
Achieving Zero Constraint Violation for Constrained Reinforcement Learning via PrimalDual Approach
Reinforcement learning is widely used in applications where one needs to...
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Concave Utility Reinforcement Learning with ZeroConstraint Violations
We consider the problem of tabular infinite horizon concave utility rein...
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On the Approximation of Cooperative Heterogeneous MultiAgent Reinforcement Learning (MARL) using Mean Field Control (MFC)
Mean field control (MFC) is an effective way to mitigate the curse of di...
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Markov Decision Processes with LongTerm Average Constraints
We consider the problem of constrained Markov Decision Process (CMDP) wh...
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Joint Optimization of MultiObjective Reinforcement Learning with Policy Gradient Based Algorithm
Many engineering problems have multiple objectives, and the overall aim ...
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Communication Efficient Parallel Reinforcement Learning
We consider the problem where M agents interact with M identical and ind...
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MultiAgent MultiArmed Bandits with Limited Communication
We consider the problem where N agents collaboratively interact with an ...
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Blind Decision Making: Reinforcement Learning with Delayed Observations
Reinforcement learning typically assumes that the state update from the ...
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DART: aDaptive Accept RejecT for nonlinear topK subset identification
We consider the bandit problem of selecting K out of N arms at each time...
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Escaping Saddle Points for Zerothorder Nonconvex Optimization using Estimated Gradient Descent
Gradient descent and its variants are widely used in machine learning. H...
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Encoders and Decoders for Quantum Expander Codes Using Machine Learning
Quantum key distribution (QKD) allows two distant parties to share encry...
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A Reinforcement Learning Based Approach for Joint MultiAgent Decision Making
Reinforcement Learning (RL) is being increasingly applied to optimize co...
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Regret Bounds for Stochastic Combinatorial MultiArmed Bandits with Linear Space Complexity
Many realworld problems face the dilemma of choosing best K out of N op...
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Mridul Agarwal
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