46 citations · 52 across the 13 of their papers we have counts for
7 papers · 1 filter
Efficient Reinforcement Learning by Reducing Forgetting with Elephant Activation Functions
Qingfeng Lan, Gautham Vasan, A. Rupam Mahmood
Catastrophic forgetting has remained a significant challenge for efficient reinforcement learning for decades (Ring 1994, Rivest and Precup 2003). While recent works have proposed…
Deep Policy Gradient Methods Without Batch Updates, Target Networks, or Replay Buffers
Gautham Vasan, Mohamed Elsayed, Alireza Azimi +5
Modern deep policy gradient methods achieve effective performance on simulated robotic tasks, but they all require large replay buffers or expensive batch updates, or both, making…
Streaming Deep Reinforcement Learning Finally Works
Mohamed Elsayed, Gautham Vasan, Elena Sorina Lupu +1
Learning from a stream of experience as it arrives, also known as streaming learning, is a core part of natural learning. However, reliable streaming learning has remained a persis…
MaDi: Learning to Mask Distractions for Generalization in Visual Deep Reinforcement Learning
Bram Grooten, Tristan Tomilin, Gautham Vasan +5
The visual world provides an abundance of information, but many input pixels received by agents often contain distracting stimuli. Autonomous agents need the ability to distinguish…
Correcting discount-factor mismatch in on-policy policy gradient methods
Fengdi Che, Gautham Vasan, A. Rupam Mahmood
The policy gradient theorem gives a convenient form of the policy gradient in terms of three factors: an action value, a gradient of the action likelihood, and a state distribution…
Autoregressive Policies for Continuous Control Deep Reinforcement Learning
Dmytro Korenkevych, A. Rupam Mahmood, Gautham Vasan +1
Reinforcement learning algorithms rely on exploration to discover new behaviors, which is typically achieved by following a stochastic policy. In continuous control tasks, policies…
Benchmarking Reinforcement Learning Algorithms on Real-World Robots
A. Rupam Mahmood, Dmytro Korenkevych, Gautham Vasan +2
Through many recent successes in simulation, model-free reinforcement learning has emerged as a promising approach to solving continuous control robotic tasks. The research communi…