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08/21/2023
Stabilizing Unsupervised Environment Design with a Learned Adversary
A key challenge in training generally-capable agents is the design of tr...
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06/15/2023
Who Needs to Know? Minimal Knowledge for Optimal Coordination
To optimally coordinate with others in cooperative games, it is often cr...
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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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08/15/2022
Cooperative and uncooperative institution designs: Surprises and problems in open-source game theory
It is increasingly possible for real-world agents, such as software-base...
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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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05/15/2022
Sociotechnical Specification for the Broader Impacts of Autonomous Vehicles
Autonomous Vehicles (AVs) will have a transformative impact on society. ...
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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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10/06/2021
Replay-Guided Adversarial Environment Design
Deep reinforcement learning (RL) agents may successfully generalize to n...
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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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06/07/2021
Improving Social Welfare While Preserving Autonomy via a Pareto Mediator
Machine learning algorithms often make decisions on behalf of agents wit...
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01/25/2021
Accumulating Risk Capital Through Investing in Cooperation
Recent work on promoting cooperation in multi-agent learning has resulte...
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12/03/2020
Emergent Complexity and Zero-shot Transfer via Unsupervised Environment Design
A wide range of reinforcement learning (RL) problems - including robustn...
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06/24/2020
Quantifying Differences in Reward Functions
For many tasks, the reward function is too complex to be specified proce...
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05/25/2019
Adversarial Policies: Attacking Deep Reinforcement Learning
Deep reinforcement learning (RL) policies are known to be vulnerable to ...
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10/31/2017
