Jakob N. Foerster

Orcid: 0000-0001-9688-2498

Affiliations:
  • University of Oxford, UK


According to our database1, Jakob N. Foerster authored at least 105 papers between 2016 and 2024.

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Bibliography

2024
JaxUED: A simple and useable UED library in Jax.
CoRR, 2024

Rainbow Teaming: Open-Ended Generation of Diverse Adversarial Prompts.
CoRR, 2024

Craftax: A Lightning-Fast Benchmark for Open-Ended Reinforcement Learning.
CoRR, 2024

Refining Minimax Regret for Unsupervised Environment Design.
CoRR, 2024

Revisiting Recurrent Reinforcement Learning with Memory Monoids.
CoRR, 2024

Mixtures of Experts Unlock Parameter Scaling for Deep RL.
CoRR, 2024

Discovering Temporally-Aware Reinforcement Learning Algorithms.
CoRR, 2024

The Danger Of Arrogance: Welfare Equilibra As A Solution To Stackelberg Self-Play In Non-Coincidental Games.
CoRR, 2024


Rethinking Out-of-Distribution Detection for Reinforcement Learning: Advancing Methods for Evaluation and Detection.
Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024

Scaling Opponent Shaping to High Dimensional Games.
Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024

Analysing the Sample Complexity of Opponent Shaping.
Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024

2023
JaxMARL: Multi-Agent RL Environments in JAX.
CoRR, 2023

Unbiased Decisions Reduce Regret: Adversarial Domain Adaptation for the Bank Loan Problem.
CoRR, 2023

Learning to Communicate using Contrastive Learning.
CoRR, 2023

ReLU to the Rescue: Improve Your On-Policy Actor-Critic with Positive Advantages.
CoRR, 2023

Arbitrary Order Meta-Learning with Simple Population-Based Evolution.
CoRR, 2023

Similarity-based cooperative equilibrium.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Discovering General Reinforcement Learning Algorithms with Adversarial Environment Design.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

SMACv2: An Improved Benchmark for Cooperative Multi-Agent Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Structured State Space Models for In-Context Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learning Intuitive Policies Using Action Features.
Proceedings of the International Conference on Machine Learning, 2023

Adversarial Cheap Talk.
Proceedings of the International Conference on Machine Learning, 2023

Perfectly Secure Steganography Using Minimum Entropy Coupling.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

MAESTRO: Open-Ended Environment Design for Multi-Agent Reinforcement Learning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Cheap Talk Discovery and Utilization in Multi-Agent Reinforcement Learning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Adversarial Diversity in Hanabi.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Generative AI for End-to-End Limit Order Book Modelling: A Token-Level Autoregressive Generative Model of Message Flow Using a Deep State Space Network.
Proceedings of the 4th ACM International Conference on AI in Finance, 2023

JAX-LOB: A GPU-Accelerated limit order book simulator to unlock large scale reinforcement learning for trading.
Proceedings of the 4th ACM International Conference on AI in Finance, 2023

2022
SMACv2: An Improved Benchmark for Cooperative Multi-Agent Reinforcement Learning.
CoRR, 2022

Similarity-based Cooperation.
CoRR, 2022

Game-Theoretical Perspectives on Active Equilibria: A Preferred Solution Concept over Nash Equilibria.
CoRR, 2022

Learning to Optimize Quasi-Newton Methods.
CoRR, 2022

Human-AI Coordination via Human-Regularized Search and Learning.
CoRR, 2022

An Investigation of the Bias-Variance Tradeoff in Meta-Gradients.
CoRR, 2022

Illusionary Attacks on Sequential Decision Makers and Countermeasures.
CoRR, 2022

Learning to Coordinate with Humans using Action Features.
CoRR, 2022

Proximal Learning With Opponent-Learning Awareness.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Equivariant Networks for Zero-Shot Coordination.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Influencing Long-Term Behavior in Multiagent Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Grounding Aleatoric Uncertainty for Unsupervised Environment Design.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Self-Explaining Deviations for Coordination.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Off-Team Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Discovered Policy Optimisation.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

COLA: Consistent Learning with Opponent-Learning Awareness.
Proceedings of the International Conference on Machine Learning, 2022

Communicating via Markov Decision Processes.
Proceedings of the International Conference on Machine Learning, 2022

Evolving Curricula with Regret-Based Environment Design.
Proceedings of the International Conference on Machine Learning, 2022

Generalized Beliefs for Cooperative AI.
Proceedings of the International Conference on Machine Learning, 2022

Model-Free Opponent Shaping.
Proceedings of the International Conference on Machine Learning, 2022

Mirror Learning: A Unifying Framework of Policy Optimisation.
Proceedings of the International Conference on Machine Learning, 2022

A Fine-Tuning Approach to Belief State Modeling.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Lyapunov Exponents for Diversity in Differentiable Games.
Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022

Centralized Model and Exploration Policy for Multi-Agent RL.
Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022

2021
Reinforcement learning enhanced quantum-inspired algorithm for combinatorial optimization.
Mach. Learn. Sci. Technol., 2021

