one step closer to the real world NIPS 2022 Equivariant Networks for Zero-Shot Coordination NIPS 2022 Off-Team Learning NIPS 2022 Discovered Policy Optimisation NIPS 2022 Influencing Long-Term Behavior in Multiagent Reinforcement Learning NIPS 2022 Proximal Learning With Opponent-Learning Awareness NIPS 2022 Grounding Aleatoric Uncertainty for Unsupervised Environment Design NIPS 2022 Self-Explaining Deviations for Coordination NIPS 2022 Evolving Curricula with Regret-Based Environment Design ICML 2022 Model-Free Opponent Shaping ICML 2022 K-level Reasoning for Zero-Shot Coordination in Hanabi NIPS 2021 Replay-Guided Adversarial Environment Design NIPS 2021 Neural Pseudo-Label Optimism for the Bank Loan Problem NIPS 2021 Off-Belief Learning ICML 2021 Trajectory Diversity for Zero-Shot Coordination ICML 2021 A New Formalism, Method and Open Issues for Zero-Shot Coordination ICML 2021 Ridge Rider: Finding Diverse Solutions by Following Eigenvectors of the Hessian NIPS 2020 β€œOther-Play” for Zero-Shot Coordination ICML 2020 Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning JMLR 2020 Compositionality and Capacity in Emergent Languages ACL 2020 Improving Policies via Search in Cooperative Partially Observable Games AAAI 2020 Exploratory Combinatorial Optimization with Reinforcement Learning AAAI 2020 On the interaction between supervision and self-play in emergent communication ICLR 2020 A Survey of Reinforcement Learning Informed by Natural Language IJCAI 2019 Loaded DiCE: Trading off Bias and Variance in Any-Order Score Function Gradient Estimators for Reinforcement Learning NIPS 2019 Multi-Agent Common Knowledge Reinforcement Learning NIPS 2019 Stable Opponent Shaping in Differentiable Games ICLR 2019 Bayesian Action Decoder for Deep Multi-Agent Reinforcement Learning ICML 2019 A Baseline for Any Order Gradient Estimation in Stochastic Computation Graphs ICML 2019 Seeded self-play for language learning EMNLP 2019 Differentiable Game Mechanics JMLR 2019 The Mechanics of n-Player Differentiable Games ICML 2018 DiCE: The Infinitely Differentiable Monte Carlo Estimator ICML 2018 QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning ICML 2018 Stabilising Experience Replay for Deep Multi-Agent Reinforcement Learning ICML 2017 Learning to Communicate with Deep Multi-Agent Reinforcement Learning NIPS 2016