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07/25/2023
Counterfactual Explanation Policies in RL
As Reinforcement Learning (RL) agents are increasingly employed in diver...
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06/28/2023
SARC: Soft Actor Retrospective Critic
The two-time scale nature of SAC, which is an actor-critic algorithm, is...
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05/06/2023
Explaining RL Decisions with Trajectories
Explanation is a key component for the adoption of reinforcement learnin...
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07/20/2022
Differentiable Agent-based Epidemiology
Mechanistic simulators are an indispensable tool for epidemiology to exp...
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11/23/2021
Status-quo policy gradient in Multi-Agent Reinforcement Learning
Individual rationality, which involves maximizing expected individual re...
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10/09/2021
DeepABM: Scalable, efficient and differentiable agent-based simulations via graph neural networks
We introduce DeepABM, a framework for agent-based modeling that leverage...
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10/08/2021
Medical Dead-ends and Learning to Identify High-risk States and Treatments
Machine learning has successfully framed many sequential decision making...
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10/05/2021
Robustness and sample complexity of model-based MARL for general-sum Markov games
Multi-agent reinfocement learning (MARL) is often modeled using the fram...
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11/23/2020
An Empirical Study of Representation Learning for Reinforcement Learning in Healthcare
Reinforcement Learning (RL) has recently been applied to sequential esti...
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10/17/2020
Approximate information state for approximate planning and reinforcement learning in partially observed systems
We propose a theoretical framework for approximate planning and learning...
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01/15/2020
Inducing Cooperative behaviour in Sequential-Social dilemmas through Multi-Agent Reinforcement Learning using Status-Quo Loss
In social dilemma situations, individual rationality leads to sub-optima...
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04/03/2018