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12/14/2022
SMACv2: An Improved Benchmark for Cooperative Multi-Agent Reinforcement Learning
The availability of challenging benchmarks has played a key role in the ...
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10/28/2022
Game-Theoretical Perspectives on Active Equilibria: A Preferred Solution Concept over Nash Equilibria
Multiagent learning settings are inherently more difficult than single-a...
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10/11/2022
Learning to Optimize Quasi-Newton Methods
We introduce a novel machine learning optimizer called LODO, which onlin...
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07/20/2022
Illusionary Attacks on Sequential Decision Makers and Countermeasures
Autonomous intelligent agents deployed to the real-world need to be robu...
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07/14/2022
K-level Reasoning for Zero-Shot Coordination in Hanabi
The standard problem setting in cooperative multi-agent settings is self...
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03/07/2022
Influencing Long-Term Behavior in Multiagent Reinforcement Learning
The main challenge of multiagent reinforcement learning is the difficult...
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02/11/2020
Reinforcement Learning Enhanced Quantum-inspired Algorithm for Combinatorial Optimization
Quantum hardware and quantum-inspired algorithms are becoming increasing...
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12/04/2019
Simplified Action Decoder for Deep Multi-Agent Reinforcement Learning
In recent years we have seen fast progress on a number of benchmark prob...
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10/23/2019
Robust Domain Randomization for Reinforcement Learning
Producing agents that can generalize to a wide range of environments is ...
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09/09/2019
Exploratory Combinatorial Optimization with Reinforcement Learning
Many real-world problems can be reduced to combinatorial optimization on...
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02/01/2019
The Hanabi Challenge: A New Frontier for AI Research
From the early days of computing, games have been important testbeds for...
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11/04/2018
Bayesian Action Decoder for Deep Multi-Agent Reinforcement Learning
When observing the actions of others, humans carry out inferences about ...
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10/27/2018
Multi-Agent Common Knowledge Reinforcement Learning
In multi-agent reinforcement learning, centralised policies can only be ...
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09/13/2017
Learning with Opponent-Learning Awareness
Multi-agent settings are quickly gathering importance in machine learnin...
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11/28/2016
Input Switched Affine Networks: An RNN Architecture Designed for Interpretability
There exist many problem domains where the interpretability of neural ne...
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02/08/2016