Don't Sweep your Learning Rate under the Rug: A Closer Look at Cross-modal Transfer of Pretrained Transformers.
CoRR, 2021

Implicit Communication as Minimum Entropy Coupling.
CoRR, 2021

Learned Belief Search: Efficiently Improving Policies in Partially Observable Settings.
CoRR, 2021

Quasi-Equivalence Discovery for Zero-Shot Emergent Communication.
CoRR, 2021

Off-Belief Learning.
CoRR, 2021

Neural Pseudo-Label Optimism for the Bank Loan Problem.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Replay-Guided Adversarial Environment Design.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

K-level Reasoning for Zero-Shot Coordination in Hanabi.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

A New Formalism, Method and Open Issues for Zero-Shot Coordination.
Proceedings of the 38th International Conference on Machine Learning, 2021

Trajectory Diversity for Zero-Shot Coordination.
Proceedings of the 38th International Conference on Machine Learning, 2021

Off-Belief Learning.
Proceedings of the 38th International Conference on Machine Learning, 2021

Trajectory Diversity for Zero-Shot Coordination.
Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021

2020
Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning.
J. Mach. Learn. Res., 2020

Exploring Zero-Shot Emergent Communication in Embodied Multi-Agent Populations.
CoRR, 2020

The Struggles of Feature-Based Explanations: Shapley Values vs. Minimal Sufficient Subsets.
CoRR, 2020

The Hanabi challenge: A new frontier for AI research.
Artif. Intell., 2020

Compositionality and Capacity in Emergent Languages.
Proceedings of the 5th Workshop on Representation Learning for NLP, 2020

Ridge Rider: Finding Diverse Solutions by Following Eigenvectors of the Hessian.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

"Other-Play" for Zero-Shot Coordination.
Proceedings of the 37th International Conference on Machine Learning, 2020

On the interaction between supervision and self-play in emergent communication.
Proceedings of the 8th International Conference on Learning Representations, 2020

Simplified Action Decoder for Deep Multi-Agent Reinforcement Learning.
Proceedings of the 8th International Conference on Learning Representations, 2020

Capacity, Bandwidth, and Compositionality in Emergent Language Learning.
Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

Improving Policies via Search in Cooperative Partially Observable Games.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Exploratory Combinatorial Optimization with Reinforcement Learning.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Differentiable Game Mechanics.
J. Mach. Learn. Res., 2019

Robust Domain Randomization for Reinforcement Learning.
CoRR, 2019

Can I Trust the Explainer? Verifying Post-hoc Explanatory Methods.
CoRR, 2019

Loaded DiCE: Trading off Bias and Variance in Any-Order Score Function Estimators for Reinforcement Learning.
CoRR, 2019

Multi-Agent Common Knowledge Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Loaded DiCE: Trading off Bias and Variance in Any-Order Score Function Gradient Estimators for Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

A Survey of Reinforcement Learning Informed by Natural Language.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

A Baseline for Any Order Gradient Estimation in Stochastic Computation Graphs.
Proceedings of the 36th International Conference on Machine Learning, 2019

Bayesian Action Decoder for Deep Multi-Agent Reinforcement Learning.
Proceedings of the 36th International Conference on Machine Learning, 2019

Stable Opponent Shaping in Differentiable Games.
Proceedings of the 7th International Conference on Learning Representations, 2019

Seeded self-play for language learning.
Proceedings of the Beyond Vision and LANguage: inTEgrating Real-world kNowledge, 2019

The StarCraft Multi-Agent Challenge.
Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

On the Pitfalls of Measuring Emergent Communication.
Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

2018
Deep multi-agent reinforcement learning.
PhD thesis, 2018

QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning.
Proceedings of the 35th International Conference on Machine Learning, 2018

The Mechanics of n-Player Differentiable Games.
Proceedings of the 35th International Conference on Machine Learning, 2018

DiCE: The Infinitely Differentiable Monte-Carlo Estimator.
Proceedings of the 6th International Conference on Learning Representations, 2018

Learning with Opponent-Learning Awareness.
Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, 2018

Pommerman: A Multi-Agent Playground.
Proceedings of the Joint Proceedings of the AIIDE 2018 Workshops co-located with 14th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE 2018), 2018

Counterfactual Multi-Agent Policy Gradients.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Fake News in Social Networks.
CoRR, 2017

Stabilising Experience Replay for Deep Multi-Agent Reinforcement Learning.
CoRR, 2017

Stabilising Experience Replay for Deep Multi-Agent Reinforcement Learning.
Proceedings of the 34th International Conference on Machine Learning, 2017

Input Switched Affine Networks: An RNN Architecture Designed for Interpretability.
Proceedings of the 34th International Conference on Machine Learning, 2017

2016
Intelligible Language Modeling with Input Switched Affine Networks.
CoRR, 2016

Learning to Communicate to Solve Riddles with Deep Distributed Recurrent Q-Networks.
CoRR, 2016

Learning to Communicate with Deep Multi-Agent Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016


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