16 citations · 56 across the 15 of their papers we have counts for
7 papers · 1 filter
Achieving Zero Constraint Violation for Constrained Reinforcement Learning via Primal-Dual Approach
Qinbo Bai, Amrit Singh Bedi, Mridul Agarwal +2
Reinforcement learning is widely used in applications where one needs to perform sequential decisions while interacting with the environment. The problem becomes more challenging w…
Concave Utility Reinforcement Learning with Zero-Constraint Violations
Mridul Agarwal, Qinbo Bai, Vaneet Aggarwal
We consider the problem of tabular infinite horizon concave utility reinforcement learning (CURL) with convex constraints. For this, we propose a model-based learning algorithm tha…
On the Approximation of Cooperative Heterogeneous Multi-Agent Reinforcement Learning (MARL) using Mean Field Control (MFC)
Washim Uddin Mondal, Mridul Agarwal, Vaneet Aggarwal +1
Mean field control (MFC) is an effective way to mitigate the curse of dimensionality of cooperative multi-agent reinforcement learning (MARL) problems. This work considers a collec…
Markov Decision Processes with Long-Term Average Constraints
Mridul Agarwal, Qinbo Bai, Vaneet Aggarwal
We consider the problem of constrained Markov Decision Process (CMDP) where an agent interacts with a unichain Markov Decision Process. At every interaction, the agent obtains a re…
Joint Optimization of Multi-Objective Reinforcement Learning with Policy Gradient Based Algorithm
Qinbo Bai, Mridul Agarwal, Vaneet Aggarwal
Many engineering problems have multiple objectives, and the overall aim is to optimize a non-linear function of these objectives. In this paper, we formulate the problem of maximiz…
Communication Efficient Parallel Reinforcement Learning
Mridul Agarwal, Bhargav Ganguly, Vaneet Aggarwal
We consider the problem where agents interact with identical and independent environments with states and actions using reinforcement learning for rounds. The a…
Multi-Agent Multi-Armed Bandits with Limited Communication
Mridul Agarwal, Vaneet Aggarwal, Kamyar Azizzadenesheli
We consider the problem where agents collaboratively interact with an instance of a stochastic arm bandit problem for . The agents aim to simultaneously minimize t…