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01/10/2023
Sequential Fair Resource Allocation under a Markov Decision Process Framework
We study the sequential decision-making problem of allocating a limited ...
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11/28/2022
Inapplicable Actions Learning for Knowledge Transfer in Reinforcement Learning
Reinforcement Learning (RL) algorithms are known to scale poorly to envi...
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10/13/2022
Towards Multi-Agent Reinforcement Learning driven Over-The-Counter Market Simulations
We study a game between liquidity provider and liquidity taker agents in...
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10/12/2022
Phantom – A RL-driven multi-agent framework to model complex systems
Agent based modelling (ABM) is a computational approach to modelling com...
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06/21/2022
Certifiably Robust Policy Learning against Adversarial Communication in Multi-agent Systems
Communication is important in many multi-agent reinforcement learning (M...
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01/05/2022
Mixture of basis for interpretable continual learning with distribution shifts
Continual learning in environments with shifting data distributions is a...
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10/13/2021
Towards a fully RL-based Market Simulator
We present a new financial framework where two families of RL-based agen...
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06/04/2021
Consensus Multiplicative Weights Update: Learning to Learn using Projector-based Game Signatures
Recently, Optimistic Multiplicative Weights Update (OMWU) was proven to ...
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02/20/2021
Causal Policy Gradients
Policy gradient methods can solve complex tasks but often fail when the ...
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06/23/2020
Calibration of Shared Equilibria in General Sum Partially Observable Markov Games
Training multi-agent systems (MAS) to achieve realistic equilibria gives...
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06/23/2020
Risk-Sensitive Reinforcement Learning: a Martingale Approach to Reward Uncertainty
We introduce a novel framework to account for sensitivity to rewards unc...
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11/14/2019