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08/25/2023
JAX-LOB: A GPU-Accelerated limit order book simulator to unlock large scale reinforcement learning for trading
Financial exchanges across the world use limit order books (LOBs) to pro...
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08/15/2023
Unbiased Decisions Reduce Regret: Adversarial Domain Adaptation for the Bank Loan Problem
In many real world settings binary classification decisions are made bas...
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07/03/2023
Learning to Communicate using Contrastive Learning
Communication is a powerful tool for coordination in multi-agent RL. But...
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05/26/2023
A Model-Based Solution to the Offline Multi-Agent Reinforcement Learning Coordination Problem
Training multiple agents to coordinate is an important problem with appl...
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03/16/2023
Arbitrary Order Meta-Learning with Simple Population-Based Evolution
Meta-learning, the notion of learning to learn, enables learning systems...
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03/07/2023
Structured State Space Models for In-Context Reinforcement Learning
Structured state space sequence (S4) models have recently achieved state...
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03/06/2023
MAESTRO: Open-Ended Environment Design for Multi-Agent Reinforcement Learning
Open-ended learning methods that automatically generate a curriculum of ...
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11/26/2022
Similarity-based Cooperation
As machine learning agents act more autonomously in the world, they will...
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11/20/2022
Adversarial Cheap Talk
Adversarial attacks in reinforcement learning (RL) often assume highly-p...
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10/24/2022
Perfectly Secure Steganography Using Minimum Entropy Coupling
Steganography is the practice of encoding secret information into innocu...
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10/21/2022
Equivariant Networks for Zero-Shot Coordination
Successful coordination in Dec-POMDPs requires agents to adopt robust st...
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10/11/2022
Discovered Policy Optimisation
Tremendous progress has been made in reinforcement learning (RL) over th...
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10/11/2022
Human-AI Coordination via Human-Regularized Search and Learning
We consider the problem of making AI agents that collaborate well with h...
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09/22/2022
An Investigation of the Bias-Variance Tradeoff in Meta-Gradients
Meta-gradients provide a general approach for optimizing the meta-parame...
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07/11/2022
Grounding Aleatoric Uncertainty in Unsupervised Environment Design
Adaptive curricula in reinforcement learning (RL) have proven effective ...
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06/26/2022
Generalized Beliefs for Cooperative AI
Self-play is a common paradigm for constructing solutions in Markov game...
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05/03/2022
Model-Free Opponent Shaping
In general-sum games, the interaction of self-interested learning agents...
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03/08/2022
COLA: Consistent Learning with Opponent-Learning Awareness
Learning in general-sum games can be unstable and often leads to sociall...
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03/02/2022
Evolving Curricula with Regret-Based Environment Design
It remains a significant challenge to train generally capable agents wit...
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01/29/2022
Learning to Coordinate with Humans using Action Features
An unaddressed challenge in human-AI coordination is to enable AI agents...
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01/07/2022
Mirror Learning: A Unifying Framework of Policy Optimisation
General policy improvement (GPI) and trust-region learning (TRL) are the...
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12/24/2021
Lyapunov Exponents for Diversity in Differentiable Games
Ridge Rider (RR) is an algorithm for finding diverse solutions to optimi...
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12/03/2021
Neural Pseudo-Label Optimism for the Bank Loan Problem
We study a class of classification problems best exemplified by the bank...
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10/06/2021
Replay-Guided Adversarial Environment Design
Deep reinforcement learning (RL) agents may successfully generalize to n...
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07/26/2021
Don't Sweep your Learning Rate under the Rug: A Closer Look at Cross-modal Transfer of Pretrained Transformers
Self-supervised pre-training of large-scale transformer models on text c...
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07/17/2021
Implicit Communication as Minimum Entropy Coupling
In many common-payoff games, achieving good performance requires players...
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07/14/2021
Centralized Model and Exploration Policy for Multi-Agent RL
Reinforcement learning (RL) in partially observable, fully cooperative m...
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06/16/2021
Learned Belief Search: Efficiently Improving Policies in Partially Observable Settings
Search is an important tool for computing effective policies in single- ...
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06/11/2021
A New Formalism, Method and Open Issues for Zero-Shot Coordination
In many coordination problems, independently reasoning humans are able t...
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03/14/2021
Quasi-Equivalence Discovery for Zero-Shot Emergent Communication
Effective communication is an important skill for enabling information e...
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03/06/2021
Off-Belief Learning
The standard problem setting in Dec-POMDPs is self-play, where the goal ...
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11/12/2020
Ridge Rider: Finding Diverse Solutions by Following Eigenvectors of the Hessian
Over the last decade, a single algorithm has changed many facets of our ...
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10/29/2020
Exploring Zero-Shot Emergent Communication in Embodied Multi-Agent Populations
Effective communication is an important skill for enabling information e...
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09/23/2020
The Struggles of Feature-Based Explanations: Shapley Values vs. Minimal Sufficient Subsets
For neural models to garner widespread public trust and ensure fairness,...
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03/19/2020
Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning
In many real-world settings, a team of agents must coordinate its behavi...
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03/06/2020
"Other-Play" for Zero-Shot Coordination
We consider the problem of zero-shot coordination - constructing AI agen...
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12/05/2019
Improving Policies via Search in Cooperative Partially Observable Games
Recent superhuman results in games have largely been achieved in a varie...
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10/24/2019
Capacity, Bandwidth, and Compositionality in Emergent Language Learning
Many recent works have discussed the propensity, or lack thereof, for em...
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09/23/2019
Loaded DiCE: Trading off Bias and Variance in Any-Order Score Function Estimators for Reinforcement Learning
Gradient-based methods for optimisation of objectives in stochastic sett...
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06/10/2019
A Survey of Reinforcement Learning Informed by Natural Language
To be successful in real-world tasks, Reinforcement Learning (RL) needs ...
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05/13/2019
Differentiable Game Mechanics
Deep learning is built on the foundational guarantee that gradient desce...
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03/12/2019
On the Pitfalls of Measuring Emergent Communication
How do we know if communication is emerging in a multi-agent system? The...
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02/11/2019
The StarCraft Multi-Agent Challenge
In the last few years, deep multi-agent reinforcement learning (RL) has ...
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11/20/2018
Stable Opponent Shaping in Differentiable Games
A growing number of learning methods are actually games which optimise m...
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09/19/2018
Pommerman: A Multi-Agent Playground
We present Pommerman, a multi-agent environment based on the classic con...
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03/30/2018
QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning
In many real-world settings, a team of agents must coordinate their beha...
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02/15/2018
The Mechanics of n-Player Differentiable Games
The cornerstone underpinning deep learning is the guarantee that gradien...
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02/14/2018
DiCE: The Infinitely Differentiable Monte-Carlo Estimator
The score function estimator is widely used for estimating gradients of ...
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08/21/2017
Fake News in Social Networks
We model the spread of news as a social learning game on a network. Agen...
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05/24/2017
